Multivitamin supplementation in an older population: the impact … · 2017. 2. 6. · Swisse...

Multivitamin Supplementation in an

Older Population: The Impact on

Mood

Renee Rowsell

Doctor of Philosophy

Swinburne University

Melbourne, Australia

2016

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Abstract

Our population is ageing, and with that comes a greater social and economic burden on

society in terms of mental and neurological health services. In Australia, 14% of the

population is aged over 65 years. Therefore, novel and inexpensive ways to reduce the

financial burden associated with ageing and improve the quality of life of older

individuals is paramount. Adequate nutrition is important for the regulation of mood

and quality of life, particularly in older population groups. Multivitamin and mineral

(MVM) supplementation would seem a cheap, easy way for individuals to enhance their

vitamin and nutrient intake.

Data from epidemiological studies suggest that the elderly are likely to benefit from

MVM supplementation; however, there is a paucity of randomised controlled trials

(RCTs) in older groups. RCTs in more vulnerable groups suggest a potential role for

multivitamins in improving mood. Only one study has been conducted in a healthy

older sample, with null results. This thesis presents the results from two randomised

controlled trials of multivitamin, mineral and herbal supplements. These trials aimed to

examine both the chronic (long-term) and acute (more immediate) effects of MVM’s in

a healthy older group, in order to address the lack of information regarding the efficacy

of MVM supplementation in healthy older individuals.

The first trial investigated 16 weeks of chronic MVM supplementation in healthy men

and women aged 50-78 years. Mood, cardiovascular function and blood biomarkers

were assessed at baseline and follow-up sessions. The tests included self-reported mood

assessments, measures of peripheral and central blood pressure, including arterial

stiffness, and blood markers of vitamin status, inflammation, homocysteine and general

health markers. To date, no study has investigated the acute actions of multivitamin in

an older group. Therefore, the second study investigated the acute and chronic effects

of supplementation with a multivitamin, mineral and herbal supplement in healthy older

women aged 50-75 years. Assessments of mood and cardiovascular function were

conducted at baseline, 1-2 hours post dose, and at 4-weeks follow-up. The tests were

similar to those used in the first study, but also included an acute testing phase where

mood was assessed 1-2 hours post supplement ingestion.

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Chronic MVM supplementation had no effect on mood or cardiovascular function.

However, the analysis of blood biomarkers revealed positive changes as a result of

supplementation. This included increases in B12, folate and B6, and reductions in

homocysteine. Additionally, increases in folate levels were associated with a reduction

in mental fatigue. Acute benefits to mood were observed in the second study indicating

that the MVM was effective in improving mood more immediately, with particular

influence on self-reported stress.

Despite no longer-term benefits to mood and cardiovascular health in this healthy older

cohort, the results from both the blood biomarkers and the acute mood improvements

suggest a possible role for MVM’s in reducing risk factors of cardiovascular disease and

mood dysfunction, as well as more immediate improvements in mood and stress. The

design of both chronic studies required that participants abstain from supplementing on

the morning of testing. This requirement to eliminate possible acute effects has not

always been stipulated in previous studies. The present findings therefore indicate that

in a healthier population, MVM supplementation may be more effective for improving

mood in the hours following ingestion and not necessarily through accumulative effects

over time. However, future studies should explore potential chronic mood effects

beyond 16 weeks.

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Acknowledgements

Firstly I would like to thank my supervisor, A.Prof Andrew Pipingas, for not only

putting up with me for so many years, but whose expertise, kindness, and

encouragement, made this thesis possible. Not all PhD students have a supervisor as

dedicated and hard working as Andrew, so I am extremely thankful.

Thank you to my parents and sisters, who believed in me, and supported me through my

entire PhD, and who so often offered to look after Ava so I could work, words cannot

express how much that means to me. And thanks to Dad who kindly offered to proof

read this thesis.

To the CHP team, particularly Prof Andrew Scholey and Prof Con Stough, thank you

for providing such a supportive group, where PhD students are valued as an integral part

of the centre. Working with CHP has enabled me to develop my research skills way

beyond what many students are able to achieve during their candidature. I would

especially like to thank Dr David White, Rebecca King, Katharine Cox, Dr Luke

Downey, Dr Amie Hayley and Dr Elizabeth Harris for their unwavering support and

encouragement.

Thank you to Dr Helen Macpherson, who has been a great support to me throughout my

entire PhD. The study reported in chapter 6, was conducted as part of Helen’s post-

doctoral research during her time at CHP, and I thank her for allowing me to be

involved in the project, and allowing me to report some of the data in my thesis.

I am also grateful to Swisse Vitamin Pty Ltd, who provided the funding and

supplements for both clinical trials presented in this thesis. Swisse Vitamins also

funded my PhD scholarship, which gave me the means to complete the projects.

I would also like to thank my husband Chris, and daughter Ava who have supported and

encouraged me through my entire candidature.

Lastly, I would like to thank my Pa. From the first day of my undergrad, he called me

“Doc”. He always believed that I would one day become the first doctor in the family.

Thank you for believing in me, I only wish you were still here to see it.

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Declaration

I certify that except where due acknowledgement has been made, the work is that of the

author alone; the work has not been submitted previously, in whole or in part, to qualify

for any other academic award; the content of the thesis is the result of work which has

been carried out since the official commencement date of the approved research

program; any editorial work, paid or unpaid, carried out by a third party is

acknowledged; and, ethics procedures and guidelines have been followed.

Renee Rowsell

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Table of Contents

Chapter 1 Introduction and Overview .................................................................... 21

Chapter 2 Clinical Mood, Mood Symptoms, Stress and Fatigue ............................ 27

2.1 Clinical Depressive Disorders ................................................................................27 2.1.1 Clinical Depression in the Elderly ....................................................................................30 2.1.2 Minor, Sub-Syndromal or Sub-Threshold Depression .......................................................33

2.2 The Neurobiology of Depression ...........................................................................35 2.2.1 Depression and the Brain .................................................................................................35 2.2.2 Brain Neurochemistry and Monoamine Dysfunction in Depression ...................................37 2.2.3 The role of inflammation in depression .............................................................................40

2.3 Anxiety Disorders ..................................................................................................41 2.3.1 Anxiety in the Elderly ......................................................................................................43 2.3.2 Sub-threshold Anxiety .....................................................................................................44

2.4 The Neurobiology of Anxiety .................................................................................45 2.4.1 Anxiety and the Brain ......................................................................................................45 2.4.2 Brain Neurochemistry and Anxiety ..................................................................................46

2.5 The Co-morbidity of Anxiety and Depression ......................................................47

2.6 Stress. .....................................................................................................................49 2.6.1 The Body’s Response to Stress: The Activation of the HPA Axis......................................49

2.7 Fatigue ....................................................................................................................51

2.8 Cardiovascular Health and Mood .........................................................................53

2.9 Summary and Conclusion......................................................................................55

Chapter 3 Micronutrients and Mood...................................................................... 59

3.1 Introduction ...........................................................................................................59

3.2 The Influence of Diet and Nutritional Intake on Mood ........................................61

3.3 Vitamins, Minerals and Mood ...............................................................................65 3.3.1 Vitamins, Nutrition and Cardiovascular Health .................................................................67

3.4 B Vitamins and Homocysteine ...............................................................................68 3.4.1 Vitamin B12 .....................................................................................................................70 3.4.2 Vitamin B9 (Folate) .........................................................................................................71 3.4.3 Vitamin B6 .......................................................................................................................73 3.4.4 Homocysteine ..................................................................................................................74

3.5 The Relationship between B Vitamins, Homocysteine and Mood in the Elderly. 77 3.5.2 B-Vitamin interventions for improving mood ...................................................................81

3.6 Vitamin D ...............................................................................................................88

3.7 Vitamin A ...............................................................................................................90

3.8 Antioxidant Vitamins and Oxidative Stress ..........................................................90 3.8.1 Vitamin E: .......................................................................................................................91 3.8.2 Vitamin C: .......................................................................................................................92 3.8.3 The Synergistic Effects of Vitamins C and E: ...................................................................92

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3.9 Minerals ................................................................................................................. 93 3.9.1 Calcium .......................................................................................................................... 93 3.9.2 Chromium ....................................................................................................................... 94 3.9.3 Zinc ................................................................................................................................ 94 3.9.4 Magnesium ..................................................................................................................... 96 3.9.5 Selenium ......................................................................................................................... 97

3.10 Phytonutrients and Herbal extracts ...................................................................... 97

3.11 Summary and Conclusion ..................................................................................... 98

Chapter 4 The influence of Multi-Nutrient Interventions on Mood in Healthy Individuals 99

4.1 Introduction ........................................................................................................... 99

4.2 Micronutrient supplementation and Mood: Results from Randomised Controlled Trials 101

4.2.1 Multivitamins and Mood ............................................................................................... 101 4.2.2 Multivitamin Supplementation and mood in Older Adults .............................................. 102 4.2.3 Multivitamins and Mood in Younger Groups ................................................................. 107 4.2.4 Acute Effects of Multivitamin Supplementation: Results from RCTs .............................. 112 4.2.5 Summary of Multivitamin RCT Findings ....................................................................... 113

4.3 Summary.............................................................................................................. 113

4.4 Thesis aims and rationale .................................................................................... 114

Chapter 5 The Effects of Chronic Multivitamin Supplementation in Healthy Older Adults: Mood, Cardiovascular Function and Blood Biomarkers ............................. 117

5.1 Introduction ......................................................................................................... 117

5.2 Aims and hypotheses: .......................................................................................... 120

5.3 Methods ............................................................................................................... 121

5.4 Participant Characteristics ................................................................................. 122 5.4.1 Screening ...................................................................................................................... 122 5.4.2 Screening Measures ....................................................................................................... 124 5.4.3 Participant baseline demographics and morphometrics ................................................... 124

5.5 Trial design, randomisation and blinding procedures ....................................... 125 5.5.1 Treatment ...................................................................................................................... 125

5.6 Measures .............................................................................................................. 129 5.6.1 The Depression, Anxiety and Stress Scale ...................................................................... 129 5.6.2 The Beck Depression Inventory ..................................................................................... 129 5.6.3 The Beck Anxiety Inventory .......................................................................................... 129 5.6.4 The Hospital Anxiety and Depression Scale ................................................................... 130 5.6.5 The Perceived Stress Scale ............................................................................................ 130 5.6.6 The General Health Questionnaire ................................................................................. 130 5.6.7 The Chalder Fatigue Scale ............................................................................................. 130 5.6.8 Pittsburgh Sleep Quality Index ...................................................................................... 131 5.6.9 The State-Trait Anxiety Inventory ................................................................................. 131 5.6.10 The Bond-Lader Visual analogue scales..................................................................... 132 5.6.11 Stress and fatigue visual analogue scales.................................................................... 132 5.6.12 The NASA Task Load Index ..................................................................................... 132

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5.6.13 Purple Multitasking Research Framework .................................................................. 132 5.6.14 Cardiovascular and Haematological measures ............................................................ 134

5.7 Pre- and Post-treatment testing procedure ......................................................... 138

5.8 Statistical analysis ................................................................................................ 140

5.9 Results .................................................................................................................. 141 5.9.1 Participant Demographics .............................................................................................. 141 5.9.2 Concurrent medications and supplements ....................................................................... 141 5.9.3 Compliance.................................................................................................................... 141 5.9.4 Treatment Evaluation ..................................................................................................... 142 5.9.5 Treatment side effects .................................................................................................... 142

5.10 Baseline Biochemical results ................................................................................ 142

5.11 The Treatment Effects of Multivitamin Supplementation .................................. 144 5.11.2 The Effect of Multivitamins on Stress Reaction. ......................................................... 148 5.11.3 Haematological Biomarkers ....................................................................................... 149 5.11.4 The change in blood biomarkers verses the change in mood........................................ 157 5.11.5 Cardiovascular Results ............................................................................................... 159

5.12 Discussion ............................................................................................................. 161 5.12.1 The Relationship between Blood Nutrient Levels and Mood at Baseline ..................... 162 5.12.2 Effects of multivitamin supplementation on mood ...................................................... 163 5.12.3 Multivitamins and Stress reaction ............................................................................... 165 5.12.4 Multivitamin Supplementation and Blood Biomarkers ................................................ 167 5.12.5 Multivitamins and Cardiovascular Health. .................................................................. 172 5.12.6 The Action of Multivitamins on Neurotransmitter Production. .................................... 174

5.13 Limitations and future directions ........................................................................ 175

5.14 Summary and Conclusion.................................................................................... 176

Chapter 6 The Acute and Chronic effects of Multivitamin Supplements: The BEMS study in women. ............................................................................................ 179

6.1 Introduction ......................................................................................................... 179

6.2 Aims and hypotheses: .......................................................................................... 181

6.3 Methods ................................................................................................................ 183

6.4 Participant Characteristics .................................................................................. 183 6.4.1 Screening ....................................................................................................................... 183 6.4.2 Screening Measures ....................................................................................................... 185 6.4.3 Participant baseline demographics .................................................................................. 186

6.5 Trial design, randomisation and blinding procedures ........................................ 186 6.5.1 Treatment ...................................................................................................................... 186 6.5.2 Determination of Sample size ......................................................................................... 187

6.6 Measures .............................................................................................................. 189 6.6.1 Mobile phone measures .................................................................................................. 189 6.6.2 Mood measures .............................................................................................................. 189 6.6.3 Wellbeing and energy .................................................................................................... 191 6.6.4 Cardiovascular Measures ............................................................................................... 191

6.7 Procedures............................................................................................................ 192

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6.8 Statistical analysis ................................................................................................ 194

6.9 Results .................................................................................................................. 194 6.9.1 Participant demographics ............................................................................................... 194 6.9.2 Chronic Treatment effects.............................................................................................. 196 6.9.3 Acute effects of Treatment on Mood .............................................................................. 198

6.10 Discussion ............................................................................................................ 201 6.10.1 Chronic effects .......................................................................................................... 201 6.10.2 Acute effects ............................................................................................................. 203 6.10.3 Cardiovascular function ............................................................................................. 204 6.10.4 Limitations and Future directions .............................................................................. 206 6.10.5 Summary and Conclusion .......................................................................................... 207

Chapter 7 General Discussion .............................................................................. 209

7.1 Summary of Key findings .................................................................................... 209 7.1.1 Chronic multivitamin supplementation: effects on mood in older individuals .................. 209 7.1.2 Acute and Chronic Multivitamin Supplementation: Effects on Mood in Older Women ... 210

7.2 Acute verses Chronic Multivitamin Supplementation........................................ 211

7.3 Multivitamin formulations, dosage and duration. .............................................. 215

7.4 Physiological effects of multivitamin supplementation ...................................... 218

7.5 The Benefit versus Risk of Multivitamin Supplementation. .............................. 221

7.6 Limitations and Future Directions ...................................................................... 225

7.7 Summary and Conclusion ................................................................................... 226

Chapter 8 References ........................................................................................... 229

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List of Tables

Table 2-1. DSM-5 Depressive Disorder and Bipolar and Related Disorders (American Psychiatric Association, 2013) ................................................................................................28 Table 2-2. The risk factors associated with depression in the elderly (Cole and Dendukuri, 2003; Birrer, DeLisi et al., 2007) .......................................................................................................32 Table 2-3. Anxiety, Obsessive Compulsive and Trauma- and Stressor related disorders as categorised in the DSM-V (American Psychiatric Association, 2013). ......................................42 Table 3-1. The B Group vitamins along with their traditional names. .......................................69 Table 3-2. Summary of the B vitamin trials that have investigated mood. ................................84 Table 4-1. Summary of Chronic MVM Trials conducted in older participants ........................ 104 Table 4-2. A comparison of the supplement ingredients across the studies in the elderly ........ 105 Table 4-3. Summary of MVM studies with younger participants............................................ 109 Table 4-4. Supplement characteristics for RCTs in younger samples...................................... 110 Table 5-1 Participant demographics and morphometrics at baseline ....................................... 125 Table 5-2: Ingredients of the multivitamin and daily doses for Men ....................................... 127 Table 5-3: Ingredients of the multivitamin and daily doses for women ................................... 128 Table 5-4 – Baseline multivitamin and placebo group demographics. .................................... 141 Table 5-5 Correlation Coefficients (r) for Baseline Mood and Biochemical measures ............ 143 Table 5-6 – Means, standard deviations and interaction values for the mood, stress and fatigue scales .................................................................................................................................... 147 Table 5-7. Means and Standard Deviations of the pre- and post-stressor measures ................. 149 Table 5-8 - Means and Standard Deviations of Haematological Safety Measures at Baseline and Post-Treatment ...................................................................................................................... 151 Table 5-9. Means and Standard Deviations for the B vitamins and homocysteine at baseline and post-treatment. ...................................................................................................................... 152 Table 5-10. Zinc and Vitamin E: means and standard deviations at baseline and follow-up .... 156 Table 5-11. Inflammation and Cholesterol Profile: Means and Standard Deviations ............... 156 Table 5-12. Correlation Coefficients (r) for the change from baseline scores ......................... 158 Table 5-13 - Means and standard deviations for cardiovascular measurements at baseline and follow-up. ............................................................................................................................. 160 Table 6-1 - Participant demographics and morphometrics at baseline ..................................... 186 Table 6-2 - Constituents of the multivitamin treatment .......................................................... 188 Table 6-3 - Baseline multivitamin and placebo group demographics and morphometrics ....... 195 Table 6-4. Means,Standard Deviations and Interaction Values for the Chronic Mood Measurements ....................................................................................................................... 197 Table 6-5 - Means and Standard Deviations and Interaction Values for Cardiovascular Parameters pre and post treatment ......................................................................................... 198 Table 6-6. Means, Standard Deviations and Interaction Values for Acute Mood Assessments 199

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List of Figures

Figure 2-1. The inter-relationships of monoamine neurotransmitters and behavioural responses (adapted from Nemeroff, 2002) ...............................................................................................38 Figure 2-2. Diagrammatic representation of the HPA axis. Adapted from (Hećimović and Gilliam 2006). .........................................................................................................................51 Figure 3-1 - The impact of selected vitamins on neurotransmitter synthesis via amino acid metabolism. Taken from Huskisson et al. (2007a)...................................................................70 Figure 3-2 - The folate and Homocysteine-methionine cycle. Adapted from Malouf and Grimley Evans (2008). ..........................................................................................................................75 Figure 5-1. Participant recruitment flowchart ......................................................................... 123 Figure 5-2: Screenshot of the Purple Multi-tasking Framework ............................................. 134 Figure 5-3. Estimated marginal means for HADS anxiety scale ............................................. 146 Figure 5-4. Estimated marginal means for HADS depression scale ........................................ 146 Figure 5-5. Mean Vitamin B12 concentrations for the multivitamin and placebo groups. Error bars show ± 1 standard error. ................................................................................................. 153 Figure 5-6. Mean Folate concentrations for the multivitamin and placebo groups. Error bars show ± 1 standard error. ........................................................................................................ 154 Figure 5-7. Mean B6 concentrations for the multivitamin and placebo groups. Error bars show ± 1 standard error. .................................................................................................................... 154 Figure 5-8. Mean homocysteine concentrations for the multivitamin and placebo groups. Error bars show ± 1 standard error. ................................................................................................. 155 Figure 5-9. Scatterplot of the relationship between the change in red blood cell folate and the change in mental fatigue. ....................................................................................................... 159 Figure 6-1. Participant recruitment flowchart ......................................................................... 185

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Glossary of Abbreviations

ABS Australian Bureau of Statistics

ACTH Adrenocorticotropic hormone

ADHD Attention-Deficit/Hyperactivity Disorder

AE Adverse Event

ALP Alkaline Phosphate

ALT Alanine aminotransferase

APA American Psychiatric Association

AST Aspartate aminotransferase

BAI Beck Anxiety Inventory

BDI Beck Depression Inventory

BDNF Brain-derived neurotrophic Factor

BMI Body Mass Index

BSI Berocca Stress Index

CDR Cognitive Drug Research

CES-D Centre for Epidemiological Studies – Depression Scale

CFS Chalder Fatigue Scale

CNS Central Nervous System

CRH Corticotropin-releasing Hormone

CRP C-Reactive Protein

CSF Cerebrospinal Fluid

CVD Cardiovascular Disease

DALY Disability-Adjusted Life Year

DASH Dietary Approaches to Stop Hypertension

DASS Depression Anxiety and Stress Scale

DSM Diagnostic and Statistical Manual of Mental Disorders

EAR Estimated Average Requirement

ECT Electroconvulsive therapy

eGFR Glomerular filtration rate - estimate

GABA Gamma-aminobutyric Acid

GAD Generalised Anxiety Disorder

GDS Geriatric Depression Scale

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GGT Gamma-glutamyl transpeptidase

GSH Glutathione

HADS Hospital Anxiety and Depression Scale

HARS Hamilton Anxiety Rating Scale

HDL High-density lipoprotein

HPA Hypothalamic-pituitary-adrenal axis

hsCRP High sensitivity C-Reactive Protien

I&ND Inflammation and Neurodegenerative

LDL Low-density lipoprotein

MADRS Montgomery-Åsberg Depression Rating Scale

MAO Monoamine Oxidase

MCI Mild Cognitive Impairment

MDD Major Depressive Disorder

MI Myocardial Infarction

MIND Mediterranean-DASH diet Intervention for Neurodegenerative Delay

MMA Methylmalonic acid

MMSE Mini Mental State Examination

MRC Medical Research Council

MRI Magnetic Resonance Imaging

MTF Multi-Tasking Framework

MTHF Methyltetrahydrofolate

MVM Multivitamin and mineral

NART-R National Adult Reading Test-Revised

NASA-TLX NASA Task Load Index

NHMRC National Health and Medical Research Council

NMDA N-methyl-D-aspartate

OCD Obsessive Compulsive Disorder

OSI-R Occupational Stress Inventory-Revised

PATH Personality and Total Health

PGA Pteroyl Glutamic Acid

PGWS Psychological General Well-being Schedule

PILL Pennebaker Inventory of Limbic Languidness

PLP Pyridoxal 5’-phosphate

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PMS Premenstrual Syndrome

PNAS Positive and Negative Affect Schedule

POMS Profile of Mood States

PSQ Personal Strain Questionnaire

PSQI Pittsburgh Sleep Quality Index

PSS Perceived Stress Scale

PTSD Post-Traumatic Stress Disorder

RBC Red blood cell

RCT Randomised Controlled Trial

RDA Recommended Daily Allowance

RDI Recommended Dietary Intake

SAH S-adenosylhomocysteine

SAMe S-adenosylmethionine

SF-36 Short-Form 36

SNRI Selective norepinephrine reuptake inhibitor

SNS Sympathetic nervous system

SSRI Selective serotonin reuptake inhibitor

STAI State-Trait Anxiety Inventory

SUHREC Swinburne University Human Research Ethics Committee

TGA Therapeutic Goods Administration

THF Tetrahydrofolate

VAS Visual Analogue Scale

VicHealth Victorian Health Promotion Foundation

WHO World Health Organisation

YLD Years of Life Lost to Disability

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Chapter 1 Introduction and Overview

Rapid population ageing in the Western world is a cause for concern. In the United

States and the United Kingdom, 15% of the population is made up of individuals aged

over 65 years (Crews and Zavotka, 2006). These numbers are expected to increase

exponentially in the next 50 years. With the ageing population comes greater financial

and health consequences. The Australian Bureau of Statistics (ABS) reported that 14%

of the Australian population in 2013 was made up of those aged over 65 (Australian

Bureau of Statistics, 2013). This figure is estimated to increase to 22% in 2061, and

then increase further to 25% in 2101 (ABS, 2013). Additionally, in 2012, those aged

over 85 made up 2% of the Australian population, again, the figures are projected to

increase to 5% in 2061, and 6% in 2101 (ABS, 2013). As the population ages, the

financial, social and personal burdens increase. The figures projected by the ABS

predict a future where the costs and burdens on health services and the like only

increase further.

In Australia, depressive illness is the most common mental illness, and a major public

health problem (Hawthorne, Cheok et al., 2003). The Australian Burden of Disease

study (ABD) listed mental disorders as the main cause of disability, accounting for

almost 30% of total years of life lost to disability (YLD). Of this, 8% was attributed to

depression alone (Mathers, Vos et al., 2001). Furthermore, the World Health

Organisation (WHO) has listed unipolar depression as the leading global cause of YLD

in 2011, and anxiety as the fifth leading cause of YLD (World Health Organisation,

2013). Additionally, unipolar depression is number 10 on the disability-adjusted life

year (DALY) list, a summary measure of population health (Mathers, Vos et al., 2001).

A DALY equates to a year of “healthy” life lost due to disease, and allows for the

measurement of the burden of disease in the population as the gap between current

health and ideal health (WHO, 2013).

As we age, we become more vulnerable and susceptible to disease and disability

(Cassidy, Kotynia-English et al., 2004). For instance, in Australia, depression and

dementia are two commonly reported mental health disorders in the elderly, and as such

are the two most common causes of YLD (Cassidy, Kotynia-English et al., 2004).

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Reports of the prevalence of depression in those aged over 65 years are wide ranging.

Population studies have estimated prevalence to range between 1% to 20 % (Steffens,

Skoog et al., 2000), with some studies reporting prevalence statistics up to 46%,

depending on the setting in which they are recorded (Djernes, 2006). These figures are

predicted to increase by 60% by 2020 (Birrer, DeLisi et al., 2007). Birrer et al. (2007)

suggest that the rate of recurrence in elderly populations could be as high as 40%, but

the actual figures are lower than that of the younger population, due to reporting of

somatic symptoms in the elderly, or the interference of cognitive impairment with the

accuracy of reporting. The economic burden of depression is high in developed

countries (Luppa, Heinrich et al., 2007). In 1990, the annual direct and indirect cost of

depression in the US was equal to that of coronary heart disease (Approx. US$43

billion). In 1998, it had increased to an estimated US$60 billion per annum (Berto,

D'Ilario et al., 2000). By 2005, these figures had increased to just over US$66 billion,

and further increased to approximately US$80 billion in 2010 (Greenberg, Fournier et

al., 2015).

Until recently, it was assumed that the prevalence of anxiety symptoms and disorders in

the elderly was much lower than those in younger groups (Flint, 1994) and as such,

anxiety in the elderly had received much less attention than depression. However,

researchers are now suggesting that anxiety symptoms and anxiety disorders present

differently in older patients, and are often obscured or missed completely by healthcare

professionals, due to the tendency of elderly patients to somaticise, or convert their

anxiety symptoms into physical symptoms (Fuentes and Cox, 1997). The prevalence

statistics for anxiety disorders within community samples range between 1.2% to 14%,

whereas anxiety symptoms are estimated to have prevalence as high as 24% in elderly

populations (Bryant, Jackson et al., 2008).

There is increasing evidence of diet and lifestyle factors influencing morbidity and

mortality as we age (de Groot and Van Staveren, 2010). An adequate supply of

nutrients is essential for neurological health and function (Bodnar and Wisner, 2005).

Additionally, epidemiological and prospective studies have highlighted the importance

of adequate nutritional status in the regulation of mood and quality of life, particularly

in older populations (Brownie, 2006). Furthermore, this research has highlighted the

importance of a healthy diet, whereby diets rich in fruit and vegetables reduce the risk

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of mortality, cardiovascular disease mortality and the risk of cancer. For example,

eating a Mediterranean style diet has been associated with reducing these risks (Sofi,

Cesari et al., 2008). Researchers suggest that the high levels of micronutrients,

monounsaturated fatty acids, omega-3 fatty acids, polyphenols and anti-oxidants within

the diet play a key role in the health benefits received (Detopoulou, Demopoulos et al.,

2015). The elderly are more at risk of developing micronutrient deficiencies than

younger adults. Poor nutritional status is associated with increased utilisation of health

care services, immune dysfunction, and is a risk factor for increased morbidity and

mortality (Brownie, 2006). The brain, as the most metabolically active organ in the

body may be the first to show signs of sub optimal nutritional status (Benton, 2013).

Furthermore, Benton (2013) suggests including psychological assessments, such as

mood and quality of life, as well as physiological measures, as a tool for investigating

optimal dietary intake.

The use of multivitamin and mineral (MVM) supplements is increasing, particularly in

the elderly (Rock, 2007). MVMs are among the most common forms of supplements

used to enhance the diet (Radimer, Bindewald et al., 2004; Nahin, Fitzpatrick et al.,

2006). This is particularly evident in elderly Australians, where MVMs are the most

common supplement used (Goh, Vitry et al., 2009). A recent meta-analysis conducted

by Long and Benton (2013) has found that MVM supplementation may also benefit

those in the general population in good health. Even small inadequacies in the diet can

negatively impact mood states, as slight decreases in nutrient status can disrupt the

efficiency of enzymes within the brain, and cumulatively affect mood (Benton, 2013).

The findings suggest that MVM supplementation in healthy individuals can help to

reduce perceived stress, mild psychiatric symptoms, anxiety, fatigue and confusion.

Despite these findings, very few studies have investigated the effects of MVM

supplementation, particularly in the elderly. To date, the acute effects of MVMs on

mood have not been studied in older individuals. As a group, the elderly are more

susceptible to a compromised nutritional state, and would likely benefit from MVM

interventions. Benton (2013), proposed that psychiatric symptoms are likely to be the

first sign of vitamin deficiency, evident even in those that are otherwise healthy.

Coupled with the growing popularity of MVM preparations, it is surprising that this

area has not been more thoroughly investigated.

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This thesis presents the results from two separate clinical trials. The first study was a

16-week, randomised, double-blind, placebo-controlled trial, that investigated the

effects of a multivitamin, mineral and herbal supplement on aspects of mood and

cardiovascular health in 84 healthy older adults aged between 50 and 78 years. The

second study investigated both the acute and chronic effects of MVM supplementation

in 76 healthy older women aged between 50 and 75 years. This trial was a four-week

randomised, double-blind, placebo-controlled trial.

This thesis comprises seven chapters. Chapter 1 provides a brief background and

introduction to the thesis. Chapter 2 provides the background rationale for investigating

ways in which mood can be improved in an older population. This chapter gives a brief

introduction to depression and anxiety disorders, and how they manifest in the elderly.

A basic overview of the neurobiology of depression and anxiety disorders is provided in

order to provide a general understanding of one of the proposed mechanisms of mood

disturbance. Additionally, the impact of stress and fatigue and how these conditions

manifest in the elderly is explored. The chapter concludes with a review of the

relationship between cardiovascular function and mood.

Chapter 3 examines the role that vitamins play in the maintenance of mood. A general

overview of the role that each vitamin and mineral of interest has within the body is

presented, with a focus on the B vitamins, as well as the main antioxidants and

minerals. Correlational and epidemiological research investigating the role of B

vitamins and homocysteine in mood regulation is presented. The aim of this chapter is

to provide an understanding of how vitamins and minerals influence mood, and how

even small changes in nutritional status can become problematic.

The focus of Chapter 4 is more specific, providing detailed reviews of randomised

controlled trials that have investigated the effects of vitamins on mood. An overview of

randomised controlled trials that have investigated the effects of B vitamin

supplementation on mood is provided. Following this, an exhaustive review of the

literature with regards to MVMs and mood is presented. Given that the influence of

MVMs may differ in the elderly compared to younger groups, due to the natural ageing

process, the evidence from these studies are examined separately. Another justification

for examining these trials separately is that the elderly are more susceptible to

nutritional deficiencies; therefore the potential of nutritional interventions to elicit

25

improvements in mood and general health is greater in older groups. The Chapter is

concluded with an overview of trials that have investigated the acute (short-term) effects

of MVM supplementation.

The two chapters that follow comprise the original research investigations. The study

presented in Chapter 5 was a randomised controlled trial investigating the effects of 16-

week MVM supplementation on mood and cardiovascular health in healthy, older

adults. The study in Chapter 6 is a randomised controlled trial, in which both the acute

(short-term) as well as the chronic (longer-term) effects of 4-weeks MVM

supplementation on mood was investigated in a group of healthy older women.

A discussion of the findings from both experimental chapters is contained in Chapter 7.

This chapter will also consider the broader implications of the research conducted, and

discuss limitations of this research and future directions for ongoing research.

26


27

Chapter 2 Clinical Mood, Mood Symptoms, Stress and Fatigue This chapter provides an overview of depressive and anxiety disorders, the prevalence

and aetiology of these disorders, as well as how they present in elderly populations.

The prevalence and aetiology of stress and fatigue will also be presented. This chapter

will also describe the sub-clinical presentation of anxiety and depression, particularly

focusing on the elderly, as well as discussing the presentation of anxiety and depressive

symptoms in healthy, older population groups.

The purpose of this chapter is to provide a general understanding of depression and

anxiety and how they manifest in the elderly. An overview of clinical depression and

anxiety with particular emphasis on the elderly is provided. A brief discussion of sub-

threshold anxiety and depressive disorders, with particular emphasis on the elderly

population is also presented. A basic overview of the neurobiology of depression and

anxiety disorders is provided in order to provide a general understanding of one of the

proposed mechanisms of mood disturbance.

The latter part of the chapter is comprised of an overview of stress and fatigue and how

these conditions manifest in the elderly. A brief review of the relationship between

cardiovascular function and mood concluded the chapter.

2.1 Clinical Depressive Disorders

Depression is one of the oldest, most well recognised mental illnesses, having been

described in medical literature dating back to Ancient Greece (Fava and Kendler, 2000).

Depression is a mental state characterised by low mood, low self-esteem, and a loss of

interest in pleasurable activities.

Mood disorders are a group of disorders in the Diagnostic and Statistical Manual of

Mental Disorders (DSM-IV-TR; American Psychiatric Association, 2000), where the

main underlying attribute is a disturbance of mood. Mood disorders are very common

forms of mental illness, with milder forms estimated to affect up to 20% of the US

population (Nestler, Barrot et al., 2002). In 2013, the American Psychiatric Association

(APA) released the fifth edition of the Diagnostic and Statistical Manual of Mental

Disorders (DSM-5; APA, 2013), in which the mood disorders cluster was separated into

depressive disorders and bipolar and related disorders. Table 2-1 below shows the

disorders in each grouping. In the DSM-5, the common feature of all disorders in the

28

depressive disorders cluster is “sad, empty or irritable mood”, along with significant

impairments to daily functioning due to somatic and cognitive disruptions (APA, 2013).

Diagnosis of the various depressive disorders depends on differences in timing, duration

of episodes and aetiology. Furthermore, clinicians now have the option of adding

specifiers to the diagnosis, for instance they can specify if the depressive disorder is

with anxious distress, mixed features, melancholic features, atypical features, psychotic

features, catatonia, peripartum onset, or has a seasonal pattern.

Table 2-1. DSM-5 Depressive Disorder and Bipolar and Related Disorders (American

Psychiatric Association, 2013)

Depressive Disorders Bipolar and Related Disorders

Disruptive Mood Dysregulation

Disorder

Bipolar I Disorder

Major Depressive Disorder Bipolar II Disorder

Persistent Depressive Disorder

(Dysthymia)

Cyclothymic Disorder

Premenstrual Dysphoric Disorder Substance/Medication-Induced Bipolar

and Related Disorder

Substance/Medication-Induced

Depressive Disorder

Bipolar and Related Disorder Due to

Another Medical Condition

Depressive Disorder Due to Another

Medical Condition

Other Specified Bipolar and Related

Disorder

Other Specified Depressive Disorder Unspecified Bipolar and Related

Disorder

Unspecified Depressive Disorder

The course of depression is highly variable and treatment response is inconsistent

(Belmaker and Agam, 2008). A diagnosis of clinical depression is based on a set of

criteria, such as those outlined in the DSM-IV-TR (APA, 2000) or DSM-5 (APA, 2013).

Major Depressive Disorder (MDD), the most common form of depressive disorders, is a

highly disabling, widely prevalent medical condition. MDD is characterised by

episodes of abnormalities of mood and affect, sleep disturbances, appetite changes as

well as cognitive dysfunction, such as inappropriate feelings of guilt and worthlessness

29

(Fava and Kendler, 2000). A diagnosis of major depression, according to the DSM-5,

will be given if the individual has suffered from five or more symptoms during the same

two week period. The symptoms must be present in combination with one of the core

symptoms; either depressed mood or loss of interest or pleasure, and must be present

almost every day. The symptoms include: significant weight loss or gain while not

dieting; insomnia or hypersomnia; psychomotor agitation or retardation (this must also

be observed by others and not just subjectively measured); fatigue or loss of energy;

feelings of worthlessness or excessive or inappropriate guilt; diminished ability to

concentrate or think, or indecisiveness; recurrent thoughts of death, recurrent suicidal

ideation (without a plan), or suicide attempt or specific plan for suicide. In order to

reach clinical significance, these symptoms must cause significant impairment or

distress in social, occupational or other aspects of daily functioning. Furthermore, the

symptoms must not be caused by other medical conditions or the effects of substances

(APA, 2013).

Findings common across studies of prevalence, are early age of onset as well as a high

comorbidity with other DSM disorders (Kessler, Berglund et al., 2003). The prevalence

of lifetime MDD has been estimated at 16.2%, whereas estimates of 12-month MDD are

6.6% (Kessler, Berglund et al., 2003). Females typically experience depression 1.5-3

times more often than males (Kessler, Berglund et al., 2003). Usually, individuals

diagnosed with MDD are treated with antidepressant medications, with or without

adjunct counselling or therapy (Fava and Kendler, 2000). Chronic forms of depression

are classified as dysthymia or persistent depressive disorder (Nestler, Barrot et al.,

2002). Persistent depressive disorder is commonly milder then MDD (Kalia, 2005), but

with a longer course.

Depressive disorders are the most common forms of mental illness in Australia, and a

major public health problem (Hawthorne, Cheok et al., 2003). Mental disorders were

listed as the main cause of disability in the Australia Burden of Disease study (ABD). It

was estimated that mental illnesses accounted for almost 30% of total years of life lost

to disability (YLD), 8% was attributed to depression alone (Mathers, Vos et al., 2001).

Additionally, unipolar depression is number 10 on the disability-adjusted life year

(DALY) list, a summary measure of population health (Mathers, Vos et al., 2001). In

the United States in 1990, the annual direct and indirect cost of depression is equal to

30

that of coronary heart disease (Approx. US$43 billion), but by 1998, it had increased to

an estimated US$60 billion per annum (Berto, D'Ilario et al., 2000). The total cost of

depression for Australia in 1998 was estimated at US$1.8 billion (Teh-Wei, 2004). A

recent Victorian Health Promotion Foundation (VicHealth) report has estimated the cost

of depression to the Australian economy was approximately AU$12.6 billion annually

(LaMontagne, Sanderson et al., 2010).

Depression in the elderly is a major public health problem. It burdens families and

healthcare providers by disabling those who would normally be healthy (Lebowitz,

Pearson et al., 1997). Depression is a common problem in the elderly, and is not

considered to be a part of normal ageing. Frequently misdiagnosed or overlooked in the

elderly, depression not only decreases quality of life, but often shortens the length of

life (Birrer, DeLisi et al., 2007). Often the symptoms are not recognised by both the

patient, or the healthcare professional, due to the being lost in the context of physical

symptoms associated with ageing (Lebowitz, Pearson et al., 1997). As such, depressed

mood, a core symptom required for diagnosis, may be less prominent than other

depressive symptoms, such as appetite loss, poor sleep, and loss of interest or

enjoyment of life (Lebowitz, Pearson et al., 1997). This often leads to the conclusion

that depression is a normal consequence of the symptoms associated with ageing, a

view that is quite often shared by the sufferer themselves (Lebowitz, Pearson et al.,

1997). However, depressive symptoms often results in greater functional impairment,

which is comparable and often worse than those suffering from other chronic disease

(Wells, Burnam et al., 1992). The perception of poor health (Wells, Burnam et al.,

1992), the utilisation of medical and healthcare services and health care costs are all

increased by depression and depressive symptoms (Simon, Ormel et al., 1995).

2.1.1 Clinical Depression in the Elderly Reports of the prevalence of depression in those aged over 65 years are wide ranging.

In the general elderly population, major depression is present in 1% to 3% of people,

and an additional 8% to 16% of the elderly suffer from clinically significant depressive

symptoms (Cole and Dendukuri, 2003). Population studies have estimated prevalence

of geriatric depression to range between 1% to 20 % (Steffens, Skoog et al., 2000).

Methodological differences account for most of the differences across studies (Djernes,

2006). A recent review found that prevalence statistics among elderly Caucasians vary

depending on the setting in which they are collected (Djernes, 2006). For instance,

31

major depression in those living independently ranges from 0.9% to 9.4%, while those

living in care facilities range from 14% to 42%. Additionally, clinical significant

depressive symptoms range between 7.2% and 49% for those living in similar settings

(Djernes, 2006). These figures are predicted to increase to 60% by 2020 (Birrer, DeLisi

et al., 2007). Birrer et al. (2007) suggest that the rate of recurrence in elderly

populations could be as high as 40%, but the actual figures are lower than that of the

younger population, due to reporting of somatic symptoms in the elderly, or the

interference of cognitive impairment with the accuracy of reporting. It has been

suggested that depressive symptoms are more frequent amongst the oldest old, and can

be partially explained by factors associated with ageing (Blazer, 2003).

Depression in elderly populations is often associated with a decline in quality of life

(Dimopoulos, Piperi et al., 2007). Geriatric depression is often comorbid with other

physical and psychological illnesses, which is not the case in younger populations and

represents a major difference between the two populations (McCusker, Cole et al.,

2005). Medical comorbidities adversely affect the outcomes of depression and vice

versa. For instance, depression is frequently associated with chronic illnesses such as

cardiovascular disease, and can worsen the treatment outcome, and as such disease

progression can influence depressive symptoms, and prolong depressive episodes

(Blazer, 2003). The risk of suicide, cognitive impairment, and worsening of pre-

existing conditions, and poor treatment of illness increase in untreated geriatric

depression (Blazer, 2003).

It is suggested that fewer than 20% of depressive cases in the elderly are actually

detected and treated (Cole, Bellavance et al., 1999) and treatment outcomes of those that

are detected, are often poor (McCusker, Cole et al., 1998). While many have found that

depressive symptoms are less common in old age than in middle age, it is quite common

for older patients to report less specific symptoms of depression to health care

professionals. For instance, the reporting of somatic and cognitive symptoms is more

common than affective symptoms (Alexopoulos, Borson et al., 2002). Additionally,

older depressed patients are more likely to report symptoms such as insomnia, anorexia

or fatigue, rather than depressed mood (Blazer, 2003). Gallo and Rabins (1999)

described this as “depression without sadness”. They suggested that although older

people may present with other typical symptoms of depression, such as loss of appetite

32

and sleep disturbances, they often don’t experience depressed mood or sadness. Other

researchers have proposed that older patients tend to view their sadness as a weakness

or something to be expected, therefore are less likely to report the feelings to a medical

professional (Birrer, DeLisi et al., 2007).

The risk factors associated with depression in the elderly are shown in Table 2-2 below.

Table 2-2. The risk factors associated with depression in the elderly (Cole and Dendukuri, 2003; Birrer, DeLisi et al., 2007)

A history of depression Chronic medical illness

Female gender Widowed, single or divorced status

Brain disease Alcohol or drug abuse

Smoking Certain drug therapies

Stressful life events. I.e. bereavement or

hospitalisation.

Living alone

Sleep disturbance Prior depression

Furthermore, as we age, we experience more loss. Bereavement is often a precursor to

depression, and as such in the new DSM-5, bereavement is no longer an exclusion

criteria for a depression diagnosis.

Another factor of ageing is the idea of a “biological depression-proneness” (Ernst and

Angst, 1995). This model suggests that the neuroanatomical and neurochemistry

changes that occur as a part of natural ageing parallel those thought to occur in

depression. For example, norepinephrine, serotonin and monoamine oxidase (MAO)

function are all altered as we age (Veith and Raskind, 1988). Changes in the secretion

of growth hormone and cortisol also occur, and sleep architecture changes to mimic

those associated with depression (Ernst and Angst, 1995). Additionally, older age in

depressed patients is associated with greater hypothalamic-pituitary-adrenal (HPA) axis

and sympathetic nervous system (SNS) activity (Veith and Raskind, 1988).

As discussed above, increasing costs and decreasing resources are leading researchers to

find novel and less expensive treatment avenues for the depressed elderly. The

following section will provide an overview of the neurobiology of depression. This

33

overview is intended only as background, and will help to form the premise behind the

effectiveness of nutritional supplements in the treatment of mood disorders.

2.1.2 Minor, Sub-Syndromal or Sub-Threshold Depression

Minor, sub-syndromal or sub-threshold depression is given as a diagnosis when the

individual’s symptoms are not significant enough to warrant a diagnosis of major

depression. The criteria for minor depression in the appendix of the DSM-IV-TR states

that a diagnosis can be given when one core symptom is accompanied by one to three

additional symptoms described in section 2.1. In the DSM-5, minor depression falls

under the category named “Unspecified Depressive Disorder” (American Psychiatric

Association, 2013). Unspecified Depressive disorder is applied when the depressive

symptoms cause significant impairment and distress, but do not meet the full criteria of

major depression or other depressions within the depressive disorders class. For the

purpose of this thesis, Unspecified Depressive Disorders will be referred to as Minor

depression or sub-threshold depression.

Like major depression, minor depression is associated with significant impairment,

including reduced physical functioning, poorer health and perceived low social support

(Beekman, Deeg et al., 1995; Blazer, 2003). The presence of sub-threshold disorders

predicts the development of major depressive episodes and in turn major depressive

disorders (Angst and Merikangas, 1997). A WHO study, investigating the presence of

psychological disorder in primary health care settings found that of the subjects

investigated, approximately 9% suffered from sub-threshold conditions, all of which

included significant symptoms that impaired functional ability (Sartorius, Üstün et al.,

1996). Some researchers have suggested that these minor depressive conditions may be

a variant of the more severe, clinical depressive disorders (Kessler, Zhao et al., 1997;

Steffens, Skoog et al., 2000). However, Judd, Akiskal and Paulus (1997) demonstrated

that sub-threshold symptoms were a clinically significant subtype of unipolar major

depressive disorder.

Compared with major depression, sub-threshold depression typically has a milder

course (Wells, Burnam et al., 1992), and therefore the associated healthcare costs are

lower (Simon, Ormel et al., 1995). On the other hand, although individuals with minor

depressive conditions make less use of health services, due to the higher prevalence of

minor depression in the community, the absolute number of individuals utilising

34

services is high (Cuijpers, de Graaf et al., 2004). However, a paper by Kessler et al.

(1997) found that the course of minor depression was similar to that of major

depression, and had very similar risk factors. They suggested that minor depression

should be considered as more serious than just a transient mood state (Kessler, Zhao et

al., 1997). This seems to be the case in the most recent DSM, as minor depression is

now classed as a depressive disorder under the new diagnostic criteria (APA, 2013).

Sub-threshold depressive disorders have been shown to respond well to treatment

interventions. For example, high response rate to pharmacological interventions such as

paroxetine have been demonstrated in those with minor depression (Szegedi, Wetzel et

al., 1997). Additionally, therapeutic interventions, such as telephone counselling have

also proven to be effective treatment for minor depressive disorders (Lynch,

Tamburrino et al., 1997).

2.1.2.1 Minor Depression in the Elderly In comparison to major depression, advancing age sees an increase in the prevalence of

sub-threshold depression (Ernst and Angst, 1995). In the elderly, the prevalence of sub-

threshold depression is more than double that of major depression (Snowdon, 2001;

Blazer, 2003). Heun, Papassotiropulos and Ptok (2000) found that almost 32% of their

sample reported a lifetime diagnosis of sub-threshold depression or recurrent brief

depression, while only approximately 5% of the sample reported a lifetime diagnosis of

major depression. The prevalence of major depression in community-dwelling

individuals over 65 is around 2%. However, sub-threshold depression has been

estimated to affect approximately 15% to 30% of older individuals in the community

(Dimopoulos, Piperi et al., 2007).

Minor depression in the elderly, may be a brief episode of an underlying depressive

disorder that lacks the duration or severity of a major depressive episode, or could also

be the reaction to life stressors experienced by the older population (Birrer, DeLisi et

al., 2007). It is important to note that approximately 15% to 25% of minor depressive

episodes progress to a major depressive episode within two-years (Birrer, DeLisi et al.,

2007). The natural course of untreated minor depression is one to two years; however

the likelihood of becoming disabled by depression within a year occurs in

approximately 53% of patients (McCusker, Cole et al., 2005). Additionally,

comorbidity with anxiety disorders is more likely in those with minor depressive

disorders (Birrer, DeLisi et al., 2007). While minor depressive conditions present with

35

a lower number or severity of symptoms, they are still associated with significant

functional and social impairment and impact quality of life and daily living (Kessler,

Zhao et al., 1997). Chachamovich, Fleck, Laidlaw and Power (2008), found that even

low levels of depression were associated with significant decreases in quality of life.

The results indicated that depression was associated with a negative attitude towards

ageing and both quality of life scores and ageing attitudes decreased as depression

increased in severity, even in sub-threshold levels (Chachamovich, Fleck et al., 2008).

2.2 The Neurobiology of Depression

A number of theories have been postulated to explain the aetiology of depression and

other affective disorders, such as mitochondrial dysfunction, circadian rhythms as well

as psychological theories, which are outside the scope of the current thesis. Classic

theories as well as more recent theories regarding monoamine activity in depressive

states will be discussed in the section that follows.

Additionally, information about brain changes and regions thought to be involved in the

development and/or maintenance of depression and depressive symptoms will be

discussed. This section is provided to give an overview of the area, which will help to

inform the subsequent chapters describing the function of nutrition, vitamins and

minerals and their roles in mood.

2.2.1 Depression and the Brain

Recent advances in neuroimaging have allowed researchers to investigate the neural

underpinnings of the depressed brain. It is likely that many brain regions are involved

in the development of depression (Nestler, Barrot et al., 2002). Magnetic resonance

imaging (MRI) studies have revealed differences in brain structure of depressed patients

when compared to controls. These studies have found reduced brain volume in areas

involved in emotional processing, such as the frontal cortex, orbitofrontal cortex,

cingulate cortex, hippocampus and striatum in patients with unipolar depression

(Arnone, McIntosh et al., 2012). Furthermore, a recent meta-analysis revealed

associations between MDD and enlargement of the lateral ventricles and larger

cerebrospinal fluid (CSF) volumes (Kempton, Salvador et al., 2011). However, it is not

clear if these structural abnormalities in the brains of depressed patients are the cause of

depression, or if depression causes changes to the structure of the brain after its onset.

36

Researchers have linked the onset of major depression with the hippocampus (Lai,

Moxey et al., 2012). Recently, two large meta analyses concluded that hippocampal

volume in depressed patients is reduced (Campbell, Marriott et al., 2004; Videbech and

Ravnkilde, 2004). These findings have been supported in a recent meta-analysis that

examined data from structural neuroimaging studies in depression and Bipolar disease

(Kempton, Salvador et al., 2011). Additionally, those currently experiencing a

depressive episode have significantly smaller hippocampal volume than those in

remission (Kempton, Salvador et al., 2011). Interestingly, the difference in

hippocampal volumes between patients currently experiencing an episode of depression

and those in remission suggests that the hippocampus is an area that should be targeted

by treatments.

It has been suggested that one of the most commonly replicated findings in major

depression research is focal white matter hyperintensities in frontal areas and the basal

ganglia (Fava and Kendler, 2000). White matter hyperintensities are areas of the brain

with increased signal intensity revealed by MRI scans (Herrmann, Le Masurier et al.,

2008; Debette and Markus, 2010). Pathological changes associated with white matter

hyperintensities include demyelination or myelin pallor, loss of tissue density due to

axon and myelin loss and mild gliosis (Fazekas, Kleinert et al., 1993; Pantoni and

Garcia, 1997).

White matter hyperintensities increase with age (Raz, Rodrigue et al., 2007), and are

often found in healthy individuals (Raz, Rodrigue et al., 2007; Sachdev, Wen et al.,

2007). However, many researchers have demonstrated that individuals with late life

depression often have a higher rate and severity of white matter hyperintensities

compared to healthy elderly individuals (Greenwald, Kramer-Ginsberg et al., 1996;

Iidaka, Nakajima et al., 1996; Tupler, Krishnan et al., 2002; Taylor, MacFall et al.,

2005). There is evidence to suggest that in late life depression, white matter

hyperintensities are more common than in early onset depression (Herrmann, Le

Masurier et al., 2008).

There has been some suggestion that white matter hyperintensities may be a result of

reduced blood flow to the areas affected (Brickman, Zahra et al., 2009), lending support

to the theory of vascular depression. Vascular depression is hypothesised to arise due to

cerebrovascular dysfunction (Alexopoulos, Meyers et al., 1997). In the elderly, vascular

37

pathology is often associated with depression. For those with cardiovascular disease

(CVD), depression often results in worse outcomes. According to the theory of vascular

depression, described by Alexopoulos and colleagues (1997), cerebrovascular disease

can “predispose, precipitate or perpetuate a depressive syndrome”, suggesting that all

elderly patients that have cardiovascular disease, and go on to develop depression, will

have vascular depression. However, as the mechanisms underlying the development of

depression are unknown, the authors acknowledge that direct testing of the vascular

depression hypothesis is not possible (Alexopoulos, Meyers et al., 1997). Not all agree

with this suggestion. For instance Almeida et al. (2008) propose if the vascular

depression hypothesis was true, it would mean that virtually all late-onset cases of

depression will be categorised as vascular depression, particularly those who have

experienced a cardiovascular event. Although depression in old age is still a major

public health problem, we should be seeing a rise in the number of depression cases if

cardiovascular disease predisposes or perpetuates a depressive episode, but this is not

the case (Almeida, 2008). Research in this area has increased in recent years, but the

conflicting results indicate that further research is needed.

2.2.2 Brain Neurochemistry and Monoamine Dysfunction in Depression

Numerous hypotheses have suggested that depression is the result of a dysregulation of

one or more neurotransmitter or neuroregulators in areas of the brain involved in mood

regulation such as the limbic system and cerebral cortex. Research has suggested a

possible genetic predisposition to the development of altered neurobiology (Nemeroff,

1998). Furthermore, an adaptation of several neural systems may be involved in the

neurobiology of depression. Antidepressant medications work to increase the levels of

neurotransmitters available in the brain, or work directly on the receptor sites.

The monoamines; serotonin, norepinephrine and dopamine are amongst the most widely

distributed neurotransmitters in the central nervous system. They regulate a number of

behaviours including mood, appetite, cognition, libido, anxiety and aggression

(Nemeroff, 2002). Individually, norepinephrine is associated with stress,

responsiveness, energy and socialisation; serotonin, with impulsivity; and dopamine

with motivation and reward. However there is considerable overlap between the

functions of the neurotransmitters (see Figure 2-1). For example, norepinephrine and

serotonin work together to influence anxiety responses. Norepinephrine and dopamine

are associated with motivation; while dopamine and serotonin work together to effect

38

sexual behaviour, appetite and aggression. All three of these neurotransmitters are

important in the regulation of mood, emotion and cognitive function. Many of these

functions are impaired in depressed patients (Nemeroff, 2002).

Figure 2-1. The inter-relationships of monoamine neurotransmitters and behavioural

responses (adapted from Nemeroff, 2002)

Early theories of depression proposed that an imbalance in the metabolism of

norepinephrine was responsible for mood disorders. The classical catecholamine

hypothesis of affective disorders proposed by Schildkraut (1965) suggested that

abnormally low levels of norepinephrine may lead to depressive symptoms, whereas

high levels of norepinephrine may lead to euphoric or manic symptoms.

Norepinephrine levels are often low in the brains of depressed patients. Post-mortem

research shows that norepinephrine receptors are often increased in the brains of

depressed suicide victims, suggesting lower levels of circulating norepinephrine prior to

death (Nemeroff, 1998). However, norepinephrine dysfunction alone cannot explain the

complex and highly variable nature of depression (Anand and Charney, 2000).

Serotonergic dysfunction has been implicated in a number of neuropsychiatric disorders

(Hećimović and Gilliam, 2006). There is considerable evidence of abnormalities in the

serotonergic neurotransmitter system in patients suffering from depression (Owens and

Nemeroff, 1994). The serotonergic hypothesis of depression, classically known as the

39

indoleamine hypothesis of depression, suggests that depression may be caused by

alterations in serotonergic activity within the brain (Mann, 1999). Once again, this

model fails to account for the complexity of depressive disorders.

The monoamine hypothesis of depression posits that symptoms of depression result

from insufficient monoamine neurotransmission. That is, that a depletion of serotonin,

norepinephrine, and/or dopamine in the central nervous system (CNS) results in the

development of depressive symptoms (Delgado, 2000) and that a reconstitution of

normal synaptic serotonin and norepinephrine levels provides alleviation of depressive

symptoms (Hećimović and Gilliam, 2006). Although the monoamine hypothesis is

quite simple, it has provided an important theoretical framework, which has been the

focus of research in the area of depression. However, the overly simplistic model

cannot explain the complex nature of many mood and affective disorders. Additionally,

the monoamine hypothesis fails to explain the delay between onset of antidepressant

treatment, and the resulting alleviation of symptoms (Meyer and Quenzer, 2005). This

implies that there may be some other mechanism of action of antidepressant

medications, rather than just acting on neurotransmitters. Furthermore, research has yet

to reliably implicate a specific monoamine system dysfunction in depressed patients

(Belmaker and Agam, 2008). For example, studies have shown that the monoamines,

serotonin and norepinephrine are important in the treatment of depression, but may not

necessarily be implicated in the cause of the disorder (Belmaker and Agam, 2008). For

instance, tryptophan limits the synthesis of serotonin in the brain (Belmaker and Agam,

2008). Tryptophan is essential for the formation of serotonin, and is introduced through

the diet. The conversion of tryptophan to serotonin is dependent on vitamin B6 (Le

Floc’h, Otten et al., 2011). Tryptophan depletion studies show that, in healthy control

participants, tryptophan depletion will not cause depression, but in depressed people

treated with selective serotonin reuptake inhibitors (SSRI), tryptophan depletion will

often cause a relapse of depression (Ruhé, 2007).

Subsequently, the monoamine hypothesis of depression has resulted in numerous

scientific publications aimed at finding support for the theory, primarily through the

measurement of central monoamine function in depressed patients. Although this

research has led to very few robust conclusions, it has resulted in the discovery of novel

antidepressant treatments such as fluoxetine and sertraline (Iversen, 2008).

40

Despite the extensive research, spanning many decades, there is still no convincing

evidence that monoamine dysfunction is an underlying feature of depression.

Monoamine enhancing drug therapies only seem to benefit a subgroup of those

receiving treatment for depressive disorders, indicating again, that monoamine

dysfunction may not be as influential as previously assumed (Iversen, 2008).

Increasing age has been associated with changes in neurotransmitter metabolism,

particularly those implicated in depression. For instance, advancing age is associated

with a decrease of neurons in the locus coeruleus, the major norepinephrine nucleus in

the brain (Veith and Raskind, 1988). Subsequently, age related decreases in

norepinephrine have been observed in several studies (Veith and Raskind, 1988),

however others have found an increase in CSF norepinephrine with increasing age,

which has consequently been linked to a decline in cognitive performance (Wang,

Murphy et al., 2013). Additionally, serotonin concentrations have been shown to

decline with advancing age. A recent imaging study found that serotonin binding in the

thalamus and midbrain decrease by 9.65 and 10.5% respectively, per decade

(Yamamoto, Suhara et al., 2002). Age-related declines in dopamine synthesis and

receptor numbers have also been observed (Volkow, Logan et al., 2000). However,

even with these alterations to the brain, not all elderly individuals go on to develop

depression.

Taken together, the research may imply that monoamines have no direct role in the

manifestation of depression; or perhaps they are markers of an underlying dysfunction

of other areas within the brain that have not yet been implicated in depression

(Heninger, Delgado et al., 1996). The conflicting nature of this research has prompted

researchers to expand the search for the underlying mechanisms related to depression,

such as structural brain changes, brain vasculature, as well as nutritional influences.

2.2.3 The role of inflammation in depression Over the years, studies have consistently reported increased levels of pro-inflammatory

cytokines in depressed patients (For a review see Schiepers, Wichers et al., 2005). The

“cytokine hypothesis of depression” suggests that both inflammatory and neural-

immune processes have an important role in depression (Maes, Yirmyia et al., 2009).

Additional support for this hypothesis comes from studies of cancer and hepatitis C

treatments. Patients treated with interleukin-2 and interferon-α immunotherapy often

41

developed full blown depression in approximately 70% of cases (Bonaccorso, Puzella et

al., 2001; Maes, Capuron et al., 2001; Bonaccorso, Marino et al., 2002), which suggests

that pro-inflammatory cytokines can induce depression in a large number of individuals.

Maes et al. (2009) extended on the cytokine hypothesis of depression, and have

proposed the Inflammatory and Neurodegenerative (I&ND) hypothesis of depression.

The I&ND hypothesis postulates that an underlying mechanism of depression is both

inflammatory process as well as increased neurodegeneration, and reduced

neurogenesis. As explained in section 2.2.1 above, depression is associated with a

number of structural brain changes. These changes, along with reduced neurogenesis

(the regeneration of neurons) in depression may be the result of inflammatory processes

(Ekdahl, Claasen et al., 2003; Monje, Toda et al., 2003).

2.3 Anxiety Disorders

In humans, anxiety occurs in response to a stressor, either physiological or

environmental (Clement and Chapouthier, 1998). Normal anxiety, while generating

uneasiness, is an important component of human behaviour, and helps to adapt to stress

and change (Antai-Otong, 2000), however anxiety can become pathological when it

manifests without specific cause (Clement and Chapouthier, 1998).

Anxiety disorders, outlined in the DSM-IV-TR (American Psychiatric Association,

2000), are characterised by excessive worry, unease, apprehension and fear, based on

real or imagined events. Anxiety disorders include generalised anxiety disorder (GAD),

agoraphobia, social anxiety disorder, panic disorder, Obsessive-Compulsive Disorder

(OCD), specific phobias and post-traumatic stress disorder (PTSD). Within the DSM-V,

anxiety disorders as described in the previous version of the DSM, have been split over

3 chapters, now known as Anxiety Disorders, Obsessive-Compulsive and related

disorders, and finally Trauma- and Stressor-related disorders. Table 2-3 below lists the

disorders within each category.

Like mood disorders, anxiety disorders are highly variable and can be highly disabling.

Anxiety is associated with significant impairment and disability (Alonso and Lépine,

2007), increased chronic illnesses (Scott, Bruffaerts et al., 2007), and have high

comorbidity with other psychiatric disorders, in particular mood disorders and substance

42

abuse disorders (Mathew, Price et al., 2008). Also, like mood disorders, in order to

diagnose a clinically significant anxiety disorder, certain criteria must be fulfilled.

Anxiety disorders are the most prevalent class of psychiatric disorders in the U.S

(Kessler, Berglund et al., 2005; Garakani, Mathew et al., 2006). Recently, the incidence

of anxiety disorders in the U.S has been estimated at around 18% (Kessler, Chiu et al.,

2005) with a lifetime prevalence of 28.8% (Kessler, Berglund et al., 2005).

Furthermore, the annual cost in the U.S for both direct and indirect costs is $42.3 billion

(Greenberg, Sisitsky et al., 1999). Surprisingly, there are reports that only 37% of

individuals with anxiety disorders utilize health services (Wang, Lane et al., 2005).

Table 2-3. Anxiety, Obsessive Compulsive and Trauma- and Stressor related disorders as categorised in the DSM-V (American Psychiatric Association, 2013).

Anxiety Disorders Obsessive Compulsive and related disorders

Trauma- and Stressor-Related Disorders

Separation Anxiety Disorder Obsessive-Compulsive Disorder

Reactive Attachment Disorder

Selective Mutism Body Dysmorphic Disorder Disinhibited Social Engagement Disorder

Specific phobia Hoarding Disorder Posttraumatic Stress Disorder Social Anxiety Disorder (Social phobia)

Trichotillomania (Hair-pulling Disorder)

Acute Stress Disorder

Panic Disorder Excoriation (Skin-Picking) Disorder

Adjustment Disorders

Panic Attack (Specifier) Substance/Medication-Induced Obsessive Compulsive and Related Disorder

Other Specified Trauma- and Stressor-Related Disorder

Agoraphobia Obsessive-Compulsive and related Disorder due to Another Medical Disorder

Unspecified Trauma- and Stressor-Related Disorder

Generalized Anxiety Disorder

Other Specified Obsessive-Compulsive and Related Disorder

Substance/Medication-Induced Anxiety Disorder

Unspecified Obsessive-Compulsive and Related Disorder

Anxiety Disorder due to Another Medical Condition

Other Specified Anxiety Disorder

Unspecified Anxiety Disorder

43

2.3.1 Anxiety in the Elderly The study of anxiety in older populations has received far less attention than that of

depression and dementia (Flint, 2005a; Bryant, Jackson et al., 2008). In the elderly,

anxiety is associated with significant distress (Ayers, Sorrell et al., 2007). Increased

disability (de Beurs, Beekman et al., 1999) and reductions in quality of life (Brenes,

Guralnik et al., 2005) have also been connected with late-life anxiety. Late-life anxiety

is often chronic and unrelenting (Livingston, Watkin et al., 1997), and has been linked

to increased mortality, both from suicide (Allgulander, 1994) and other diseases,

particularly cardiovascular diseases (Van Hout, Beekman et al., 2004).

Until recently, the generally held opinion about anxiety in the elderly was that it was

less common than in their younger counterparts, this now seems to be changing in the

recent literature. In a review published by Bryant et al. (2008), findings suggest that

both symptoms of anxiety as well as anxiety disorders are quite common in older adults.

Furthermore, Fuentes and Cox (1997) have since argued that the reason that anxiety

symptoms are often underestimated in older populations is due to the tendency to

somatise anxiety symptoms, leading to misdiagnosis and under-treatment. Others have

suggested that late-life anxiety is qualitatively different than in younger adults, as

elderly individuals do not tend to report experiencing excessive worries occurring over

several days, which is a core feature defining GAD (Flint, 2005a). Furthermore, Flint

(2005a), has suggested that although late-life anxiety is common with the community,

they are less common in the mental health setting, and when they are present, it is often

in conjunction with depression, which becomes the primary area of concern. However

some researchers are finding that the presence of comorbid anxiety and depression is far

less common than each disorder individually (Schoevers, Beekman et al., 2003).

Additionally, the rate of diagnosis of anxiety in the elderly is low in clinical practice

settings, with some suggesting that this is due to the majority of adults with anxiety

being found in primary care settings rather than mental health settings (Wetherell,

Maser et al., 2005).

The prevalence statistics for anxiety disorders within community samples range

between 1.2% to 14%, whereas anxiety symptoms are far more common, with a

prevalence estimated as high as 24% in elderly, community samples (Bryant, Jackson et

al., 2008). Bryant et al. (2008) suggest that although the differences in figures may

reflect real differences, it is more than likely due to differences in how anxiety is

44

measured that give the wide range of discrepancies between studies, as well as the use

of scales that are un-validated for use in older individuals. Bryant et al. concluded, that

like depression, anxiety might present as a sub-threshold disorder in older populations.

2.3.2 Sub-threshold Anxiety

While the prevalence of clinical anxiety disorders in community-dwelling older adults is

common, there is emerging evidence from cross-sectional research suggesting that sub-

threshold anxiety disorders in the elderly are even more prevalent (Heun,

Papassotiropoulos et al., 2000; Rivas-Vazquez, Saffa-Biller et al., 2004; Bryant,

Jackson et al., 2008). Sub-threshold anxiety refers to a condition where the individual

does not meet the full symptom criteria for an anxiety disorder and/or do not report

significant distress or impairment in function (Grenier, Préville et al., 2011). Yet,

studies have shown that impairments to functioning are just as severe as clinically

significant anxiety disorders (Preisig, Merikangas et al., 2001; Wetherell, Le Roux et

al., 2003). Though, unlike sub-threshold depression, sub-threshold anxiety is not

considered a disorder under the DSM-IV criteria of diagnosis, particularly if the

individual does not meet the criterion for significant impairment (Grenier, Préville et al.,

2011). Currently, the disregard for sub-threshold anxiety disorders may result in greater

false negative cases (Grenier, Préville et al., 2011; Haller, Cramer et al., 2014). In their

systematic review, Haller et al. (2014) found consistent evidence of high prevalence

rates of sub-threshold Generalised Anxiety Disorder (GAD), often twice as high as the

DSM-IV GAD. It was also found that patients in primary care were more likely to have

sub-threshold GAD than those in the general population. And like depression, women

were more likely to be affected than men. Furthermore, adolescents and older adults

had higher prevalence rates of sub-threshold GAD, than middle-aged individuals.

Additionally, the presence of sub-threshold GAD was a significant risk factor for

developing clinically significant GAD, as well as developing other anxiety, mood and

substance use disorders. Additionally, sub-threshold GAD was closely related to other

mental health conditions and negatively impacted on pain-related disorders (Haller,

Cramer et al., 2014).

Data from the ESA study (Entquête sur la Santé des Aînés) of French-speaking

community dwelling older adults revealed that, depending on the criteria used, there

was great variation in the 12-month prevalence rates for anxiety disorders. The

prevalence of any DSM-IV anxiety disorder was 5.6%, whereas when a more flexible

45

criteria was applied, 26.2% of older adults reported some variation of sub-threshold

anxiety symptoms (Grenier, Préville et al., 2011). Similarly, a study conducted by

Heun, Papassotiropulos and Ptok (2000) found that 18.5% of their sample reported a

sub-threshold anxiety disorder, compared to the 6.6% with a major anxiety disorder.

Similarly, Grenier et al. (2011) reported the prevalence of DSM-IV anxiety disorders as

5.6% in their sample, when all sub-threshold disorders were considered, this figure

increased to 26.2%. The results of these studies indicate that sub-threshold anxiety

disorders are more common in the elderly than major anxiety disorders.

2.4 The Neurobiology of Anxiety

Research has implicated a number of brain regions in the pathogenesis of anxiety.

Additionally, a number of neurotransmitter systems have been linked to anxiety

symptoms and disorders. The following sections will provide an overview of the most

prominent views of the brain regions and the neurotransmitter systems involved in the

manifestation of anxiety symptoms. These sections will briefly highlight the literature

and views in a continually growing area of research. Additionally, this background will

inform the subsequent chapters that describe the role of vitamins, minerals and nutrients

in mood processes.

2.4.1 Anxiety and the Brain

A number of brain regions have been associated with symptoms of anxiety, such as the

limbic system, including the hippocampus and the amygdala (Clement and Chapouthier,

1998), and the basal ganglia, particularly in generalized anxiety disorder (Connor and

Davidson, 1998). In anxiety, the limbic system is involved in the integration of

behavioural and physiological mechanisms in defensive reactions (Clement and

Chapouthier, 1998). Central to many theories of anxiety and fear is the amygdala. The

amygdala is the key structure within the brain that coordinates the automatic threat

response. Additionally, the amygdala integrates both internal and external information

of the stimuli, including sensory features and context (Mathew, Price et al., 2008). A

large number of both lesion and drug studies have suggested that the amygdala may be

responsible for the components of anxiety: autonomic activation (Davis, 1992),

defensive behaviour (Clement and Chapouthier, 1998), enhanced reflexes, activation of

the HPA axis (Herman and Cullinan, 1997), and a number of other responses.

46

Furthermore, neuroimaging studies have consistently shown that fearful stimuli

activates the amygdala in healthy participants (Phan, Wager et al., 2002).

Another area of interest that is emerging in the literature is the role of the insula in

anxiety (Paulus and Stein, 2006). The insula is known for its central role in

interoception (Critchley, Wiens et al., 2004). Interoception refers to ones awareness of

the physiological condition of the body, such as temperature, itching, pain, hunger and

thirst to name a few. Interoception is important for self-awareness, in that it links

cognitive and affective process with the current state of the body (Paulus and Stein,

2006). Paulus and Stein (2006) propose that the insula is the area that integrates

information from other brain areas such as the amygdala, nucleus accumbens and the

orbitofrontal cortex, and provides an internal representation of the difference between

the body’s current state and the predicted future state of the body. The key hypothesis

proposed in their “insula-view of anxiety” is that individuals prone to anxiety show an

altered interoceptive prediction signal. They also suggest that the initiation of anxiety is

primarily influenced by altered interoception. A number of neuroimaging studies

support the hypothesis of altered insula function in anxiety patients. For example,

Wright et al. (2003) showed that fearful faces presented to patients with specific phobia

resulted in an increased activation in the right insula. Furthermore, citalopram treatment

has been associated with reduced activity in the insula after anxiety reduction in patients

with GAD (Hoehn-Saric, Schlund et al., 2004).

2.4.2 Brain Neurochemistry and Anxiety

Impaired neurochemistry may also have a role in anxiety disorders. There is increasing

evidence, from both human and animal studies suggesting a role of the serotoninergic

system in the aetiology, expression and treatment of anxiety (Graeff, Guimarães et al.,

1996). Research findings are implicating the over activity of the serotonergic system in

those with anxiety disorders (Clement and Chapouthier, 1998; Connor and Davidson,

1998). Specifically, serotonin dysfunction has been linked to increased serotonin

transmission and decreased reuptake (Antai-Otong, 2000).

The gamma-aminobutyric acid (GABA)/benzodiazepine complex has been shown to be

impaired in patients with generalised anxiety disorder. GABA is one of the most

prevalent neurotransmitters in the CNS (Gorman, Hirschfeld et al., 2002), and is the

brains predominant inhibitory neurotransmitter, with widespread pathways all through

47

the CNS (Connor and Davidson, 1998). GABA has been found to effect mood and

emotions. Increased levels of GABA appear to have anxiolytic effects, while decreased

levels generate anxiogenic responses (Antai-Otong, 2000). Benzodiazepine receptors

not only have a close proximity to GABA receptors, they also appear to have a close

functional relationship. For instance, treatment with benzodiazepine drugs such as

diazepam (Valium) result in anxiolytic effects.

There is emerging evidence for norepinephrine abnormalities in anxiety disorders. In

anxiety, there is reduced adrenergic receptor sensitivity due to high levels of circulating

catecholamine’s (Connor and Davidson, 1998). Sympathetic nervous system function

and neuroendocrine processes are mediated by norepinephrine receptor function. It is

currently believed that excess production of norepinephrine along with a dysregulation

of post synaptic adrenergic receptors are a mechanism underlying the manifestation of

anxiety disorders (Antai-Otong, 2000)

2.5 The Co-morbidity of Anxiety and Depression

The interaction between anxiety and depressive disorder is well established in the

clinical literature. Early research proposed a continuum between the symptoms of

anxiety and depression, however subsequent research has suggested that anxiety and

depression should be considered as distinct from one another (Angst, 1997).

Nevertheless, depression and anxiety have many overlapping symptoms such as fatigue,

impaired concentration, irritability, sleep disturbance, somatisation, subjective

experiences of nervousness, worry and restlessness (Ninan, 1999). Furthermore,

comorbid anxiety and depression is associated with a greater severity of symptoms and

poorer treatment outcomes (Lenze, Mulsant et al., 2001). In the replication of the

National Comorbidity Survey (NCS-R), it was found that 59.2% of individuals with

lifetime MDD also met the criteria for anxiety disorder (Kessler, Berglund et al., 2003).

As yet, there is little research that as investigated the comorbidity of anxiety and

depression in the elderly.

Earlier reviews of the literature have suggested that the rate of comorbid anxiety and

depression in the elderly was low compared to younger individuals (Flint, 1994),

however recent findings show that this may not actually be true (Lenze, Mulsant et al.,

2001).

48

In the elderly, high comorbidity between GAD and depression has been reported in

community-based epidemiological studies (Manela, Katona et al., 1996; Schoevers,

Beekman et al., 2003). For instance, Manela et al. (1996) reported that 67.7% of those

with generalised anxiety were also depressed. Furthermore, Schoevers et al. (2003)

found that comorbid depression was present in 56% to 100% of generalised anxiety

cases, progressively increasing with severity of anxiety symptoms. Additionally,

Beekman et al. (2000) found major depression with comorbid anxiety was present in

47.5% of their sample, while Anxiety disorder with major depression affected 26.1%.

King-Kallimanis et al. (2009) found that in those aged over 65, over half of those with

major depression, also met the criteria for a comorbid anxiety disorder or dysthymia.

Furthermore, they found that major depression was present in 36.7% of panic disorder

cases in those aged over 65 years.

Additionally, considerable overlap of anxiety and depressive symptoms has been

observed at the sub-threshold level. Clinical studies have shown that comorbid anxiety

and depression is accompanied by greater symptom severity, poorer treatment

outcomes, significantly higher impairment and longer course than either anxiety or

depression alone (Angst, 1997; Lenze, Mulsant et al., 2001). The mixed anxiety and

depression perspective takes into account both threshold and sub-threshold anxiety and

depression, and treatment is individualised based on the patients specific combination of

symptoms (Rivas-Vazquez, Saffa-Biller et al., 2004). These investigations have

indicated that the prevalence rates for mixed anxiety and depression are much higher

than each disorder alone. Furthermore, comorbidity is more common when at least one

of the disorders reaches clinically significance (Preisig, Merikangas et al., 2001).

The overlap between depression and anxiety pathology is further supported by the

pharmacology literature. The selective serotonin reuptake inhibitor (SSRI) anti-

depressant class of medication has been shown to effectively treat both depression and

anxiety disorders (Ninan, 1999), and as such anti-depressant medications are often the

first-line treatment option for both disorders (Ravindran and Stein, 2010).

The results of this work suggest that the assessment of depression and anxiety in the

elderly should be considered carefully. The rates of comorbid or mixed anxiety and

depression are much higher than disorders occurring in isolation. Furthermore, the rates

of sub-threshold disorders, often comorbid with a clinically significant disorder are

49

providing support for a more dimensional classification of depression and anxiety

(Preisig, Merikangas et al., 2001).

2.6 Stress.

The concept of stress is broadly defined. Some of the current definitions include: the

wear and tear caused by life; any circumstance that upsets homeostatic balance; and as a

challenge to an organisms physiologic systems (Dinges, 2001). Stress has both a

biological component as well as a psychological component. Biological aspects of

stress refer to the activation of neuroendocrine systems and brain regions. While

psychological stress refers to the control, predictability and coping behaviours of the

individual (López, Akil et al., 1999). Psychological stress appears in many forms, and

as such can be acute or chronic, minor or major, positive or negative. The majority of

life stressors are often combinations of all of these things, often also including a

physical aspect of stress (Glatthaar, 1999). While researchers have determined close

links between the biological and psychological aspects of stress, they have yet to

elucidate the exact relationship between the two.

The role of stress in both depression and anxiety is important. For example, stress is

often associated with the onset of psychiatric disorders, in particular depression. Both

depressive and anxiety symptoms can be induced by the addition of a psychosocial

stressor or stressful life events in some individuals (Blazer, Hughes et al., 1987;

Kendler, Karkowski et al., 1999).

The human brain responds to stressors in a complex, orchestrated pattern. The stress

response requires activation of brain structures involved in sensory, motor, autonomic,

cognitive and emotional functions. This stress response seems to be activated to both

general and stimulus-specific stressors and involves other biological systems such as the

endocrine, autonomic, cardiovascular and immunological systems (Tsigos and

Chrousos, 2002).

2.6.1 The Body’s Response to Stress: The Activation of the HPA Axis

The most well-known mechanism by which the brain reacts to acute and chronic stress,

that involves both cerebral and biological systems, is the hypothalamic-pituitary-adrenal

axis (HPA axis) (Nestler, Barrot et al., 2002). Over-activity of the HPA axis in

depression is among the most consistently replicated biological findings in psychiatry

50

(Nemeroff, 1998; Goodwin and Jamison, 2007). The HPA axis is important in

understanding the aetiology of depression. HPA axis dysfunction has also been

implicated in anxiety disorders, including panic disorder (Abelson, Khan et al., 2007),

social anxiety disorder (Condren, O'Neill et al., 2002) and generalised anxiety disorder

to a lesser extent (Martin, Ressler et al., 2009).

The HPA axis regulates a number of homeostatic processes in the body, including the

immune system, cardiovascular function as well as the stress response (Tsigos and

Chrousos, 2002). When the brain detects a threat to homeostasis, such as an increase in

stress, the HPA axis is stimulated. The normal HPA response begins in the

paraventricular nucleus of the hypothalamus. Neurons in this brain region secrete

corticotropin-releasing hormone (CRH), which stimulates the anterior pituitary gland to

synthesise and release adrenocorticotropic hormone (ACTH). ACTH then stimulates

the adrenal cortex to synthesise and release glucocorticoids (cortisol in humans).

Glucocorticoids influence general metabolism and behaviour (Herman and Cullinan,

1997; Nestler, Barrot et al., 2002). The activity of the HPA axis is influenced by a

number of brain regions, including the hippocampus and the amygdala. The

hippocampus serves to provide an inhibitory effect on CRH-containing neurons of the

hypothalamus, while the amygdala provides a direct excitatory effect (Hećimović and

Gilliam, 2006). Once in circulation, glucocorticoids exert powerful feedback on the

HPA axis and appear to enhance hippocampal inhibition of HPA activity (Tsigos and

Chrousos, 2002; Hećimović and Gilliam, 2006) (See Figure 2-2). However, prolonged

increased concentration of glucocorticoids may be harmful and damage or impair

hippocampal function (Hećimović and Gilliam, 2006). Impaired hippocampal function

might be expected to contribute to some of the cognitive abnormalities of depression.

Clinical studies have shown that almost half of the depressed individuals observed have

abnormal or excessive activation of the HPA axis, resulting in a significantly increased

level of cortisol, and that this effect can be reversed by antidepressant treatment

(Holsboer, 2001; Hećimović and Gilliam, 2006). Recent hypotheses suggest that

increased cortisol levels, caused by stressful life-events, may result in altered brain

serotonin levels, which may then manifest into a depressive state (Cowen, 2002).

However, not all depressed patients hypersecrete cortisol, indicating that increased

cortisol in depression may be a response to life-stressors, rather than a symptom or even

cause of depression.

51

Figure 2-2. Diagrammatic representation of the HPA axis. Adapted from (Hećimović

and Gilliam 2006).

Some suggest that CRH may have a direct influence on the development of depression.

Arborelius et al. (1999) reviewed the evidence for the role of CRH in depression. The

literature shows that CRH is hypersecreted in depression, which leads to hyperactivity

of the HPA axis and a subsequent increase in CSF levels of CRH. Additionally, CRH is

thought to mediate some of the behavioural symptoms associated with depression such

as sleep and appetite loss, reduced libido, and psychomotor dysfunction. Arborelius and

colleagues (1999) suggested that CRH could be used as a state marker of depression due

to evidence for HPA axis normalisation after effective antidepressant treatment, and

further suggest that CRH receptor antagonists may be a novel treatment option for

depression.

In summary, while there are close links between stress and depression and anxiety, HPA

axis dysfunction is not evident in all cases of depression or anxiety.

2.7 Fatigue

Fatigue can be conceptualised in many ways and refers to both psychological and

physical workload reactions. For example, some suggest that it can be viewed as the

inability to maintain sufficient energy levels in the face of continuing demand (Dinges,

2001). It can also be thought about in terms of the perception of exhaustion, decreased

energy, lethargy and the need for sleep (Avlund, 2010). Furthermore, fatigue is the

body’s natural reaction when it has reached its limit of strain. For the purpose of this

52

thesis, mental fatigue is conceptualised as a decrease in cognitive performance, resulting

from long periods of mental activity. Physical fatigue refers to exhaustion of the body.

The definition of fatigue in general will refer to Avlund’s (2010) description of fatigue;

the perception of exhaustion, decreased energy, lethargy and the need for sleep.

Fatigue is a common complaint among older people (Avlund, 2010), and has been

associated with a sedentary lifestyle, disability and poor functional performance (Hardy

and Studenski, 2008a; Vestergaard, Nayfield et al., 2009; Moreh, Jacobs et al., 2010),

and as such is often used as a marker for age-related health and functional decline

(Avlund, 2010; Eldadah, 2010). Additionally, perceived fatigue has been shown to be a

significant predictor of future functional decline in a number of prospective studies in

the elderly (Avlund, Damsgaard et al., 2001; Avlund, Damsgaard et al., 2002; Avlund,

Vass et al., 2003; Avlund, Rantanen et al., 2006), and these fatigue-related functional

deficits have been shown to persist over a number of years (Hardy and Studenski,

2008a). Furthermore, one population study found that older adults with fatigue

increased the risk of mortality more so than those without fatigue (Hardy and Studenski,

2008b). In elderly populations, fatigue is often associated with other underlying

medical or psychiatric conditions such as cancer, cardiovascular disorders, or depression

(Addington, Gallo et al., 2001; Avlund, 2010). Watt (2000) suggested depressive

symptoms may be more strongly associated with general or mental fatigue rather than

physical fatigue. In many cases, when the cause of the fatigue is unknown, and

therefore untreatable, the fatigue in itself becomes a syndrome (Yu, Lee et al., 2010).

This mechanism however is not well understood.

The subjective nature of fatigue research has hindered the advancement of knowledge

within the field. Past researchers have been unable to develop a standardised

measurement tool, and as such the different aspects of fatigue are still relatively unclear

in the elderly. Furthermore, the prevalence of fatigue within the general older

population has been shown to be quite high, although very few studies have investigated

fatigue in older population groups (Avlund, 2010). In particular, few have investigated

potential interventions to improve symptoms of fatigue with the elderly population.

53

2.8 Cardiovascular Health and Mood

Cardiovascular disease (CVD) and depression are the Western world’s most prevalent

health problems. All diseases of the heart and blood vessels fall under the banner of

cardiovascular disease (Australian Institute of Health and Welfare (AIHW), 2011). In

the US, CVD is the leading cause of death and hospitalisation, with 2010 figures

showing the direct and indirect costs of CVD and stroke at well over US$315 billion

(Go, Mozaffarian et al., 2014). In 2004-05 in Australia, CVD accounted for 18% of the

overall burden of disease, 80% of this was attributed to coronary heart disease and

stroke. The WHO has predicted that depression and heart disease will become numbers

1 and 2 on the list of DALYs for high income countries by 2030, and 2 and 3 globally

(Mathers and Loncar, 2006). In Australia, the figures suggest that 90% of adults have at

least one cardiovascular risk factor, while 60% of older adults have some type of

vascular illness, such as heart problems or stroke (AIHW, 2004). As such, in 2008,

CVD was the leading cause of death in Australia, accounting for 34% of all deaths

(AIHW, 2011). Furthermore, approximately 70% of Australians aged over 65 have

hypertension. The figures for high blood cholesterol are similar to those for

hypertension. Coronary heart disease, stroke and heart failure/cardiomyopathy are the

main types of CVD in the Australian community.

Structural and functional changes of the arterial wall are associated with morbidity and

mortality in hypertension (O'Rourke, 1995). Arterial stiffness can occur with alterations

to the arterial wall, and has been implicated as a risk factor for cardiovascular pathology

(Nürnberger, Keflioglu-Scheiber et al., 2002; O'Rourke and Seward, 2006). In order to

non-invasively measure the elasticity of arteries, pulse wave analysis is being

increasingly used in clinical studies to assess arterial stiffness (Smith, Page et al., 2000;

Wilkinson, MacCallum et al., 2000a). Pulse wave analysis allows for the measurement

of the augmentation index. The augmentation index is a measure of systemic arterial

stiffness (Wilkinson, MacCallum et al., 2000b). Recent work has associated

augmentation index with increased cardiovascular disease risk (Nürnberger, Keflioglu-

Scheiber et al., 2002).

Arterial stiffness increases with age, resulting from a gradual decline in the elasticity of

the arteries (Pase, Grima et al., 2011). Functional decline also contributes to the

stiffening of arteries and can often be reversed with treatment (Wilkinson, Hall et al.,

54

2002; Pase, Grima et al., 2011). Increased arterial stiffness has been associated with

cognitive decline (Hanon, Haulon et al., 2005) and cardiovascular disease (Mattace-

Raso, van der Cammen et al., 2006). Additionally, elevated plasma levels of

homocysteine have been linked with more advanced arterial stiffness (Tayama,

Munakata et al., 2006).

There is increasing evidence for a relationship between depression and increased arterial

stiffness in the literature. Results from the Rotterdam Study show that elderly

participants with increased arterial stiffness were more likely to report depressive

symptoms (Tiemeier, 2003). Similarly, data from the Netherlands Study of Depression

and Anxiety found that augmentation index was elevated in individuals with current

depression or anxiety (Seldenrijk, van Hout et al., 2011). The results reported by Oulis

et al (2010) demonstrated that successful treatment of depression through traditional

antidepressant treatment not only successfully treated the depressive disorder, but also

resulted in significant reductions in arterial stiffness. These results suggest that the

successful reduction of depressive symptoms also leads to a significant improvement in

arterial stiffness. Taken collectively, current anxiety or depressive disorders increase

systemic arterial stiffness, and therefore may increase the risk of developing

cardiovascular pathology. Successful treatment of the depressive or anxiety disorder

can help to reduce arterial stiffness, and therefore lower the risk of cardiovascular

disease.

Depression and depressive symptoms are a major risk factor for both the development

of CVD, but also for death after myocardial infarction (MI) (Musselman, Evans et al.,

1998). Patients with coronary heart disease are rarely given a diagnosis of depression,

however the recognition and treatment of depression in these patients is important,

particularly in those following MI (Musselman, Evans et al., 1998). Research indicates

that patients with depression are two to four times likely to develop CVD (Ford, Mead

et al., 1998; Penninx, Beekman et al., 2001), and clinical depression remains a risk

factor for CVD, particularly coronary artery disease, for decades after the onset of the

first depressive episode (Ford, Mead et al., 1998). Results from the Longitudinal Aging

Study Amsterdam (LASA) indicate that cardiac mortality in depressed older people was

significantly higher than in non-depressed people. Furthermore, the authors reported

that the associated risk between depression and cardiac mortality was present in all

55

depressed patients with or without CVD at baseline (Penninx, Beekman et al., 2001).

Furthermore, a number of review papers have concluded that future coronary events can

be predicted by depressive symptoms, even in those that were initially healthy and

poorer outcomes for those with established CVD (Musselman, Evans et al., 1998;

O’Connor, Gurbel et al., 2000). If left untreated, depression can adversely affect the

treatment of cardiac events, but in most cases the depression can be successfully treated

with antidepressant medications, improving outcomes for cardiac patients (O’Connor,

Gurbel et al., 2000).

Links between CVD and anxiety disorders have also been identified in the literature

(Van Hout, Beekman et al., 2004; Vogelzangs, Seldenrijk et al., 2010). The baseline

data from the Netherland Study of Depression and Anxiety revealed that anxiety

disorders, or comorbid anxiety and depression were associated with a three-fold

increase in the likelihood of CVD. Depression alone was not associated with CVD.

Cerebrovascular disease refers to disease of the blood vessels that supply blood to the

brain, and is classified by the WHO as a form of cardiovascular disease (Mendis, Puska

et al., 2011). As described in section 2.2.1, the presence of focal white matter

hyperintensities in frontal regions of the brain in depression is one of the most

replicated findings in depression research (Fava and Kendler, 2000). Researchers have

suggested that white matter hyperintensities arise from reduced blood flow to affected

brain regions (Brickman, Zahra et al., 2009), leading to the theory of vascular

depression. Vascular depression is hypothesised to arise due to cerebrovascular

dysfunction (Alexopoulos, Meyers et al., 1997). While neuroimaging studies have

shown that persons with late-onset depression have more vascular abnormalities than

non-depressed individuals, supporting the vascular depression hypothesis (Steffens,

Helms et al., 1999), results from studies measuring atherosclerosis and cerebrovascular

risk factors have reported mixed results (Lyness, Caine et al., 1999).

2.9 Summary and Conclusion

When taken together, the impact of negative mood states, stress and fatigue is of

particular importance in elderly populations. The elderly make a large proportion of our

society, with 14% of the Australian population aged over 65 years (Australian Bureau

of Statistics, 2013). With the increasing number of elderly in our society, the

56

importance of reducing the burden of disease is high and as such, the need for

interventions to address these burdens is manifest. Depression is the most common

mental illness in Australia, and is a major public health problem (Hawthorne, Cheok et

al., 2003). The prevalence of depression in the elderly is estimated to range between

1% to 20% (Steffens, Skoog et al., 2000), with figures predicted to rise to around 60%

by 2020 (Birrer, DeLisi et al., 2007). Aside from the burden of mental illness on the

public healthcare system, the economic burden of depression is high in developed

counties (Luppa, Heinrich et al., 2007). In Australia, mental illness costs the economy

approximately AU$20 billion per year (Australian Bureau of Statistics, 2009), and the

annual cost in the US is over US$80 billion annually (Greenberg, Fournier et al., 2015).

The elderly represent a group that have been neglected in the depression literature, and

until recently, the general consensus was that depression was uncommon in older

groups. However, recent cross-sectional data is highlighting the increasing number of

both clinical depression and sub-threshold depressive cases in the elderly community.

The successful treatment of depression in the elderly, particularly those living in care

facilities will not only improve the quality of life of the elders, but also reduce the

burden on the healthcare system.

There have been many theories postulated regarding the underlying cause of depression.

Research has consistently found that depressed patients have disturbed monoamine

function, particularly with regards to serotonin, norepinephrine and dopamine, however,

both the classical and more modern hypothesis relating to monoamine dysfunction and

depression still fail to explain the complexity of depressive disorders. Despite the many

thousands of publications, spanning many decades, there is still no concrete evidence

that monoamine dysfunction is an underlying feature of depression. It could be perhaps

that monoamine dysfunction is simply a marker of depression. While normal ageing is

associated with changes to brain structure and neurotransmitter metabolism, not all

elderly patients go on to develop depression. Depression on the other hand is associated

with a number of changes in the brain that might otherwise not be associated with

ageing. Regardless of the countless number of publications in the depression literature,

the precise mechanisms underlying the development and maintenance of depression are

still unknown. With this in mind, prevention of depression and related symptoms may

be the next path with which the research will follow.

57

Like depression, anxiety disorders are highly prevalent in the broader community. The

direct cost of anxiety disorders is also high and the burden placed on the health care

system is projected to increase exponentially over the next 20 years. Sub-threshold

anxiety disorders have been found to be twice as prevalent as clinically significant

anxiety disorders, and are just as disabling. Moreover, sub-threshold anxiety is a

significant predictor of developing a clinically relevant anxiety disorder. While the

study of anxiety in the elderly has received much less attention than depression, the

recent literature is indicating that anxiety disorders in the elderly are more common than

previously thought. Furthermore, the prevalence of sub-threshold manifestations of

anxiety disorders is more than double than major anxiety disorders in those aged over

65 (Haller, Cramer et al., 2014). Like sub-threshold depression, the presence of sub-

threshold anxiety can be associated with significant impairment and disability.

Various brain regions and neurotransmitter systems have been shown to have a role in

anxiety disorders. The majority of research has focus on the role the amygdala plays in

the development of anxiety disorders (Clement and Chapouthier, 1998). This research

has its origins in the human response to fear, and the amygdala has been shown to be

the structure within the brain that coordinates the automatic threat response (Mathew,

Price et al., 2008). Furthermore, evidence for the role of the insula in anxiety is

emerging. Neuroimaging studies have shown that altered insula function is present in

many different anxiety disorders, and may be an underlying cause of the anxiety

response (Paulus and Stein, 2006). There is growing evidence for neurotransmitter

dysfunction in anxiety, with a number of neurotransmitter systems being implicated in

anxiety disorders. Serotonin, norepinephrine and GABA dysfunction have all been

observed in anxiety patients.

As has been described in this chapter, mood and anxiety disorders are likely the

reflection of many biochemical processes within the brain. Therefore, minor

disturbances of these chemical processes may lead to dysfunction. The high prevalence

of these disorders within the elderly community is cause for concern. The addition of

sub-threshold disorders in the elderly compounds the problem, particularly as

epidemiological studies are suggesting that the rates of sub-threshold anxiety and

depression are twice that of the clinically significant disorders (Snowdon, 2001; Blazer,

2003; Haller, Cramer et al., 2014). Why this is the case is still a matter of great debate

58

in the literature, with some suggesting that depression and anxiety present differently in

the elderly (Flint, 2005a; Birrer, DeLisi et al., 2007), and others suggesting that they are

merely a milder version of the more severe, clinical significant disorders (Kessler, Zhao

et al., 1997; Steffens, Skoog et al., 2000). Additionally, there has been some suggestion

that there may be a continuum of depression, with the evidence of both depression and

sub-threshold depression leading researchers to lean more towards a spectrum of

depressive disorders rather than a categorical diagnostic system (Angst and Merikangas,

1997; Lebowitz, Pearson et al., 1997; Cuijpers, de Graaf et al., 2004).

Due to the high economic burden of mental illness on society, the identification of novel

and inexpensive treatments to reduce the prevalence are required. As such, researchers

have been investigating the influence of diet on clinical mood disorders. Adequate

micronutrient status is essential for the optimal functioning of the central nervous

system. In recent years, the potential benefit of micronutrient supplementation in

clinical mood disorders has been investigated (Long and Benton, 2013). It has been

argued that if a subclinical deficiency of micronutrients is present, psychological

symptoms are likely to be amongst the first benefit from supplementation (Long and

Benton (Long and Benton, 2013).

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Chapter 3 Micronutrients and Mood

3.1 Introduction

As was described in the previous chapter, the presence of depression and anxiety in the

elderly is a cause for concern. The high economic burden of mental illness, as well as

the strain on the healthcare system makes the identification of novel and inexpensive

treatment options to reduce the prevalence of these disorders paramount. Section 2.2.2

of the previous chapter described the many neurochemical processes that can affect

mood. While the exact mechanisms underlying mood disorders is unknown, several

neurochemical and neurological processes have been implicated in mood disturbance.

Poor nutrition is another factor that may influence both mood and stress. It has been

suggested that even small inadequacies in the diet could cumulatively influence mood

states (Long and Benton, 2013), indicating that improving nutritional status may in turn

improve mood outcomes. There are a number of ways through which vitamins may

benefit mood, the main mechanisms being via direct influences on brain chemistry.

Many biological processes within the brain cumulatively influence mood, and an

adequate supply of vitamins and minerals is essential to the health and functioning of

the central nervous system. Secondly, the cardiovascular system is another mechanism

through which vitamins may benefit mood. Associations between cardiovascular

disease and depression (Musselman, Evans et al., 1998), and to a lesser extent, anxiety

(Vogelzangs, Seldenrijk et al., 2010) in the general population and in those with

cardiovascular disease are well established in the literature.

Vitamins are organic compounds that occur naturally in plants and animals, and are

essential for normal growth, nutrition and the maintenance of health (Bender, 2003).

The body cannot synthesise vitamins and mineral in sufficient quantities, therefore they

must be introduced through the diet. Many vitamins share a number of characteristics.

One such quality shared by many vitamins taken through the diet is their inability to be

used in the form in which they are absorbed, but require conversion into their active

forms (Brody, 1999). Body stores of particular vitamins and minerals are limited, and

impairments in absorption, reduced intake or increased requirements may lead to

deficiencies (Huskisson, Maggini et al., 2007a). This is particularly evident in the

elderly, where reduced food intake and malabsorption is common (Bhat, Chiu et al.,

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2005). Vitamins, including A, B-Group, C, D and E, are vital for the optimal

performance of numerous physiological processes, particularly in the central nervous

system (Calvaresi and Bryan, 2001). Vitamins have both direct and indirect influences

on brain function, such as energy metabolism, neurotransmission, neuroprotection,

cerebral blood flow, receptor binding and the functioning of membrane ion pumps

(Haller, 2005).

The Australian National Health and Medical Research Council (NHMRC), and other

agencies around the world have suggested minimum daily requirements for vitamin and

mineral intake in order to maintain health. Recommended Dietary Intake (RDI) values

have been set by the NHMRC for Australians and New Zealanders, and they reflect the

average daily dietary intake needed to meet the nutritional requirements of almost all

healthy individuals (National Health and Medical Research Council, 2006). RDIs are

calculated from the Estimated Average Requirement (EAR) for each nutrient, by adding

2 standard deviations (where available) to the EAR. Of important note, is the fact that

as these RDIs are population statistics, they should not be used to assess the diet of

individuals (Benton, 2013). Furthermore, the NHMRC guidelines were set only as

guidelines to maintain “adequate physiological or metabolic function and/or avoidance

of deficiency states” (National Health and Medical Research Council, 2006). They

therefore do not include values aimed to prevent chronic disease, or to maintain optimal

performance of the body. Recently, the NHMRC has released dietary guidelines, aimed

towards promoting healthy eating and lifestyle choices for Australians (National Health

and Medical Research Council, 2013). These guidelines provide recommendations for

the maintenance of a healthy diet that are based on the scientific literature.

Diet and lifestyle factors have been shown to influence morbidity and mortality as we

age (de Groot and Van Staveren, 2010). Additionally, an adequate supply of nutrients is

essential for the health of the neurological system (Long and Benton, 2013).

Epidemiological and cross-sectional research has highlighted the importance of

adequate nutritional status in the regulation of mood and quality of life, particularly in

older populations (Brownie, 2006). Furthermore, the risk of mortality, cardiovascular

disease mortality and the risk of cancer is reduced when eating a healthy diet, rich in

fruits and vegetables, such as the Mediterranean diet (Sánchez-Villegas, Henríquez et

al., 2006). Additionally, a recent epidemiological study has found that those consuming

61

a “traditional” diet, comprised of fruit, vegetables, beef, lamb, fish and whole-grain

foods were less likely to develop depressive and anxiety disorders, whereby those

consuming an unhealthy, “western” diet, high in fatty foods, pizza, processed meats and

white bread, were at a higher risk of developing psychiatric symptoms and disorders

(Jacka, Pasco et al., 2010).

The following section (3.2) will outline the relationship between diet and mood.

Following this, Section 3.3 will briefly discuss the more specific relationship between

mood and vitamins, focusing on the elderly population. A brief overview of the role of

nutrition and vitamins on cardiovascular health will also be presented (section 3.3.1).

The role of the B vitamins and homocysteine with regards to mood will be discussed in

section 3.4, including evidence from epidemiological research. The sections that follow

will consider different vitamin and nutrient groups and will explain the roles they play

in the brain and body and how this may relate to mood (Sections 3.6 to 3.9).

3.2 The Influence of Diet and Nutritional Intake on Mood

“Let food be thy medicine and medicine be thy food” ~ Hippocrates, ca. 400bc

A balanced diet is essential for optimal functioning of the human body and an adequate

supply of nutrients is important for the health of the neurological system (Gómez-

Pinilla, 2008). As we age, morbidity and mortality have been shown to be influenced

by diet and lifestyle factors (de Groot and Van Staveren, 2010), and the importance of

adequate nutritional status in the elderly has been highlighted by epidemiological and

cross-sectional research (Brownie, 2006). As described in chapter 2, micronutrient

deficiencies can result in a number of poor health outcomes, and have particular

relevance to mood. Nutrients are involved in numerous physiological processes and

exert both direct and indirect effects on the brain, such as facilitation of neurotransmitter

production, energy metabolism and improved cerebral blood flow (Haller, 2005;

Huskisson, Maggini et al., 2007b).

Researchers have investigated the relationship between dietary intake of vitamins and

minerals and the risk of depression. For example, Wurtman and Wurtman (1986)

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proposed that serotonin neurotransmission can be influenced by the balance of protein

and carbohydrate consumed in a meal, by altering the amount of tryptophan available

for the brain. Tryptophan is an amino acid precursor of serotonin. Research suggests

that serotonin conversion in the brain is influenced by the availability of tryptophan

(Volker and Ng, 2006). This theory suggests that meals high in protein increase

alertness and that snacks and meals rich with carbohydrates relieve depressed mood,

often acutely (Wurtman and Wurtman, 1995). While there is some evidence to support

this hypothesis, other researchers have failed to draw the same conclusions (Teff,

Young et al., 1989; Rogers, 1995).

A large proportion of the population in industrialised countries are failing to consume

an adequate level of vitamins through their diet. The typical Western diet is high in

saturated fats and refined sugars, defined by energy-laden, low-nutrient foods, with a

subsequent reduction in fruits, vegetables and fibre (Jacka and Berk, 2007). A recent

Australian epidemiological study found that those who typically consume a

“traditional” diet, comprised of fruit, vegetables, beef, lamb, fish and whole-grain foods

were less likely to develop depressive and anxiety disorders, whereby those consuming

an unhealthy, “western” diet, high in fatty foods, pizza, processed meats and white

bread, were at a higher risk of developing psychiatric symptoms and disorders (Jacka,

Pasco et al., 2010). Similarly, a large UK study found that a diet high in process foods

was a risk factor for depression, whereas eating a diet rich in whole foods was

protective (Akbaraly, Brunner et al., 2009).

Adherence to a healthy diet, rich in fruits and vegetables, such as the Mediterranean

diet, has been shown to reduce the risk of mortality, cardiovascular disease mortality

and the risk of cancer (Sánchez-Villegas, Henríquez et al., 2006). Additionally, the risk

of developing cardiovascular disease and stroke (Estruch, Ros et al., 2013), type II

diabetes (Ajala, English et al., 2013), mild cognitive impairment (Scarmeas, Stern et al.,

2009) and Alzheimer’s Disease (Scarmeas, Stern et al., 2006) are all reduced when

adhering to a Mediterranean-style diet. Recently, results from a pilot study conducted

by our research group indicated that switching to a Mediterranean diet for 10-days led to

improvements in self-rated vigour, alertness and calmness in a small group of healthy,

young females (McMillan, Owen et al., 2011). In a more recent study, also conducted

by our group, the study by McMillan et al. (2011) was replicated using a crossover

63

design, finding that changing to a Mediterranean-style diet for 10-days significantly

improved self-rated levels of contentment and alertness, and reduced confusion (Lee,

Pase et al., 2015). Additionally, augmentation pressure, a measure of aortic blood

pressure, was significantly decreased following the Mediterranean diet intervention

period.

Other dietary interventions have been shown to be beneficial for mood and overall

general health. For instance, the DASH diet (Dietary Approaches to Stop

Hypertension), which was originally developed to reduce blood pressure, has also been

shown to be beneficial on a number of other health outcomes. The DASH diet is rich in

fruits, vegetables, low-fat dairy products and lean meats, poultry and fish (Appel,

Moore et al., 1997; Sacks, Moore et al., 1999). Adherence to this diet style has been

proven effective in reducing blood pressure (Appel, Moore et al., 1997; Sacks, Svetkey

et al., 2001; Blumenthal, Babyak et al., 2010), blood cholesterol levels (Obarzanek,

Sacks et al., 2001) and results in improvements in measures of arterial stiffness

(Blumenthal, Babyak et al., 2010). More recently, the DASH diet plan has been

associated with lower risk of depression (Valipour, Esmaillzadeh et al., 2015).

Furthermore, a DASH-style diet was found to improve mood after 14 weeks in a group

of postmenopausal women (Torres and Nowson, 2012).

These results have led a group in the USA to develop a new diet that was designed to

protect the brain from neurocognitive decline and enhance brain health (Morris,

Tangney et al., 2014). The MIND diet (Mediterranean-DASH diet intervention for

neurodegenerative delay) is a combination of the Mediterranean and DASH diet styles,

based on the results from the field of diet and dementia. The MIND diet is rich in leafy

green vegetables, which have been shown to protect the brain against cognitive decline

(Kang, Ascherio et al., 2005; Morris, Evans et al., 2006), as well as berries, beans and

nuts. Preliminary data suggests that the MIND diet not only slows age-associated

cognitive decline (Morris, Tangney et al., 2015a), it may also be associated with a

reduced risk of Alzheimer’s disease (Morris, Tangney et al., 2015b).

These dietary interventions are all rich in grains, legumes, vegetables (particularly leafy

greens), fruits and nuts. Legumes, whole grains and leafy green vegetables are a rich

source of B vitamins, particularly folate (Kelly, 1998). As will be described in more

detail in the sections to follow (section 3.4), folate and B12 are vitally important for the

64

healthy functioning of the brain. Additionally, low dietary folate has been linked to

neural tube defects in newborn infants (MRC Vitamin Study Research Group, 1991),

which has resulted in the mandatory fortification of grain products with folic acid, in

most developed countries. Moreover, a diet low in folate has been associated with a

greater risk of developing severe depression (Tolmunen, Hintikka et al., 2004a). Data

from the Kuopio Ischemic Heart Disease Risk Factor study, in Finland found that men

in the lowest tertile for folate intake were 67% more likely to have elevated depression

scores than those in the highest tertile (Tolmunen, Voutilainen et al., 2003). Similarly, a

large Japanese study found that a higher intake of dietary folate was associated with a

lower incidence of depression in men, but not women (Murakami, Mizoue et al., 2008).

Furthermore, results from the ongoing Chicago Health and Aging project, show that

higher dietary intake, including supplements of vitamins B6 and B12 is associated with a

decreased risk of depression (Skarupski, Tangney et al., 2010). These results indicate

that the chance of developing depression symptoms can be decreased by 2% per year,

with the addition of 10 micrograms or 10 milligrams of B6 or B12 respectively, to the

diet. The researchers found no associations between folate and depressive symptoms.

Recently, a large Canadian study investigated the influence of nutrient intake in a group

of individuals with mood disorders (Davison and Kaplan, 2012). The investigators

examined the intake of both nutrients from food, as well as dietary supplements. They

found that consuming a diet (food and supplements) with higher nutrient levels was

associated with better psychological functioning.

While preliminary, there is a small body of evidence that suggests that altering diet may

be beneficial to mood. Furthermore, other scientific research may explain why healthier

diets may have protective effects on mental wellbeing. For example, adherence to a

Mediterranean style diet has been shown to reduce markers of inflammation

(Chrysohoou, Panagiotakos et al., 2004) and diets rich in micronutrients and omega-3,

such as the Mediterranean Diet, seem to have the most beneficial effects for mood.

Additionally, there is preliminary evidence to suggest that the DASH diet style may also

benefit mood, possibly through improving cardiovascular function (Torres and Nowson,

2012). Researchers suggest that the high levels of micronutrients and omega-3 fatty

acids present in these diets are primarily responsible for the improvements.

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Additionally, increasing the levels of B vitamins in the diet seems to protect against

detrimental mood effects.

3.3 Vitamins, Minerals and Mood

Researchers have been investigating relationships between nutrition and mood for

decades. The discovery of antidepressants in the 1950’s resulted in a reduction in the

interest of natural treatments (Kaplan, Crawford et al., 2007). Despite this, studies

have indicated associations between individual micronutrients and various illnesses.

For instance, vitamin C has long been associated with the prevention of the common

cold (Hemilä, 1992) and as such, cold and flu symptoms are often treated with the

addition of a vitamin C supplement to the diet (Hemilä, 1994). Furthermore, zinc has

been shown to help treat symptoms of the common cold, either as an oral supplement, a

nasal preparation or as a lozenge (Braun and Cohen, 2009). Additionally, zinc has been

associated with mood modulation (Levenson, 2006), and is an essential cofactor in

wound healing and immune function (Braun and Cohen, 2009). When used during

pregnancy, folic acid has consistently been shown to reduce the incidence of neural tube

defects (MRC Vitamin Study Research Group, 1991). The function of Vitamin E

within the cardiovascular system is well known (Kaul, Devaraj et al., 2001). Vitamin E

has been shown to effectively reduce blood pressure in hypertensive individuals

(Boshtam, Rafiei et al., 2002), and has been suggested to protect against atherosclerosis

due to its antioxidant effects (Stephens, Parsons et al., 1996). Vitamin E has been

successfully used in the treatment of Alzheimer’s disease, as an adjunctive treatment

along with cholinesterase inhibitors (Bonner and Peskind, 2002). Higher levels of

vitamin E have been associated with a reduced risk of cognitive impairment and

dementia in older adults (Morris, Evans et al., 2005), although results of

supplementation studies yield mixed results.

Vitamin D deficiency, in combination with limited sun exposure in children and infants

results in rickets, a condition that is defined by the softening of the bone, often resulting

in bowed legs (Wagner, Greer et al., 2008). There is evidence to suggest that vitamin D

is crucial in infancy for the development and growth of the brain, as well as the

musculoskeletal system (Braun and Cohen, 2009). Additionally, links have been made

between vitamin D and depression, although results from supplementation studies have

yielded mixed results (Berk, Sanders et al., 2007).

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A number of micronutrients have been implicated in mood regulation (Benton and

Donohoe, 1999). For example, thiamine (vitamin B1) deficiency has been associated

with poor mood. Thiamine supplementation has been shown to improve mood in

healthy individuals with an adequate thiamine status (Benton, Griffiths et al., 1997).

Investigations of folate have found associations between low folate levels and

depressive symptoms (Fava, Borus et al., 1997; Alpert, Mischoulon et al., 2000;

Tolmunen, Voutilainen et al., 2003; Sachdev, Parslow et al., 2005; Dimopoulos, Piperi

et al., 2007; Kaplan, Crawford et al., 2007). Similarly, some researchers have identified

associations between depressive symptoms and lower levels of vitamin B12 (Baldewicz,

Goodkin et al., 2000; Penninx, Guralnik et al., 2000; Dimopoulos, Piperi et al., 2007),

while others have not (Fava, Borus et al., 1997; Bjelland, Tell et al., 2003; Tolmunen,

Voutilainen et al., 2003; Sachdev, Parslow et al., 2005). Recent research has also found

that individuals with lower levels of vitamin B12 and folic acid are often more depressed

than those with higher levels. For instance, it has been observed that as many as 30% of

patients hospitalized for depression are deficient in vitamin B12 (Hutto, 1997). Despite

these findings, the relationship between depression and B12 deficiency is still unclear.

Vitamin B6 levels have also been shown to be lowered in depressed patients (Hvas, Juul

et al., 2004a).

Nutrition is an important factor in health and functional ability. The prevalence of

inadequate nutritional state in the elderly is high, and may have detrimental effects on

both physical and psychological well-being (Bhat, Chiu et al., 2005). The elderly are

particularly vulnerable to nutritional deficiencies. A US epidemiological study reported

that total food intake decreases with age, which results in the intake of nutrients well

below the recommended dietary allowance (Wakimoto and Block, 2001). This is

particularly relevant to those who are ill or institutionalised. However, the intake of

nutrients, in seemingly healthy, community-dwelling older adults, are also often below

adequate (Buhr and Bales, 2009). Vitamin D, calcium, E and B12 are most often the

nutrients that are affected by suboptimal intake.

Malnutrition, defined as a change from a normal nutritional state, is common in the

elderly (Bhat, Chiu et al., 2005). Malnutrition, both under-nutrition and obesity,

contributes to problems such as cardiovascular disease, impaired immunity and bone

formation, which in turn increases frailty (Bhat, Chiu et al., 2005). In elderly

67

populations, under-nutrition is more common, particularly in those that are

institutionalised. A study by Visvanathan et al. (2003) reported a high prevalence of

under-nutrition in patients utilising domiciliary care (care given in home) in South

Australia. Of the 250 individuals enrolled in the study, 43.2% were not well nourished,

and were found to be more likely to be admitted to hospital, spend more than 4 weeks in

hospital, fall, or lose weight, than those who were adequately nourished (Visvanathan,

Macintosh et al., 2003). In hospitalised elderly patients, malnutrition has been linked to

increased risk of morbidity and mortality (Vetta, Ronzoni et al., 1999). Obesity in the

elderly is less common than under-nutrition, with a prevalence ranging between 14-

17%, but declining in those aged over 80 years (Kennedy, Chokkalingham et al., 2004).

Collectively, these studies highlight the importance of adequate nutritional status as a

determinant of successful, healthy ageing.

3.3.1 Vitamins, Nutrition and Cardiovascular Health A diet rich in fruit and vegetables may provide the nutrients required to reduce the risk

of cardiovascular disease. Data from the Nurse’ Health Study and the Health

Professionals’ Follow-up Study indicate that the risk for coronary heart disease is

reduced with greater fruit and vegetable intake. Increasing fruit and vegetable intake by

1 serving per day was associated with a 4% lower risk for coronary heart disease.

Specifically, leafy green vegetables and vitamin-C rich fruits and vegetable contributed

the most protective effects against coronary heart disease (Joshipura, Hu et al., 2001).

A recent systematic review by Mente et al. (2009) found strong evidence supporting

association between high-quality dietary patterns and the protection against coronary

heart disease. The review reported strong associations of the protective role of vegetable

intake, nuts and Mediterranean style and high-quality diet with coronary heart disease.

Furthermore, a poor diet, high in trans-fatty acids and high glycaemic load, typical of a

“Western” dietary pattern, was associated with coronary heart disease as harmful

factors.

The results from this research suggest that the addition of nutritional interventions will

aid in the reduction of cardiovascular risk factors. As such, researchers have

investigated the effects of multivitamin supplementation on improving cardiovascular

outcomes, with mixed results. Holmquist et al. (2003) found that the risk of myocardial

infarction may be reduced by low-dose multivitamin supplementation. Likewise, a

large prospective study of older women with or without cardiovascular disease, found

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that multivitamin use was inversely associated with myocardial infarction in women

without CVD (Rautiainen, Åkesson et al., 2010). Conversely, results from the

Women’s Health Initiative clinical trials found that the use of a multivitamin

supplement had no influence on the risk of cardiovascular disease in post-menopausal

women (Neuhouser, Wassertheil-Smoller et al., 2009). Similarly, data from the

Physicians’ Health Study II, found that compared to placebo, a daily multivitamin for

over a decade, did not reduce major cardiovascular events, myocardial infarction, stroke

or CVD mortality (Sesso, Christen et al., 2012).

Multivitamin usage can also benefit other markers of cardiovascular health, such as

blood biomarkers. Multivitamin users typically have higher serum nutrient

concentrations, lower levels of biomarkers associated with disease, and lower

homocysteine, C-reactive protein, cholesterol markers and blood pressure (Block,

Jensen et al., 2007). As will be discussed in the next section, higher homocysteine

concentrations can have detrimental effects on health. High homocysteine levels have

been associated with mood dysfunction and cardiovascular disease, and randomised

trials of B vitamins have been shown to effectively reduce homocysteine concentrations

in the blood. Similarly, randomised controlled trials of MVM supplements have been

effective in reducing homocysteine concentrations in as little as 8 weeks (Harris,

Macpherson et al., 2012). Other studies have employed longer interventions with

similar results (Wolters, Hermann et al., 2005; Wolters, Hickstein et al., 2005).

The reduction of oxidative stress can also benefit mood. Oxidative stress has also been

linked to endothelial dysfunction and cardiovascular disease progression (Heitzer,

Schlinzig et al., 2001). MVM supplementation for 4 weeks, has been shown to reduce

markers of oxidative stress such as reducing oxidative DNA damage in an elderly group

(Ribeiro, Arçari et al., 2007). Oxidative stress and its impact on mood will be discussed

in more detail in section 3.8 of this chapter.

3.4 B Vitamins and Homocysteine

The B vitamins are a group of water-soluble vitamins with many important roles within

the human body and nervous system. Table 3-1 lists the main B vitamins, along with

their traditional names.

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Table 3-1. The B Group vitamins along with their traditional names.

B1 Thiamine B6 Pyroxidine

B2 Riboflavin B7 Biotin (or Vitamin H)

B3 Niacin B9 Folate

B5 Pantothenic acid B12 Cobalamin

Vitamin B1 is an important coenzyme in carbohydrate metabolism, involved in the

breakdown of glucose into energy, and also has a role in nerve impulses (Bourre, 2006).

Vitamin B2 is involved in oxidation-reduction reactions, as well as carbohydrate, fats

and protein metabolism and energy production. Vitamin B2 is an essential co-factor in

the conversion of vitamin B6 and folic acid into their coenzyme forms, and in the

conversion of tryptophan to niacin. Vitamin B3 is involved in energy metabolism, and in

the conversion of riboflavin and vitamin B6 into their active forms (Huskisson, Maggini

et al., 2007a). Vitamin B6 is required for the synthesis of many neurotransmitters and is

essential for the conversion of tryptophan to niacin (Huskisson, Maggini et al., 2007a).

Furthermore, B complex vitamins and vitamin C are essential for the formation of many

neurotransmitters, amino acids and biogenic amines (see Figure 3-1). For example,

within the CNS, dopamine and noradrenaline metabolism requires the availability of

vitamin B2, B6, B12, nicotinamide, folate and vitamin C (Huskisson, Maggini et al.,

2007a).

This review will focus on B12, folate and B6. Much of the literature has been devoted to

the influence of these particular B vitamins and their role on mood and

neuropsychological processes. The involvement of the B vitamins under investigation

in the one-carbon cycle, the reduction of homocysteine and the production of

neurotransmitters is of particular relevance to the current thesis.

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Figure 3-1 - The impact of selected vitamins on neurotransmitter synthesis via amino

acid metabolism. Taken from Huskisson et al. (2007a)

3.4.1 Vitamin B12

Vitamin B12 refers to a group of cobalt-containing vitamers, also known as cobalamins

(Bender, 2003). Vitamin B12 is utilised in the metabolism of almost all cells within the

human body. It is involved in the synthesis and regulation of DNA, and is essential for

normal functioning of the brain and nervous system, as well as for the formation of

blood (Sabeen and Holroyd, 2009). Vitamin B12 is synthesised by bacteria, and is

therefore not present in plant foods (Baik and Russell, 1999; Bender, 2003). It can be

found naturally in animal products such as meat, fish, poultry and eggs, milk and milk

products (Brody, 1999). The NHMRC (2006) recommends a daily intake of 2.4µg/day

for adults.

There are two active forms of vitamin B12 found with the human body.

Methylcobalamin and 5-deoxyadenosyl cobalamin. Methylcobalamin is a necessary

component of the methylation reaction for the formation of the enzyme methionine

synthase (Sabeen and Holroyd, 2009). In turn, methionine synthase is required for the

synthesis of methionine from homocysteine. Therefore, in vitamin B12 deficiency,

homocysteine levels rise due to decreased utilisation (Sabeen and Holroyd, 2009). 5-

deoxyadenosyl cobalamin is necessary for the production of haemoglobin and in the

production and maintenance of the myelin sheath (Sabeen and Holroyd, 2009). A

metabolite of B12 utilisation is methylmalonic acid (MMA). Often, elevated levels of

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both MMA and homocysteine are used as markers of B12 deficiency, even in the face of

“normal” serum B12 levels.

Vitamin B12 deficiency increases with age. Prevalence statistics of below normal B12

concentrations vary greatly in the literature, ranging from 3% to 40%, depending on

diagnostic thresholds and cut-offs (van Goor, Woiski et al., 1995; Baik and Russell,

1999). In the elderly, the most common cause of B12 deficiency is due to problems with

absorption (Sabeen and Holroyd, 2009). The rate of gastric atrophy in elderly

populations is high, and has been proposed to be a factor contributing to the decline in

B12 status with increasing age (Baik and Russell, 1999). However, gastric problems

alone may not be the only contributing factors, a reduced intake of B12 containing foods,

and the ability to absorb B12 through the intestine may also have a role in B12 deficiency

as we age (Wahlin, Bäckman et al., 2002). Evidence is now showing that foods that are

fortified with B12 are contributing a larger proportion of food-bound B12 in older adults,

as the form in which fortified B12 is delivered is not affected by gastric dysfunction

(Baik and Russell, 1999).

Vitamin B12 deficiency has many well-documented clinical associations. For example,

low B12 levels have been associated with pernicious anaemia and macrocytosis (Stabler

and Allen, 2004) as well as neuropsychological changes such as confusion, memory

impairment and slowing of information processing (Hector and Burton, 1988).

Furthermore, some researchers have found that B12 deficiency can lead to psychiatric

disturbances (Bell, Edman et al., 1991), while others have not (Perkins, Stern et al.,

1994). Additionally, overall psychological distress has been linked to B12 deficiency

(Baldewicz, Goodkin et al., 2000). Similarly, specific mood states such as depressed

mood (Penninx, Guralnik et al., 2000), anxious and irritable mood (Hector and Burton,

1988) have also been linked to B12 deficiency. See section 3.5 for a review of the

literature.

3.4.2 Vitamin B9 (Folate)

Vitamin B9, also known as Folate, is a collective term, used to describe folic acid and

derivatives with similar activities such as tetrahydrofolate (THF). The many forms of

folate are most commonly found in foods, however free folic acid (pteroyl glutamic acid

or PGA) is most often used in supplements and food fortification due to its higher

bioavailabilty and higher stability than the other folate derivatives (Bender, 2003;

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National Health and Medical Research Council, 2006). PGA is metabolised to

methylfolate within the body. Methylfolate is the form of folate that is transported in

blood plasma (Lucock, 2004). The human diet is rich in folates, however, in food they

are highly unstable and easily destroyed by cooking and processing. Folates are

generally found in fresh leafy green vegetables, nuts, fortified grain products, sprouts,

kidney and liver (Kelly, 1998). The RDI for folate is 400µg/day for adults (National

Health and Medical Research Council, 2006).

In developed countries, approximately 8% to 10% of the population have a folate

deficiency or low folate stores (Bender, 2003). Studies in older populations have

revealed that although folate deficiencies are common, levels tend to remain constant

over the age span (Wahlin, Bäckman et al., 2002). Adequate folate levels are critical for

growth and development, particularly during pregnancy. Furthermore, links between

suboptimal folate status and a number of degenerative diseases such as atherosclerosis

as well as cancer has been identified in the literature. For example, the Medical

Research Council Vitamin Study Research Group (1991), through an international,

multicentre randomised controlled trial, provided the first clear evidence of the link

between maternal folate status and the incidence of spina bifida. Their research showed

that the risk of infants born with spina bifida decreased when mothers were

supplemented with folate during pregnancy (MRC Vitamin Study Research Group,

1991). Additionally, folate is important for amino acid metabolism, in particular

homocysteine (Paul, McDonnell et al., 2004), where folate deficiency has been linked to

hyperhomocysteinemia (Boushey, Beresford et al., 1995). Furthermore, folate

coenzymes are essential for DNA synthesis, in that without folate, living cells cannot

divide (Bottiglieri, 2005; National Health and Medical Research Council, 2006). Folate

is also critical for blood and nerve tissue formation (Huskisson, Maggini et al., 2007a).

Folate deficiency has also been implicated in neurological dysfunction (Selhub, Bagley

et al., 2000), and psychiatric disorders such as depression (Hutto, 1997). Additionally,

folate has been linked to neurotransmitter metabolism, in particular, serotonin,

dopamine and noradrenaline (Reynolds, Carney et al., 1984; Bottiglieri, Hyland et al.,

1992), which could be a potential mechanism behind links with depression.

Mandatory folate fortification of cereal and grain products was introduced in Australia

between 2007 and 2009, prior to this folate fortification was voluntary (Food Standards

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Australia New Zealand, 2009). The result being that most bread (excluding organic) in

Australia will contain folic acid, up to 120µg per 100 grams (approx. 3 slices),

approximately one third of the recommended daily intake for adults. The reduction of

neural tube defects is the primary motive for mandatory fortification. Despite the

introduction of voluntary folate fortification in 1995, along with education programs,

encouraging the use of supplements and health claims on food packaging, most women

are still not consuming adequate amounts of folate. Food Standards Australia New

Zealand (2009) estimate that the number of neural tube defects affected pregnancies will

decrease by 14% each year.

Folate fortification not only has the potential to lower the incidence of birth defects, but

also to decrease levels of homocysteine. There is evidence to suggest that mandatory

fortification in the United States has helped to reduce folate deficiency and subsequently

decrease homocysteine levels (Pfeiffer, Caudill et al., 2005). However, folate repletion

can mask B12 deficiency, and in turn homocysteine levels become dependent on B12

status (Quinlivan, McPartlin et al., 2002). For example, Alshatwi (2007) found that

homocysteine concentrations in their sample were largely related to B12 deficiency, but

not folate deficiency.

3.4.3 Vitamin B6

Vitamin B6 has six active forms, the main form in human tissue is pyridoxal 5’-

phosphate (PLP), while pyridoxine hydrochloride is more commonly found in

supplements (National Health and Medical Research Council, 2006). Vitamin B6 can

be found in both plant and animal foods, good sources of which are fish, organ meats,

legumes, eggs nuts and bananas (Braun and Cohen, 2009). Due to its presence in many

foods, B6 deficiencies are fairly rare in developed countries, although 10%-20% of

people have marginal B6 deficiencies (Bender, 2003). Bates et al. (1999) reported that

75% of elderly people living in institutions had B6 levels below the norm, and of the

community dwelling elderly in the sample, almost half (48%) had suboptimal B6 levels.

The NHMRC (2006) recommends an intake of 1.3mg/day for adults, increasing to

1.5mg/day for women over 50 years, and 1.7mg/day for men over 50.

PLP is an essential cofactor in lipid metabolism (Bender, 2003), and is an important

cofactor in the conversion of homocysteine to cysteine (Bottiglieri, 2005). Furthermore,

B6 plays a large role in the synthesis of serotonin, dopamine and norepinephrine

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(Higdon, 2003), and is a cofactor in the tryptophan-serotonin pathway (Hvas, Juul et al.,

2004a). There is increasing evidence that B6 levels are lower in depressed patients

(Hvas, Juul et al., 2004a).

3.4.4 Homocysteine

Homocysteine is a non-protein, sulphur amino acid (Sabeen and Holroyd, 2009).

Homocysteine has a close relationship with B12, folate and B6, in that the activity of

homocysteine relies on an adequate supply of these vitamins (Reutens and Sachdev,

2002; Bottiglieri, 2005). The metabolism of homocysteine is one of the many reactions

involved in one-carbon metabolism. One-carbon metabolism involves a series of

pathways essential for the repair and synthesis of DNA, the production of S-

adenosylmethionine (SAMe), and the synthesis of neurotransmitters and many other

methylation reactions (Mattson and Shea, 2003). Homocysteine is created entirely

through the methylation cycle and therefore cannot be obtained from any dietary source

(See Figure 3-2) (Bottiglieri, 1996, 2005). The methylation cycle is critical for both its

formation and removal (Bottiglieri, 2005). Homocysteine is formed by the

demethylation of SAMe, the major methyl donor in the brain. All methylation reactions

that utilise SAMe, produce S-adenosylhomocysteine (SAH), which is rapidly converted

into homocysteine inside of cells by SAH-hydrolase (Bottiglieri, 2005). Homocysteine

production is the favoured reaction under normal circumstances, however if

homocysteine levels rise, SAH production is favoured (Bottiglieri, Hyland et al., 1994).

SAH has been shown to be a powerful inhibitor of SAMe dependent methylation

reactions, affecting reactions involving DNA, RNA, proteins, phospholipids (Yi,

Melnyk et al., 2000), and neurotransmitters (Bottiglieri, Laundy et al., 2000).

Both folate and B12 are required for the methylation of homocysteine to methionine,

which is the immediate precursor of SAMe. Functional deficiency of either vitamin

results in raised concentrations of homocysteine. SAMe is synthesised through the one-

carbon cycle, and its production relies on adequate levels of folate and B12. SAMe is

essential for the production of hormones, neurotransmitters, nucleic acids, proteins and

phospholipids. Additionally, the synthesis of serotonin, norepinephrine and dopamine

require SAMe (Spillmann and Fava, 1996). There is both clinical and experimental

evidence linking folate, SAMe and monoamine metabolism (Bottiglieri, Laundy et al.,

2000), and clinical research studies have shown SAMe to be a powerful antidepressant

(Bell, Potkin et al., 1994; Bottiglieri, Hyland et al., 1994). For instance, depressed

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patients have been shown to have low SAMe concentrations in CSF (Bottiglieri,

Godfrey et al., 1990), and depressive symptoms can be improved with increases in

plasma SAMe levels (Bell, Potkin et al., 1994).

In the presence of B6, homocysteine is converted into cystathionine (Bottiglieri, 2005),

which is the precursor to glutathione, a major endogenous antioxidant (Dringen and

Hirrlinger, 2003). Glutathione levels have been shown to be reduced in depression

(Gawryluk, Wang et al., 2011).

Figure 3-2 - The folate and Homocysteine-methionine cycle. Adapted from Malouf and

Grimley Evans (2008).

Homocysteine has been associated with cognitive impairment, cardiovascular disease,

and mood dysfunction (Bottiglieri, 2005). Additionally, poor diet, lifestyle factors like

smoking and high alcohol consumption has been shown to increase total homocysteine

concentrations (Tolmunen, Hintikka et al., 2004b). Particularly relevant to the elderly

population is the growing evidence of high total homocysteine concentrations and age-

associated diseases. High homocysteine level in the elderly have been linked to

coronary heart disease, stroke, peripheral vascular disease, cognitive impairment,

dementia, depression, osteoporotic fractures and functional decline (Nygård, Vollset et

al., 1995; Kuo, Sorond et al., 2005; Wang, Wang et al., 2008). Results from the

Hordaland Homocysteine Study, a longitudinal study that has observed homocysteine

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status in over 18,000 people, has demonstrated that high total homocysteine levels in the

elderly are a risk factor for cardiovascular morbidity, cardiovascular and non-

cardiovascular mortality and hospitalisation for cardiovascular related conditions

(Refsum, Nurk et al., 2006). Homocysteine has also been found to be a moderate risk

factor for stroke and ischemic heart disease in a recent meta-analysis (Homocysteine

Studies Collaboration, 2002).

High levels of circulating homocysteine have been found to be toxic to vascular

endothelial cells (Weiss, Keller et al., 2002; Austin, Lentz et al., 2004), neuronal cells

(Mattson and Shea, 2003) and can cause damage to DNA, induce oxidative stress and

apoptosis (Lipton, Kim et al., 1997; Mattson and Shea, 2003). Recent data suggests that

total homocysteine concentrations are highly dependent on B12 status when folate levels

are replete (Quinlivan, McPartlin et al., 2002), this in itself is cause for concern,

particularly in the elderly, who are more susceptible to B12 deficiency.

There is increasing evidence in the literature regarding a link between high

homocysteine levels and depressive symptoms (Almeida, Flicker et al., 2004;

Tolmunen, Hintikka et al., 2004b; Almeida, McCaul et al., 2008; Wang, Wang et al.,

2008). The homocysteine hypothesis of depression, outlined by Folstein et al. (2007)

suggests that elevated levels of homocysteine may cause depression. This model of

depression, posits that elevated homocysteine causes vascular disease of the brain, and

interferes with neurotransmitter production, which in turn could lead to the development

of depression, particularly in older adults. The authors use evidence from a number of

health areas to support their hypothesis. However, it is still unclear if homocysteine is a

direct cause of depressive symptoms, or simply a marker of B12 and folate deficiency

(Bottiglieri, 2005). For example, changes in dietary patterns caused by depressive

symptomology may result in less nutrient rich foods in the diet, leading to disturbances

in homocysteine methylation.

A commonly replicated finding is higher homocysteine levels in elderly populations,

particularly those in geriatric settings (Selhub, Jacques et al., 1993; Marengoni, Cossi et

al., 2004). Additionally, the relationship between homocysteine and vascular disease is

well documented (Boushey, Beresford et al., 1995; Hankey and Eikelboom, 1999).

Raised total homocysteine concentrations are associated with an increased risk of

atherosclerosis and other vascular diseases (Temple, Luzier et al., 2000). Elevated

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homocysteine may also increase vascular disease of the brain (Sachdev, 2004).

Research has found that increased serum homocysteine increases the risk of stroke and

silent brain infarcts. Furthermore, increased total homocysteine levels are also

associated with ischemic white matter disease (Vermeer, Van Dijk et al., 2002). As

described in chapter 2 (section 2.2.1), white matter hyperintensities are common in the

elderly, however seem to be increased in those with depression, suggesting that

cerebrovascular disease is common in the depressed elderly.

Furthermore, as will be described in the following chapter (Chapter 4), there is

increasing evidence suggesting that reducing homocysteine levels with B vitamin

supplementation can reduce symptoms of depression (Coppen and Bailey, 2000). It has

also been suggested that raised homocysteine levels may impair neurotransmitter

metabolism, which may in turn lead to depression (Bottiglieri, Laundy et al., 2000).

Folstein et al. (2007) suggests that an association between homocysteine and depression

is supported by current evidence, however more research is needed in this area in order

to accept this theory.

Correlational and epidemiological evidence of homocysteine, and B vitamins and mood

will be discussed in the following section (section 3.5).

3.5 The Relationship between B Vitamins, Homocysteine and Mood in

the Elderly.

As described in the sections above, the B vitamins have an important role in the

synthesis of neurotransmitters, and have subsequently been associated with mood

disturbance. Deficiencies of B12, folate and/or B6 can result in an increase in total

homocysteine, which has been associated with many poor health outcomes. The

following section will describe the evidence of epidemiological studies that have

assessed the relationships between B vitamins, homocysteine and mood. The results

from randomised controlled trials will be discussed in Chapter 4.

3.5.1.1 Homocysteine Levels and Mood Symptoms There is increasing evidence to suggest a relationship between total homocysteine

concentrations in the blood and mood. Cross-sectional research has investigated this

relationship in both clinical populations as well as healthy, community-dwelling

individuals. Findings from the Kuopio Ischemic Heart Disease Risk Factors Study, in

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924 men, aged 46-64, revealed that higher serum total homocysteine was associated

with higher levels of depressive symptoms (Tolmunen, Hintikka et al., 2004b).

Similarly, Almeida et al. (2004) identified a relationship between total plasma

homocysteine concentrations and depression scores in a sample of 262, community-

dwelling older females. They found that higher levels of homocysteine were linearly

associated with higher depression scores. This relationship was not the same for

anxiety symptoms, where they found no significant associations. In the cross-sectional

Health in Men study, of 3752 men aged over 70 years, it was found that for every unit

increase in total homocysteine, the odds ratio for prevalent depression increased by 4%.

Furthermore, this study discovered that men who had previously suffered from

depression, had significantly higher total homocysteine concentrations than those who

had never suffered from depression (Almeida, McCaul et al., 2008). Lastly, Wang et al.

(2008) compared homocysteine concentrations between a group of patients with major

depression and a group of healthy controls and found that the depressed group had

significantly higher levels of total homocysteine than the control group.

3.5.1.2 B vitamins, Homocysteine and Mood Symptoms Cross-sectional research is also highlighting a link between vitamin B12, folate and

mood, although these results are more varied than those for homocysteine. Findings

from the Conselice Study of Brain Aging, in 584 elderly Italians, revealed that

regardless of gender, those with combined vitamin deficiency (B12 and folate) had

significantly higher plasma homocysteine levels. At follow-up, 21.7% of men, and 40%

of women had developed depression. In male participants, the risk of depression was

not associated with homocysteine or vitamin status. However, in women, the incidence

of high homocysteine was associated with four times higher risk of developing

depression compared to control (Forti, Rietti et al., 2010). Results from a sub-study,

drawn from the sample in the Personality and Total Health (PATH) Through Life

Project, identified that low folate levels and high homocysteine levels were related to

depressive symptoms, while no significant relationship between B12 and depression was

observed (Sachdev, Parslow et al., 2005). Furthermore, data taken from the Hordaland

Homocysteine Study found that plasma total homocysteine was significantly related to

depression scores, but not anxiety scores, while there were no significant associations

revealed between B12, and folate, with depression or anxiety (Bjelland, Tell et al.,

2003). Kim et al. (2008) followed 631 Korean people aged over 65 years and found

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that at baseline, depression scores were associated with lower B12 levels and higher

homocysteine, while folate was not significantly related. At follow-up, depression was

associated with lower baseline folate and B12 levels and higher homocysteine.

Additionally, a relative decrease in B12 levels and an increase in homocysteine over the

2-year study period were associated with incident depression. Changes in folate status

were not related to depression.

Clinical researchers have also highlighted the link between B vitamin status,

homocysteine and clinical mood disorders. For instance, Bottiglieri et al. (1992) found

that 21% of the depressed patients in their sample had severe folate deficiency. In

another study conducted by Bottiglieri et al. (2000) it was found that severely depressed

individuals had significantly higher levels of plasma total homocysteine compared to

healthy controls participants and participants with other neurological disorders.

Additionally, when compared to both control groups, the depressed participants had

significantly lower levels of red blood cell folate, however no differences in vitamin B12

levels were found across the groups. Results from a sub-group of the Rotterdam Study

found that depression was associated with hyperhomocysteinemia, B12 and folate

deficiency, however when functional disability and cardiovascular pathology was

adjusted, the relationship between folate deficiency and hyperhomocysteinemia and

depression was weakened (Tiemeier, van Tuijl et al., 2002). Baseline data from the

Women’s Health and Aging Study suggest that B12 deficiency is associated with a

twofold risk of severe depression, as measure on the geriatric depression scale. Folate

and homocysteine were not associated with depression in this sample; however, serum

MMA levels were significantly higher in those with depression. MMA is considered a

marker of B12 deficiency. B12 levels in depressed participants were lower, but failed to

reach significance (Penninx, Guralnik et al., 2000). Dimopoulos et al. (2007) identified

a relationship between homocysteine levels and depression. They found that the group

with depression had significantly higher levels of homocysteine than the control group.

Folate and B12 levels were significantly lower in the depressed group, compared to the

control group. Another study found that higher levels of B12 were associated with a

better treatment outcome for depressed patients (Hintikka, Tolmunen et al., 2003).

Similarly, a study conducted by Ebesunun et al. (2012) compared blood biomarkers of a

group of depressed patients to control participants. The results indicate that the

depressed group had significantly higher levels of homocysteine (116% higher), and

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significantly lower levels of B12, total cholesterol, high density lipoprotein (HDL)

cholesterol and low density lipoprotein (LDL cholesterol), than control participants.

Levels of folic acid, tryptophan and triglycerides did not differ between the groups.

Additionally, Şengül et al. (2014) found no differences in the concentrations of serum

folate and B12 between depressed and control participants in their sample. Furthermore,

no associations between depressive symptoms and folate and B12 levels were observed

(Şengül, Uygur et al., 2014).

Similar relationships between B12, folate and homocysteine have been observed in non-

clinical samples. The results of these studies are more variable than the data from the

clinical studies. Ramos et al. (2004) found that low folate status was associated with

depressive symptoms in elderly Latina women, but not men. Baldewicz et al. (2000)

found associations between psychological distress and lower B12 levels. Specifically,

significant inverse associations between depression, anxiety and confusion scores on the

POMS and B12 levels were observed in the sample. In another study, the same group

found that B6 deficiency was a significant predictor of overall psychological distress. In

particular they found that increases in depressed, fatigued and confused mood states

were significantly associated with B6 deficiency (Baldewicz, Goodkin et al., 1998). The

Dublin Healthy Ageing Study measured holotranscobalamin, serum vitamin B12 and

homocysteine and depressive symptoms in a larger group of healthy older adults

(Robinson, O'Luanaigh et al., 2011). Holotranscobalamin is a more reflective measure

of B12 in the tissue than traditional serum B12 measures. The results from this study

found a strong association between depressive symptoms and holotranscobalamin.

Homocysteine was weakly associated with depressive symptoms, but this relationship

disappeared when other confounding factors were taken into account. Serum B12 levels

were also associated but were somewhat weaker than the associations found for

holotanscobalamin (Robinson, O'Luanaigh et al., 2011). A study by Ng et al. (2009)

found a linear relationship between folate levels and depressive symptoms in their

sample. Participants with depression in their sample had significantly lower mean

folate levels or folate deficiency. Mean B12 levels did not differ across the groups,

however B12 deficiency was present significantly more in the depressed sample than the

non-depressed group.

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Conversely, data from the Hordaland Homocysteine Study, found no associations

between folate and B12 with anxiety or depression. Plasma total homocysteine was not

significantly associated with anxiety, but were significantly related to depression scores

(Bjelland, Tell et al., 2003). Hvas et al. (2004a) found associations between low B6

status and symptoms of depression in a sample of 140 individuals. No associations

between depressive symptoms and folate, B12, MMA or homocysteine were observed in

the sample.

3.5.2 B-Vitamin interventions for improving mood Evidence regarding the important role that B vitamins play in maintaining healthy mood

states is described above. To summarise, the B vitamins, B6, B12 and folate, are

required for the synthesis of neurotransmitters implicated in mood dysfunction and the

regulation of homocysteine levels. Despite these findings, very few studies have

investigated the effects of B vitamin supplementation on mood. The sections below

detail the findings from randomised controlled trials. The first section (3.5.2.1)

describes the evidence from trials that have used B vitamins as an intervention for

lowering homocysteine levels. The section that follows (3.5.2.2) provides an account of

the trials investigating the effects of B vitamins on measures of mood, and the last

section (3.5.2.3) provides the results from trials that have used B vitamins (mainly

folate) as adjunct treatments to traditional antidepressant treatments in clinical settings.

3.5.2.1 B-Vitamin Supplements for Lowering Homocysteine In the majority of cases, age-associated increases in homocysteine, as well as B vitamin

deficiency, can be avoided by dietary interventions. However, adherence to a healthy

diet, such as a Mediterranean-Style diet may not be enough to keep homocysteine levels

and B vitamins in the healthy range. As described in the previous chapter (section 3.4),

the nutrients in foods are often degraded or destroyed through cooking and processing

(Kelly, 1998), resulting in a reduced nutrient intake. Therefore, the addition of a

nutritional supplement to the diet may help to redress the loss of vitamins that occur

when we cook our foods. Studies have shown that supplementing with B12, folate and

B6 results in the lowering of homocysteine in the elderly in as little as 4 months

(Lewerin, Nilsson-Ehle et al., 2003). In a six-month trial of vitamin B12 and folate, total

homocysteine levels were reduced by 36% (Eussen, de Groot et al., 2006).

Furthermore, results from the FACIT trial, a three-year folate intervention in 816

healthy elderly individuals, revealed that folate supplementation resulted in a 26%

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reduction in total homocysteine concentrations (Durga, van Boxtel et al., 2007). A 2-

year, Australian trial found that supplementing with a B-vitamin combination (folate,

B12 and B6), was effective in reducing total homocysteine levels in elderly men. This

effect was even more pronounced in those with higher homocysteine concentrations and

lower folate levels prior to the intervention (Flicker, Vasikaran et al., 2006).

Furthermore, homocysteine levels in a group of older males at risk of cognitive decline

were lowered after only 8 weeks of MVM supplementation (Harris, Macpherson et al.,

2012). These results suggest that supplementation with B vitamins or a MVM is an

effective way of reducing elevated levels of homocysteine. Homocysteine is a risk

factor for a number of adverse health outcomes such as cardiovascular disease and

depression. Therefore, the lowering of homocysteine through nutritional interventions

provides another avenue of potential treatment in both the treatment and prevention of

mood disorders in the elderly.

3.5.2.2 B-Vitamin Interventions and Mood The links between B vitamin, homocysteine status and mood, provided by cross-

sectional research have prompted researchers to examine the effects of nutritional

interventions on mood. Due to the relatively consistent relationships observed in the

epidemiological literature, it is conceivable that adding a B vitamin supplement or a

combination of B vitamins to the diet would be effective in improving mood. However,

the results of randomised controlled trials have yielded inconsistent results. These

inconsistencies most likely arise due to differences in methods used, supplements and

intervention periods across the various studies, making it hard to draw any solid

conclusions about the efficacy of B vitamin supplementation in improving mood. For

many years, research predominantly investigated the efficacy of one or a few vitamins,

such as B vitamins, in the treatment of complex mood disorders. More recently,

investigators have moved away from individual nutrient strategies, and multivitamin

and mineral combinations have been the focus of research (see chapter 4). The

following review will discuss trials that have investigated the effects of B vitamins on

mood. To be considered for review, only double-blind, placebo-controlled RCTs were

included. Furthermore, only supplement regimes that contained B vitamins only, and

were administered daily were considered. Trials were excluded if the B vitamin

interventions were administered with other vitamins, minerals, herbals or omega-3 fatty

acids. Furthermore, all trials had at least one mood outcome, either as a primary or

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secondary outcome. Only trials that were conducted in healthy participant groups were

included. Participants were considered healthy if they were free from psychological

disorders, cardiovascular disease, and other major health conditions. No restriction was

placed on age so as not to limit the number of studies included in the review, and to get

a more complete understanding of the evidence for B vitamins and mood across the

lifespan.

A literature search yielded 6 trials that met the criteria for review. As shown in Table

3-2, three of the studies were conducted using a younger sample of participants; two

looked at samples across a range of ages, while one was conducted in an elderly group.

The mood assessments differed across all of the trials, making comparison across the

studies difficult. Additionally, the B vitamins under examination varied across the

studies.

Bryan et al. (2002) conducted a trial that investigated the individual effects of B12, folate

and B6 supplements on mood, in a group of healthy women. The women ranged in age,

and were grouped into younger, middle-aged and older groups for analysis. Mood was

assessed using the Centre for Epidemiological Studies – Depression scale (CES-D) and

the Profile of Mood States (POMS). After 5 weeks, no treatment effects were observed

for any of the vitamin groups.

A study conducted in an all-male group investigated the effects of folic acid

supplementation on subjective mood in 28 healthy young males (Williams, Stewart-

Knox et al., 2005). Participants were supplemented with 100µg of folate for six weeks

followed by an increased dosage to 200µg for an additional six weeks. Mood was

assessed using the Positive and Negative Affect Schedule (PNAS) at baseline and 12

week follow-up. While blood biomarkers were improved by the folate intervention, no

effects on subjective mood were observed. Another all-male study, conducted in an

elderly sample over 24 months, did not reveal any significant improvements in mood

(Beck Depression Inventory; BDI) after supplementing with a B vitamin combination

(B12, folate and B6), when compared to the placebo group (Ford, Flicker et al., 2008).

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Table 3-2. Summary of the B vitamin trials that have investigated mood.

Study (first

author, year)

Supplement Duration n Participants Measures Results

Benton, 1997 Thiamine 2 months 127 Healthy, young females.

Mean age = 20.3 years

POMS, GHQ-30 Improvement on POMS. Increases in

clear-headedness, composure and

energy.

Bryan, 2002 B12; B6; Folate 35 days 211 Healthy, young, middle-aged

and elderly women

CES-D, POMS No mood effects

Doll, 1989 B6 3 month

crossover

63 Healthy women, aged 18-49

years

Symptom

checklist

Reductions in emotional premenstrual

symptoms

Ford, 2008 B12 + Folate + B6 2 years 299 Healthy elderly men, aged

over 75 years

BDI No mood effects

Hvas, 2004b B12 3 months 140 Individuals with elevated

MMA, aged 19-92 years

MDI No mood effects

Williams, 2005 Folate 6 weeks 28 Healthy males, aged 21-39

years

PNAS No mood effects

GHQ – General Health Questionnaire; POMS – Profile of mood states; CES-D - Centre for Epidemiological Studies – Depression scale; BDI – Beck Depression Inventory; MDI –

Major Depression Inventory; PNAS – Positive and Negative Affect Schedule.

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Hvas et al. (2004b) assessed the relationship between vitamin B12 supplementation and

symptoms of depression, in a group of people with elevated plasma methylmalonic acid

(MMA) levels. Supplementation with B12 did not help to improve symptoms of

depression. Furthermore, no associations between B12 and plasma MMA and the degree

of depression were found in the sample.

Studies of vitamin B6 and mood are scarce. Studies that were identified in the literature

centre on the treatment of premenstrual symptoms in women. Vitamin B6

supplementation seems to reduce negative mood effects in women suffering from

premenstrual syndrome (PMS). For instance, Doll et al. (1989) found that B6

supplementation helped to improve the emotional disturbances of PMS, such as

depression, irritability and fatigue.

Benton et al. (1997) found that 2 months of thiamine (vitamin B1) supplementation

improved overall mood (as measured by the POMS). Specifically, they found that

improving thiamine status resulted in feeling more clearheaded, composed, energetic

and general mood improved.

Taken collectively, it is hard to draw concrete conclusions regarding the effectiveness of

B vitamins in improving aspects of mood. Of the six studies reported, positive benefits

of B vitamin supplementation on mood were found in only two of the studies (Doll,

Brown et al., 1989; Benton, Griffiths et al., 1997). These differing results may most

likely stem from differences in supplements, as well as differences in the mood

variables and tools used to measure improvements. To date there is no consensus in the

literature regarding the measurement of mood symptoms. The only common scale

reported in the studies reviewed above was the POMS. However, while one study

showed an improvement on the scale (Benton, Griffiths et al., 1997), the other did not

(Bryan, Calvaresi et al., 2002). Differences in observable benefits could be due to the

sensitivity of the mood measures. It could be that using tools that are more likely to

detect subtle changes in mood would result in more positive findings.

Differences in the study populations may also account for the disparity in the literature.

All of the studies included in the review included healthy participants, free from

cognitive impairment and mood disorder. For instance, the positive results reported by

Benton et al. (1997) were observed in a group of university student, that may be more

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vulnerable to mood disturbances and stress due to their studies. Similarly, the

participant in the Doll et al. (1989) study suffered from moderate to severe PMS. The

mood symptoms of these participants would likely have been higher than those in the

other studies assessed.

3.5.2.3 Adjunct Treatment of Depression with Folate and Antidepressants

As already discussed in section 3.5.1.2 a common biochemical finding in depressed

patients is the incidence of low serum and red cell folate levels (Bottiglieri, Hyland et

al., 1992; Tiemeier, van Tuijl et al., 2002). Moreover, folate deficiency has been

correlated with reduced levels of serotonin metabolites in cerebral spinal fluid (CSF)

(Bottiglieri, Hyland et al., 1992), suggesting a role of folate in depression. Additionally,

since their introduction in the 1950’s the efficacy of selective serotonin reuptake

inhibitors (SSRI) in reducing depressive symptoms has not improved. Approximately

50% of patients on SSRIs respond to the treatment, compared to 32% of those on

placebo treatments (Coppen and Bailey, 2000). Taken together, these findings have

influenced researchers to seek alternative treatment options such as the interaction

between B vitamin supplementation as both a treatment for depression or as an adjunct

to traditional antidepressant treatments. The following section will discuss research that

has utilised folate as adjunct therapy to traditional antidepressant treatments.

Correlational research has linked low folate status to poor treatment outcomes in

depressed patients. Fava et al. (1997) found that patients with low folate levels in their

sample, were less likely to respond to treatment than those with normal folate levels.

Similarly, Papakostas et al. (2004) found that low serum folate levels were associated

with reduced treatment response to fluoxetine treatment, among a group of patients with

fluoxetine-resistant major depression. Furthermore in another study by the same group,

they found that folate levels were linked to the timing of clinical improvement after

SSRI treatment, in that they observed that those with lower serum folate levels

experienced a delay in clinical improvement compared to those with normal folate

status (Papakostas, Petersen et al., 2005). Taken together, this research lends support to

the hypothesis that disturbances of methylation in the nervous system may be

implicated in the aetiology of some forms of mental illness, depression in particular.

This research has prompted others to examine the effects of the addition of folate to the

treatment regime of those with depression, in order to improve treatment outcomes.

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Coppen and Bailey (2000), conducted a RCT in which all 127 participants were treated

with fluoxetine, and randomised to either the folate (500µg) or placebo groups. It was

found that patients in the folate group had a significantly better response to treatment

after 10 weeks, than those in the placebo group, however when male and females were

analysed separately, this result was limited to female participants only. The authors

concluded that only in female participants, the co-administration of folate and

antidepressant medication helps to significantly improve the response to fluoxetine

treatment in depressed patients. Similarly, Resler et al. (2008) found that six weeks of

combined fluoxetine and folate resulted in significantly more improved depressive

symptoms than fluoxetine and placebo. This study found that the addition of folate to

SSRI treatment augmented the antidepressants actions rather than accelerating its

effects, as the difference between folate and placebo was only significant after six

weeks of treatment.

Alpert et al. (2002) found that 8-weeks of adding folinic acid (a highly bioavailable

folate that is metabolised into methyltetrahyrdrofolate (MTHF)) to a regimen of SSRI or

venlafaxine (selective norepinephrine reuptake inhibitor; SNRI), in a group of patients

with treatment resistance depression resulted in a significant reduction of depressive

symptoms. Likewise, Bell et al. (1992) augmented tricyclic antidepressant medication

with 10mg each of B1, B2 and B6 or placebo for four weeks. B vitamin supplementation

improved levels of B2, B6 and B12 in the supplement group. Furthermore, they observed

a trend towards a greater improvement in depressive symptoms in the supplement group

compared to the placebo group.

Another study found that administering methyl-folate to a group of depressed or

schizophrenic patients with borderline or overt folate deficiency, while also taking

standard psychotropic or antidepressant medication, resulted in significantly improved

clinical and social outcomes, compared to the placebo group (Godfrey, Toone et al.,

1990). Conversely, Bedson et al. (2014) found that adding 5mg of folate to

antidepressant medication had no effect on depressive symptoms in a group of moderate

to severely depressed patients.

Collectively, folate appears to be an affective adjunctive treatment option for those with

treatment resistant depression, although to date only a handful of RCTs have been

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conducted to investigate these effects, nevertheless, preliminary evidence seems

promising.

3.5.2.4 The efficacy of B vitamins for improving mood Overall, B vitamins are essential for the healthy functioning of the body. The B

vitamins are involved in numerous processes within the body, and deficiency can cause

detrimental health effects and are an essential component of the methylation cycle, in

which homocysteine is both produced and re-methylated. The role of B vitamins in

mood has been well established in the literature. B vitamins are essential for the

formation of SAMe, which is vital for the production of serotonin, dopamine and

norepinephrine, all of which have been implicated in mood disorders. Epidemiological

research has highlighted the importance of an adequate level of B vitamins in the

system, with a number of associations between B vitamin deficiency and poor mood. A

small number of randomised controlled trials have investigated the mood effects of B

vitamin supplements in healthy samples. The results of these trials are inconsistent. Of

the six trials that were reviewed, only two studies reported mood benefits of

supplementation. Both of these studies were conducted in a younger group, and may

have included participants that were predisposed to mood dysfunction, such as

university students, and women suffering from moderate to severe PMS. The evidence

from trials conducted in clinical groups is more consistent. When folate is added as an

adjunct to standard depression treatments, depressive symptoms are more effectively

reduced than traditional antidepressants alone. The results from the clinical groups are

encouraging, and provide evidence for the role of B vitamins, folate in particular, in

mood modulation.

The bulk of the current chapter has been dedicated to the B vitamins, and the effects that

they have on mood processes. The remainder of the chapter will describe the role of

other micronutrients and minerals, and how they may also influence mood, in order to

provide a theoretical framework for the remained of the thesis.

3.6 Vitamin D

Vitamin D is a group of fat-soluble sterol (cholesterol-like) substances that are

responsible for enhancing the absorption of calcium, iron, magnesium, phosphate and

zinc in the intestine. Cholecalciferol (D3), is the most important form of vitamin D, and

is most often found in animal products and fish oils. D3 is also produced within the

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body, through the conversion of a cholesterol-based precursor, 7-dehydrocholsterol,

within the skin. When exposed to sunlight, 7-dehyrocholesterol is converted to

cholecalciferol over a period of 2-3 days (Braun and Cohen, 2009). Ergocalciferol (D2),

is the major synthetic form of provitamin D, and most often found in fungi and yeasts.

D2 is often rare in the diet, but commonly found in supplements. The traditional role of

Vitamin D3 is in the regulation of calcium and bone metabolism, but it has recently

been implicated in muscle function, cancer prevention, immune function and the

prevention of DNA damage (Cherniack, Troen et al., 2009; Halicka, Zhao et al., 2012).

Vitamin D3 and D2 have also been shown to be membrane antioxidants that inhibit

lipid peroxidation limiting cell damage (Wiseman, 1993).

Vitamin D has many roles within the central nervous system (Kalueff and Tuohimaa,

2007). Vitamin D activates receptors in the limbic system, cortex and cerebellum, areas

that are implicated in the regulation of behaviour, as well as stimulating the release of

neurotrophins implicated in the regulation of neuronal development (Kalueff and

Tuohimaa, 2007). Moreover, a neuroprotective effect of vitamin D has been suggested

in the literature, in that vascular injury to the brain can be reduced by the anti-oxidant

and anti-inflammatory effects of vitamin D (Buell and Dawson-Hughes, 2008).

Vitamin D has been found to be widely deficient in Western populations (Inderjeeth,

Nicklason et al., 2000; Pasco, Henry et al., 2001) and links have been made between

depression and vitamin D status (Berk, Sanders et al., 2007). For instance, Wilkins et

al. (2006) studied a group of elderly participants, and found that 58% of the group had a

frank deficiency of vitamin D. Additionally, they found that low vitamin D levels were

strongly associated with the presence of mood disorder within the group. However,

others have found no associations between serum vitamin D levels and major

depression (Schneider, Weber et al., 2000). Additionally, a large meta-analysis found

that supplementing with vitamin D was associated with a decrease in mortality (Autier

and Gandini, 2007).

Intervention studies have yielded mixed results. Gloth et al. (1998) found that vitamin

D supplementation was more effective in reducing symptoms of depression in a group

of individuals with seasonal affective disorder, than treatment with phototherapy.

Lansdowne and Provost (1998) reported that vitamin D3 supplementation significantly

improved positive effect and potentially decreased negative affect, in a group of healthy

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younger students, after only 5 days of intervention. However, vitamin D

supplementation was not associated with improvements in mental health scores on the

SF-12, in a large cohort of elderly women (Dumville, Miles et al., 2006). Similarly,

Harris and Dawson-Hughes (1993), found no effect of low dose vitamin D

supplementation on mood in a group of healthy women.

3.7 Vitamin A

Vitamin A is a family of fat-soluble compounds that share biological function and

structure with retinol. Vitamin A is an essential component of many processes within

the body. One of its main functions is in the maintenance of the retina, as well as ocular

health and function. Furthermore, Vitamin A is essential for reproduction, embryotic

growth, and healthy bone development in children (Ross, McCaffery et al., 2000).

Additionally, vitamin A is involved in the maintenance and differentiation of epithelial

cells, immune function (Tanumihardjo, 2011), and has been implicated in cancer

prevention (Braun and Cohen, 2009). Vitamin A also acts a free radical scavenger in

the body, exhibiting potent antioxidant capabilities (Braun and Cohen, 2009). While the

body stores of vitamin A are good, disposal of excess amounts is poor, which can lead

to toxicity if intake is too high (Ross, 2006). Natural vitamin A can be found in foods

as itself or in precursor form (typically carotines) that is converted into vitamin A in the

body. Vitamin A is typically found in animal products such as liver, red meat, fish,

eggs, milk, butter and cream (Braun and Cohen, 2009). A search of PubMed yielded no

RCTs assessing the role of vitamin A in mood.

3.8 Antioxidant Vitamins and Oxidative Stress

The oxidative stress theory of ageing posits that oxidative stress contributes to ageing

by increasing the oxidative damage to a number of macromolecules within the body,

leading to a loss in functional cellular process (Pérez, Bokov et al., 2009). Oxidative

stress refers to an imbalance of oxidants over antioxidants, resulting in cellular damage,

such as cell dysfunction or cell death (Berk, Ng et al., 2008). The brain and CNS are

particularly susceptible to oxidative stress, as the antioxidant defence systems are not

adequately equipped to prevent oxidative damage (Halliwell, 2006), supporting the role

of oxidative stress in acute and chronic neurodegenerative diseases (Chung, Dawson et

al., 2005). Recently, impaired antioxidant defences have been associated with

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depression (Maes, De Vos et al., 2000). It has been suggested that oxidative stress may

be an underlying factor in the pathology of mood and psychiatric disorders (Gawryluk,

Wang et al., 2011).

Homocysteine and one-carbon metabolism (Sugden, 2006; Durmaz and Dikmen, 2007)

can influence oxidative stress, as well as levels of particular nutrients (vitamin D, folate

and B12) (Berk, Sanders et al., 2007; Tsao, Yin et al., 2007), mainly due to effects on the

glutathione (GSH) system. GSH is an essential antioxidant in the brain due to its role in

preventing oxidative damage (Dringen and Hirrlinger, 2003), and has recently been

implicated in depression and other psychiatric disorders (Maes, Mihaylova et al., 2010;

Gawryluk, Wang et al., 2011). Reports of increased oxidative damage in individuals

with mood disorders are increasing. Cumurcu, Ozyurt et al. (2009) found serum total

oxidant status and oxidative stress index were increased in participants with MDD

compared to controls. Others have found that lipid peroxidation markers in the blood

were higher in those with MDD compared to controls (Bilici, Efe et al., 2001; Sarandol,

Sarandol et al., 2007).

The two main antioxidant vitamins, vitamins C and E, in the human body will be briefly

described in the sections below.

3.8.1 Vitamin E:

Vitamin E is a major fat-soluble antioxidant. It is transported in blood through lipids,

such as triglyceride and low-density lipoprotein (LDL) cholesterol (Maes, De Vos et al.,

2000). Vitamin E has an important role within the brain. It has been shown to be

protective against ageing in combination with selenium, and helps to maintain cellular

structures within the brain (Bourre, 2006). Furthermore, low levels of vitamin E have

been associated with an increased risk of dementia, and antioxidant supplements have

been shown to reduce the risk of Alzheimer’s disease (Bourre, 2006). Additionally,

depressed patients have been shown to have lower serum vitamin E levels than healthy

controls (Maes, De Vos et al., 2000). However, to date there have been no reported

interventional trials with Vitamin E and its effects on mood.

Some prospective research provides support for a protective role of vitamin E in CVD

prevention (Rimm, Stampfer et al., 1993; Stampfer, Hennekens et al., 1993; Kushi,

Folsom et al., 1996), while others do not (Klipstein-Grobusch, Geleijnse et al., 1999).

Data from the Cambridge Heart Antioxidant Study (CHAOS), a large RCT of 2002

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patients, indicate that treatment with Vitamin E substantially reduces the rate of non-

fatal myocardial infarction in patients with coronary atherosclerosis, after 1 year of

treatment (Stephens, Parsons et al., 1996).

3.8.2 Vitamin C:

Vitamin C is one of the most important antioxidants in the human body. Human beings

are not able to synthesise Vitamin C endogenously, therefore it must be obtained from

dietary sources. Although relatively rare in developed countries, marginal vitamin C

deficiency is often observed in people living in poverty, war or famine, chronic

alcoholics or the institutionalised elderly (Braun and Cohen, 2009). Further, Vitamin C

is important for numerous reactions within the body, such as cholesterol metabolism,

the breakdown of energy from fatty acids and in the synthesis of neurotransmitters, in

particular noradrenaline and serotonin (Braun and Cohen, 2009).

Associations between vitamin C and cardiovascular disease are conflicting in the

literature. Enstrom et al. (Enstrom, Kanim et al., 1992) found that increased intake of

vitamin C was associated with reduced mortality due to cardiovascular disease.

However, others have not found the same associations in their data. Gale et al. (1995)

found that vitamin C status was associated with risk of mortality from stroke, but not

coronary heart disease. However, pooled cohort data suggests that high levels of

vitamin C intake reduces the risk of major coronary heart disease events (Knekt, Ritz et

al., 2004).

A search of PubMed did not locate any trials investigating the effects of vitamin C, in

isolation, on mood (depression or anxiety). A small number of studies have been

conducted with Vitamin C, in combination with other vitamins, such as B vitamins, or

in a multivitamin formulation. These trials will be reviewed in Chapter 4.

3.8.3 The Synergistic Effects of Vitamins C and E: Like many vitamins, vitamins C and E work well in combination. Due to their

antioxidant properties, vitamins C and E have an important role in cancer prevention, by

blocking the formation of carcinogens in the stomach, enhancing immune function and

protecting DNA and lipid membranes from oxidative damage (Byers and Perry, 1992).

Similarly, mixed results for associations between Vitamin C and CVD have been

reported in the literature (Enstrom, Kanim et al., 1992; Gale, Martyn et al., 1995). The

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results from RCTs investigating combinations of C, E and beta-carotene have not

reported any significant cardiovascular effects of supplementation. However, Plantinga

et al. (2007) found that a combination of vitamins C and E was effective in improving

endothelial function and arterial stiffness in a group of male hypertensive patients,

supplemented for 8 weeks.

A literature search did not yield any RCTs of Vitamins E and C in relation to mood.

3.9 Minerals

Like vitamins, minerals found in food, are essential for the normal functioning of the

body (LeMone, 1999). Minerals are involved in a number of physiological functions

within the body, such as maintaining haemoglobin levels, muscle growth and

maintenance and in nervous system functioning. Furthermore, a number of minerals

also act as antioxidants within the body. In the body, large amounts of the

macrominerals (calcium, phosphorus, sodium, chloride, potassium, magnesium and

sulphur) are present, while smaller amounts of the trace minerals (iron, manganese,

copper, iodine, zinc, cobalt, fluoride, and selenium) are found (LeMone, 1999).

Like with vitamins, some minerals have been linked to mood dysfunction. Again this is

of particular importance in the elderly where poor mineral nutrition is often observed

(Wood, Suter et al., 1995; Troesch, Eggersdorfer et al., 2012). The minerals described

below have all been implicated to some degree in mood regulation.

3.9.1 Calcium

Calcium is important for many processes within the brain. It is an important

intracellular messenger, as well as an enzyme cofactor. Additionally, calcium is

important for cell signalling, and neurotransmitter release (Smith and Augustine, 1988).

It has long been known that calcium imbalances caused by hyperparathyroidism, often

result in anxiety, depression and cognitive dysfunction. For instance, it has been shown

that depression is often accompanied by reduced calcium concentrations in the blood

erythrocytes (Kamei, Tabata et al., 1998). Additionally, calcium supplementation is

effective in reducing negative mood associated with premenstrual symptoms (Thys-

Jacobs, Starkey et al., 1998).

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3.9.2 Chromium

Chromium is a trace element that is primarily known for its role in the metabolism of

glucose and lipids (Anderson, 1997). Suboptimal chromium intake is common in

industrialised countries and deficiencies can result in impaired glucose tolerance and

increased body fat (Anderson, 1997). Furthermore, links between chromium and

depression have been made in the literature. McLeod, Gaynes and Golden (1999),

reported the results of a series of open-labelled trials of chromium supplementation in

the treatment of antidepressant-refractory dysthymic disorder. The addition of a

chromium supplement to the treatment regime of five patients, lead to the remission of

depressive symptoms in all of the patients. A follow-up case series by the same group

reported significant improvements in symptoms and functioning of 8 patients with

refractory mood disorders, with the addition of chromium supplementation (McLeod

and Golden, 2000). The authors suggested that the potential mechanism driving these

improvements could be the influence of chromium on insulin utilisation and the

subsequent increase in tryptophan levels in the brain. As mentioned earlier, tryptophan

is the immediate precursor of serotonin, and serotonin dysfunction has long been linked

to depression. Furthermore, results of a RCT in 15 medication-free patients with

atypical depression support the role of chromium in depression (Davidson, Abraham et

al., 2003). Davidson et al. (2003) found that significantly more patients (70%)

receiving chromium supplementation than those on placebo (0%) were classified as

responders. A participant was classed as a responder if they showed a decline of at least

66% on the Hamilton Depression Scale, and an improvement on the Clinical Global

Impressions of Improvement Scale. Additionally, 60% of the chromium group achieved

remission of symptoms (i.e. scores less than 8 on the Hamilton depression scale). A

PubMed search did not yield any results of chromium supplementation and mood in

healthy participants.

3.9.3 Zinc

Zinc is an essential trace element, that is required by at least 100 enzymes in the body

(some have reported up to 300) (Nowak and Szewczyk, 2002). Zinc has powerful

antioxidant actions in the brain, targeting free radicals that cause inflammation, and

therefore aiding in the reduction of oxidative stress (Wong and Ho, 2012).

Furthermore, zinc helps to maintain cellular homeostasis to protect against

neurodegeneration. Neurodegeneration is common in depression (see Chapter 2). In the

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elderly, low zinc status may be a contributing factor to age-associated immune

dysfunction and age-related inflammation (Haase and Rink, 2009).

Zinc deficiency has been related to human depression. Chronic electroconvulsive

therapy (ECT), imipramine and citalopram have been shown to increase zinc

concentrations in the brain, particularly in the hippocampus (Nowak and Szewczyk,

2002). Furthermore, in the brain, zinc is most abundant in areas that have been

associated with depression and anxiety, particularly the cerebral cortical regions,

hippocampus and amygdala (Nowak, Szewczyk et al., 2005). Some have suggested that

zinc may act to regulate synaptic transmission, or act as a neurotransmitter itself when

in the synaptic vesicles of specific neurons (Huang, 1997).

While research supports a link between zinc and depression, the precise relationship is

still unclear. Zinc is thought to act via similar pathways as antidepressants, or augment

the effects of antidepressants (Dickerman and Liu, 2011). Zinc supplementation in rats

has been shown to increase brain-derived neurotrophic factor (BDNF) levels. Research

has shown that substances that can increase the expression of BDNF in the cortex and

hippocampus are useful in treating depression (Sowa-Kućma, Legutko et al., 2008).

Through this pathway, zinc and antidepressants modulate and inhibit the function of N-

methyl-D-aspartate (NMDA) receptors (Sowa-Kućma, Legutko et al., 2008; Szewczyk,

Poleszak et al., 2008). NMDA receptor antagonists increase serotonin levels in the

brain, and could potentially battle depression (Löscher, Annies et al., 1993). There has

been some suggestion that the serotonergic system mediates the anti-depressant effects

of zinc, and not the noradrenergic system (Szewczyk, Poleszak et al., 2008).

MDD patients are often found to have serum zinc levels significantly lower than control

patients. Zinc status and the severity of depression symptoms are also related (Nowak,

Zieba et al., 1999; Levenson, 2006). And zinc levels have been found to be lower in

patients with treatment resistant depression (Maes, Vandoolaeghe et al., 1997). The

Zincage Study, conducted in five European countries, found an association between

plasma zinc levels and scores on the MMSE, Geriatric depression scale (GDS), and the

perceived stress scale (Marcellini, Giuli et al., 2006). Results from intervention studies

support the potential antidepressant properties of zinc, when administered in

conjunction with standard antidepressant treatments (Nowak, Siwek et al., 2003; Siwek,

Dudek et al., 2009).

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3.9.4 Magnesium

Magnesium is the fourth most abundant cation in the human body, and the second most

common intracellular cation (Szewczyk, Poleszak et al., 2008). Magnesium is involved

in over 300 essential enzymatic reactions in the body. It is particularly important for

nerve conduction, muscle activity, amino acid and protein synthesis, DNA synthesis and

degradation and immune function. Furthermore, magnesium is involved in the

metabolism of calcium, potassium, phosphorus, zinc, copper iron, sodium, lead and

cadmium, as well as the maintenance of intracellular thiamine homeostasis and

activation (Braun and Cohen, 2009).

Magnesium deficiency has been associated with many diseases, such as cardiovascular

disease (Elwood and Pickering, 2002), neurological diseases (Muir, 2002; Vink and

Nimmo, 2002), and affective disorders (Murck, 2002).

There is limited experimental and clinical data that suggest a possible association

between magnesium and depression. Magnesium is involved in all aspects of the

limbic-hypothalamus-pituitary-adrenocortical axis (Murck, 2002), which has been

linked to regulation of emotions. It is possible that disturbances of this axis could

contribute to mood disorders (Dickerman and Liu, 2011). Like zinc, magnesium is a

NMDA-receptor antagonist, which may be the pathway through which magnesium

exerts it’s anti-depressant actions (Szewczyk, Poleszak et al., 2008). Similarly, animal

models have shown, that like zinc, the anti-depressant actions of magnesium are

possibly mediated by the serotoninergic system (Szewczyk, Poleszak et al., 2008).

Additionally, magnesium deficiency has been associated with impaired protein and

DNA synthesis, which lowers serotonin levels. This has lead researchers to suggest that

magnesium supplementation may be effective for depression treatment (Dickerman and

Liu, 2011).

Recent findings from the Hordaland Health Study suggest that dietary magnesium

intakes are related to depression, in that lower intakes of magnesium were associated

with higher levels of depression (Jacka, Overland et al., 2009). However, correlational

research has yielded mixed findings. While some have found lower serum magnesium

levels in depressed patients (Hashizume and Mori, 1989; Rasmussen, Mortensen et al.,

1989; Zieba, Kata et al., 2000), one study identified elevated serum magnesium levels in

a sample of depressed patients (Imada, Yoshioka et al., 2002). It has been suggested

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that inadequate magnesium intake could be associated with treatment-resistant

depression, although no links have been found in the literature between magnesium

levels and depression severity (Eby and Eby, 2010).

3.9.5 Selenium Selenium is an essential trace element, taken into plants through soil (Benton, 2002).

Selenium has an important role in the body’s antioxidant system, in controlling free

radical molecules and maintaining cell-mediated immunity, in conjunction with

thioredoxin reductase and glutathione peroxidase (Braun and Cohen, 2009).

A number of RCTs have found beneficial mood effects of selenium supplementation.

Benton and Cook (1991) found that selenium supplementation resulted in mood

improvements, in particular decreases in anxiety (as measure by the Profile of Mood

States) after 5 weeks of daily supplementation. Although others have not found the

same mood elevating effects (Hawkes and Hornbostel, 1996; Rayman, Thompson et al.,

2006).

3.10 Phytonutrients and Herbal extracts

Phytonutrients are a group of compounds that have been studied for their various

benefits to health. Although not essential in the diet, these compounds have been found

to have many positive effects within the body.

Flavonoids, a group of naturally occurring polyphenols found in plant-based foods have

been found to have many positive health benefits, with flavon-3-ol (from tea) and

anthocyanin’s (ACN, from berries) emerging as the most neuroprotective forms

(Corradini, Foglia et al., 2011; Devore, Kang et al., 2012; Nehlig, 2013). Flavonoids

are found abundantly in fruits and vegetables, most often in the pigment (Bender, 2003).

It has been suggested that flavonoids are primarily responsible for the protective effects

of a diet rich in fruits and vegetables (Hooper, Kroon et al., 2008).

The supplements used in the studies detailed in Chapters 5 and 6 of the current thesis

contain a number of various herbal extracts and phytonutrients. While the vitamins and

minerals are all at or above the RDA levels, the majority of the phytonutrients and

herbal compounds were present in the supplement at sub-therapeutic levels.

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In summary, this chapter has provided an overview of the vitamins, mineral and

antioxidants and their relationship to mood. The research into dietary intake highlights

the importance of a balanced diet in the prevention of mood disruptions. Vitamin and

mineral rich diets, such as the Mediterranean style diet have been associated with better

mood outcomes, whereas diets high in processed foods and fats are often associated

with poorer mood and depression.

As was discussed, epidemiological research has provided some evidence of B vitamin

status and depressive symptoms, however not all research has found these links. The

evidence that homocysteine levels may influence mood is clearer, with most research

finding that higher homocysteine levels are detrimental to mood.

Impaired antioxidant defences and mood is gaining increasing attention in the literature,

although supplementation studies are lacking. To date there have been no studies of

single antioxidant vitamins in relation to mood. Likewise, the influence of minerals on

mood has been studied very little, and of the research available, mixed results have been

reported.

The results presented in this chapter suggest that numerous vitamins and minerals

contribute to normal mood functioning in isolation. To this point the synergistic effects

of vitamins has not been discussed. The following chapter (Chapter 4) will provide a

more detailed examination of how vitamins work in combination, and how this

synergistic effect may influence mood and stress.

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Chapter 4 The influence of Multi-Nutrient Interventions on Mood

in Healthy Individuals

4.1 Introduction

The previous two chapters provided a broad overview of mood disorders, mood

dysfunction in the elderly, as well as an introduction to single micronutrients, and their

role in mood. The focus of this chapter is more specific, providing more detailed

reviews of the literature regarding multi-nutrient interventions and their effects on

mood. It is worthwhile to consider multi-nutrient interventions separately to individual

micronutrients. The combination of ingredients in a multivitamin may provide different

benefits than a single vitamin intervention. A number of nutrients are required to

complete various metabolic processes in the body. Many processes require the addition

of vitamins or nutrients at different stages of the cycle. A good example of this is the

requirement of B12 and folate in the metabolism of homocysteine. Both folate and B12

are added to the cycle at different stages (Selhub, 1999). Furthermore, greater

reductions in homocysteine are observed when the vitamins are administered in

combination (Homocysteine Lowering Trialists Collaboration, 2005). Another example

is the synergistic effects of vitamins C and E in cancer prevention (Byers and Perry,

1992). Therefore, a combination of nutrients in one supplement may result in greater

effects than supplements administered in isolation.

Human beings have ensured their survival by eating a variety of foods (Mertz, 1994); a

balance of nutrients is required for optimal functioning of the body. Mertz (1994)

suggested that the “one disease-one nutrient” concept should be replaced with

multifactorial nutritional interventions. Mertz proposed that single ingredient

interventions might risk unbalancing and creating deficiencies in other nutrients. We

know from human physiology that vitamins and minerals work synergistically within

the body, therefore it is important to investigate the relationships and interactions of

various vitamins and minerals (Higdon, 2003). For example, as described in Chapter 3,

folate, vitamin B12 and vitamin B6 are more effective in lowering homocysteine levels

when working in combination, than when working in isolation (Homocysteine

Lowering Trialists Collaboration, 2005).

100

Multivitamin and mineral preparations are one of the most widely used dietary

supplements in developed countries, with popularity increasing (Millen, Dodd et al.,

2004; Radimer, Bindewald et al., 2004; Morgan, Williamson et al., 2012). Multi-

nutrient formulas have been shown to improve immunity (Barringer, Kirk et al., 2003),

decrease the risk of birth defects (Czeizel, 2004), and improve quality of life (Krondl,

Coleman et al., 1999; Gariballa and Forster, 2007a). Besides dietary inadequacy or

fighting the common cold, stress and fatigue are often reported as reasons for MVM use

(Carroll, Ring et al., 2000). Furthermore, vitamin deficiencies are commonly found in

elderly groups (Naurath, Joosten et al., 1995; Fairfield and Fletcher, 2002), and as a

group, are more susceptible to nutritional deficiencies (Brownie, 2006), and more likely

to benefit from a nutritional supplement. These deficiencies can lead to neurological

dysfunction (Selhub, Bagley et al., 2000), mild psychiatric symptoms (Marcellini, Giuli

et al., 2006; Long and Benton, 2013) and in some cases mood disorders (Maes,

D'Haese et al., 1994; Coppen and Bolander-Gouaille, 2005).

Most MVM supplements contain all the B vitamins, vitamins A, C, D, E, K, as well as

essential minerals such as zinc, magnesium and calcium. MVM supplements are often

advised when the diet is inadequate. The typical Western diet is often lacking in

essential vitamins and minerals, resulting a large proportion of the population exhibiting

deficiencies in one or more vitamins and minerals (America and Milling, 2008; Jacka,

Pasco et al., 2010). Furthermore, as described in chapter 3, optimal B vitamin intake is

essential for the health and function of the central nervous system. For instance, B

vitamins are crucial to one-carbon metabolism, homocysteine regulation and the

production of neurotransmitters (Mattson and Shea, 2003). Sub optimal B vitamin

intake, resulting in disturbances to methylation reactions have been linked to mood

dysfunction in the literature (Reynolds, Carney et al., 1984; Bottiglieri, Laundy et al.,

2000).

As described in the previous chapter, there is a wealth of evidence from epidemiological

studies suggesting a relationship between micronutrients and psychological functioning,

whereby deficiency of key vitamins and minerals can adversely affect mood. While

Benton (1992) suggests that psychiatric symptoms are the first to appear with

micronutrient deficiency, clinicians are yet to utilise psychological measures when

identifying deficiencies. Benton (2013) suggests that the implementation of

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psychological measures may be particularly sensitive to detecting subclinical vitamin

deficiencies.

The aim of this chapter is to provide the basis of the two interventional trials presented

in this thesis. An exhaustive review of MVM trials that have been conducted in older

groups is presented in section 4.2.2. This review will identify the differences between

studies that have found improvements in mood after supplementation, and those that

have not. It will also help to elucidate the characteristics of the studies that are

important, such as dosage, duration, participant characteristics, or measures.

Ultimately, this review will help to inform the aims and hypothesis of the research

contained within this thesis.

For a more complete understanding of the broader research area, section 4.2.3 will

outline trials conducted in younger populations. MVMs may work differently in

younger adults compared with older, due to different metabolic needs and dietary

requirements. Therefore, the trials are worthy of separate review.

A brief review of studies that have explored the acute actions of MVM supplements is

provided in section 4.2.4. As yet, no research has been conducted in an older

population, so the purpose of this review is only to determine whether there is a

potential for MVMs to influence mood in a short period of time.

The chapter will conclude with the thesis aims and rationale for the two experimental

chapters that follow (Chapters 5 and 6).

4.2 Micronutrient supplementation and Mood: Results from

Randomised Controlled Trials

4.2.1 Multivitamins and Mood Multivitamin and mineral use is common in the elderly with data from the US National

Health and Nutrition Examination Survey found that 44% of the sample aged between

51 and 70 and 46% aged over 71 regularly used a MVM (Bailey, Gahche et al., 2010).

Furthermore, of all dietary supplements examined, MVMs were the most commonly

used supplements (Bailey, Gahche et al., 2010). In Australia, data from a cross-

sectional, national survey showed that almost 15% of adults aged over 50 had used a

MVM in the previous 24 hours (Morgan, Williamson et al., 2012). However, given the

popularity of these supplements, there are surprisingly few randomised controlled trials

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(RCTs) investigating the chronic effects of multivitamins on aspects of mood and stress

in the elderly population. The elderly are among those who are more likely to benefit

from such supplements, due to suboptimal nutritional status, reduced food intake and

absorption issues (Wakimoto and Block, 2001).

It is important to note, that in the majority of studies reported in the literature, cognitive

performance is often the main experimental outcome, and mood effects are secondary.

In the reviews presented below, only the mood data from these studies will be

discussed. For the purpose of the current review, a ‘multivitamin/mineral’ is defined as

a supplement containing at least 4 micronutrients/minerals (excluding B complex

formula’s where only B vitamins are present), similar to the approach taken by Long

and Benton in their recent meta-analysis (Long and Benton, 2013). Additionally, only

double-blind, randomised, placebo controlled trials, with MVMs as a monotherapy were

included. All studies included in the following review had at least one mood outcome,

either as a primary or a secondary outcome. Furthermore, to be considered, MVM

treatments must have been administered daily. Lastly, studies that included an omega-3

supplement were excluded, due to the reported mood effects of omega-3

supplementation. Due to the limited number of trials in the elderly, the health status of

the participants was not an exclusion point for the review.

The following sections make up the literature reviews that present the basis for the two

interventional trials described in subsequent chapters (5 and 6). The first review will

focus on MVM trials that have been conducted with an elderly sample. The second

review will briefly describe the literature available in younger populations. This second

review is provided only for completeness, and is not intended as a comprehensive

review.

4.2.2 Multivitamin Supplementation and mood in Older Adults

A search of the literature resulted in the identification of four RCTs with an elderly

sample that met the criteria for review. Of these studies, only one was conducted in a

group that could be classified as healthy. The remaining three trials used participants

that were ‘at risk’. The intervention periods ranged between 6 weeks to 24 weeks, and

all but one of the MVMs under investigation contained added minerals. Furthermore, all

of the supplements contained vitamin dosages that were at or above the recommended

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daily intake values for older adults. Table 4-1 provides a brief summary of the MVMs

trials conducted in an elderly sample.

Gariballa and Forster (2007b) investigated the effects of a MVM supplement on mood

in a group of acutely ill patients in a hospital setting. The patients were supplemented

with a nutritional supplement drink or placebo. Results from this trial showed that those

in the supplement group had higher blood levels of albumin, red blood cell (RBC) folate

and B12 levels compared to the placebo group at follow-up. Additionally, significant

differences in depression scores were observed between the groups, with those in the

supplement group reporting better scores post supplementation (Gariballa and Forster,

2007b).

The study by Gosney et al. (2008) was conducted in frail elderly individuals living in

nursing homes. Participants were supplemented with a MVM or placebo for 8 weeks.

A significant negative association between depressive symptoms and selenium levels

was found, but no associations between folate and vitamin C were found. A trend

towards a negative association between selenium and anxiety scores was observed, but

this failed to reach significance. Additionally, supplementation was found to improve

symptoms of depression in those that had higher baseline depression scores. This effect

was no longer significant when all participants were included in the model (Gosney,

Hammond et al., 2008).

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Table 4-1. Summary of Chronic MVM Trials conducted in older participants

Study (first

author,

year)


Cockle, 2000 A, C, E, B1, B2, B3,

B6, B12, Folate

24 weeks 139 Healthy males and females,

aged 60-83y

POMS, GDS,

blood measures

No Mood effects

Baseline blood and mood correlations

Increased blood vitamins

Gariballa,

2007b

MV + minerals

(drink)

6 weeks +

6m

follow-up

445 Acutely ill, hospitalised

patients aged over 65 years

GDS Improvements on GDS at 6 month

follow-up

Gosney,

2008

MV + minerals 8 weeks 73 Frail elderly in nursing

homes, aged over 60 years.

HADS, MADRS Reductions of depression scores in

those with high baseline scores.

Harris, 2011 MV + minerals +

herbs

8 weeks 50 Healthy males, aged 50-69y GHQ, DASS,

PSS, POMS,

VAS

Improvements on DASS, GHQ and

alertness

MV – Multivitamin; GHQ – General Health Questionnaire; POMS – Profile of mood states; PSS – Perceived Stress Scale; HADS – Hospital Anxiety and Depression Scale; VAS

– Visual Analogue Scales; GDS – Geriatric Depression Scale; MADRS – Montgomery-Åsberg Depression Rating Scale; DASS – Depression Anxiety Stress Scale.

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Table 4-2. A comparison of the supplement ingredients across the studies in the elderly

Ingredient Cockle

(2000)

Gariballa

(2007b)

Gosney

(2008)

Harris

(2011)

Vitamin B1 (mg) 14 Not reported 1.2 30

Vitamin B2 (mg) 16 1.4 30

Vitamin B3 (mg) 180 14 30

Vitamin B5 (mg) - - 64.13

Vitamin B6 (mg) 22 3 24.68

Vitamin B7 (µg) 2 - 50

Vitamin B9 (µg) 400 600 500

Vitamin B12 (µg) 30 200 30

Vitamin D3 (µg) - 400IU -

Vitamin C (mg) 600 120 165.2

Vitamin E (mg) 100 60 41.3

Calcium (mg) - 5 21

Magnesium (mg) - 100 55.48

Chromium (µg) - 50 6.20

Zinc (mg) - 14 6

Selenium (µg) - 60 26

In a study conducted by our group, Harris et al. (2011) found a significant reduction in

the overall score on the DASS after 8-weeks MVM supplementation, in a group of at-

risk sedentary older men. Additionally, those in the MVM group reported an

improvement in subjective alertness, and general daily functioning.

Conversely, Cockle et al. (2000) investigated the effects of MVMs on mood and

cognitive function in a group of 139 individuals aged between 60-83. Participants were

supplemented for 24 weeks with either a MVM or a placebo. While no treatment

effects of MVM supplementation and mood were observed in this study, blood levels of

vitamins B1, B2, B6 and Biotin were associated with baseline measures of mood

(Cockle, Haller et al., 2000).

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Taken together, it is not possible to draw any solid conclusions from the available data.

Differences in results could be due to a number of reasons. For instance, differences in

the MVM ingredients could be influencing the results (see Table 4-2). The supplements

used by Cockle et al. (2000) did not contain any minerals, while those in the Harris et

al. (2011) study did. As discussed in chapter 3, a number of minerals can have

beneficial effects on mood. While all of the supplements contained doses of vitamins at

or above the recommended daily allowance (RDA), they varied considerably across the

trials. Furthermore, the study conducted by Gariballa and Forster (2007b) did not report

the specific dosages of the supplement they used, only stating that the composition was

set to the RDA. The supplement used in the Gosney study, had the least amount of B1,

B2, B3 and B6, but contained the highest amount of B12 and folate, and was the only

supplement reported to contain vitamin D (Gosney, Hammond et al., 2008). These

differences in supplement composition make it very difficult to make solid comparisons

across the studies.

Another explanation for these differences between the studies could be the participants

that make up the samples. All three of the studies that used vulnerable samples found

effects on mood. For example, Gariballa and Forster (2007b) used a sample of acutely

ill patients in hospital; Gosney et al. (2008) studied frail elderly residing in nursing

homes, and the sample utilised by Harris et al. (2011) were older men with a sedentary

lifestyle. Conversely, Cockle et al. (2000) used a healthy elderly sample of participants.

Another consideration is the difference in supplementation periods across the research

studies. Positive effects of MVM supplementation were found within 6 to 8 weeks in

the studies with a vulnerable sample; however, 24 weeks of supplementation in a

healthy group did not reveal any benefits of MVMs on mood. It could be that in order

to elicit benefits to mood in otherwise healthy elderly individuals, a longer

supplementation period is needed.

Another difficulty in comparing the study outcomes is the variability in the mood

instruments that were administered. Two of the studies used the GDS (Cockle, Haller et

al., 2000; Gariballa and Forster, 2007a), and two used the POMS (Cockle, Haller et al.,

2000; Harris, Kirk et al., 2011). All other measures used across the studies were unique

to that particular study. Again, this makes comparison across the studies difficult.

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In summary, while the popularity of MVM supplements are increasing, particularly in

the elderly (Rock, 2007), very few RCTs have been conducted to investigate the

beneficial effects of these supplements. A few trials have examined the cognitive

benefits of MVMs, but these are also lacking in the literature. With regards to the

purported mood benefits of MVMs, only 4 studies were identified in the literature.

Three of these studies found benefits of MVMs on mood, but were conducted in groups

that can be considered as ‘vulnerable’. One study was conducted in a healthy group of

older adults, and found no improvements in mood after MVM supplementation. As the

majority of individuals that use these supplements in the general population are in

relatively good health, and free from cognitive impairment, more studies in healthy

older adults are warranted.

4.2.3 Multivitamins and Mood in Younger Groups The effects of MVMs on mood have been studied in greater detail in younger groups.

As a group, the younger individuals are less likely to display overt nutrient deficiencies,

however may still benefit from MVM supplementation due to poor diet and lifestyle

choices that are common in Western society (Jacka and Berk, 2007). The following

section will briefly describe the current research findings from younger samples. Table

4-3 summarises the findings of the studies under review.

Briefly, for the current review a “multivitamin/mineral’ was defined as a supplement

that contained at least 3 micronutrients or minerals. Only double-blind, placebo-

controlled, RCTs, which used MVMs as monotherapy were included in the review. The

upper age range of participants in the studies was limited to 55 years of age.

Furthermore, to meet inclusion in the review, all studies must have had at least one

mood outcome, either as a primary or secondary outcome. Furthermore, to be

considered, MVM treatments must have been administered daily. Lastly, due to the

reported effects of omega-3 supplementation on mood, all studies that included an

omega-3 treatment were excluded from the review.

A search of the literature resulted in 9 RCTs that met the criteria for review (see Table

4-3). Four trials included men only; one investigated women only; and the remaining

four used a mix of men and women. The intervention periods varied across the trials,

ranging from one month to 12 months. As can be seen from Table 4-4, the supplements

differed in composition across the trials, particularly in regards to the amounts of B

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vitamins. That being said, all of the supplement dosages were close to, or above the

recommended daily intake values for younger adults.

Three of the trials did not find any effects on mood after chronic MVM supplementation

(Willemsen, Petchot-Bacqué et al., 1997; Haskell, Robertson et al., 2010; Pipingas,

Camfield et al., 2013). However, mood was benefited by MVM supplementation in six

of the studies. Benton and colleagues (1995) found that a 12 month MVM intervention

resulted in improvements in agreeableness, and female participants reported greater

composure and improvements in overall mental health. Carroll et al. (2000) reported

benefits to anxiety and perceived stress after 28 days of MVM supplementation in a

group of males. Similarly, healthy younger males benefited from 33 days of MVM

supplementation in the study reported by Kennedy et al (2010). Specifically, perceived

stress, overall mental health and vigour was improved following the month long

intervention. A subsequent paper by Kennedy et al. (2011) found that, in the same

cohort of participants, MVM supplementation increased participants physical stamina.

Improvements in concentration and mental stamina were also observed after participants

had worked a full day. Stough et al. (2011), found that MVM supplementation in a

group of younger adults, in full-time employment, resulted in reductions of personal

strain, and also improvements in depression/dejection and confusion. Finally,

Schlebusch et al. (2000) reported significant improvements in stress ratings in a group

of 300, highly stressed individuals after MVM supplementation.

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Table 4-3. Summary of MVM studies with younger participants

Study (first author (year))


Benton (1995) MV 12 months 209 Healthy males and female aged 17-27

POMS, GHQ-30 Increase in agreeableness for males and females. Females more composed and better mental health

Carroll (2000) MV + minerals

28 days 80 Healthy males aged 18-42 years GHQ-28, HADS, PSS, rating scales

Reductions in anxiety and perceived stress.

Haskell (2010) MV + minerals

62 (±2) days 216 Healthy females, aged 25-50 years, in full-time employment

SF-36, CFS, POMS, STAI, VAS

No mood effects. Attenuation of fatigue following multi-tasking framework

Kennedy (2010)

MV + minerals

33 (±2) days 215 Healthy males aged 30-55 years, in full-time employment

GHQ-12, POMS, PSS

Improvements on GHQ, PSS and vigour subscale of POMS. Trend toward improvement on overall POMS

Kennedy (2011)

MV + minerals

33 (±2) days 215 Healthy males aged 30-55 years, in full-time employment

Bond-Lader VAS, VAS

Improvements in physical stamina, concentration, mental stamina and alertness.

Pipingas (2013)

MV + minerals + herbs

16 weeks 138 Healthy males and females aged 20-50

GHQ-28, POMS, PILL, CFS

No mood effects in lab. Reductions in stress, fatigue and anxiety on mobile-phone tasks post-dose

Schlebusch (2000)

MV + Minerals

30 days 300 Highly stressed, healthy males and females aged 18-65

HARS, PGWS, BSI, VAS

Reduction in stress

Stough (2011) MV + minerals

12 weeks 60 Healthy males and females in employment, mean age 42.2 years

STAI, POMS, PSQ, OSI-R

Improvements in personal strain, depression/ dejection and confusion

Willemsen (1997)

MV + minerals

28 days 24 Healthy males aged 19-25 years GHQ-12, rating scales

No mood effects. Attenuation of stress response.

MV – Multivitamin; GHQ – General Health Questionnaire; POMS(-D) – Profile of mood states (-Depression subscale); PSS – Perceived Stress Scale; SF-36 – Short Form-36; HADS – Hospital Anxiety and Depression Scale; CFS – Chalder Fatigue Scale; STAI – State-Trait Anxiety Inventory; VAS – Visual Analogue Scales; BDI – Beck Depression Inventory; PILL – Pennebaker Inventory of Limbic Languidness; HARS – Hamilton Anxiety Rating Scale; BSI – Berocca Stress Index; PGWS – Psychological General Well-Being Schedule; PSQ – Personal Strain Questionnaire; OSI-R – Occupational Stress Inventory – Revised.

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Table 4-4. Supplement characteristics for RCTs in younger samples

Ingredient Benton (1995) Carroll (2000)

Haskell (2010)

Kennedy (2010)

Kennedy (2011)

Pipingas (2013) Schlebusch (2000)

Stough (2011)

Willemsen (1997) Women Men

Vitamin B1 (mg)

14

15 4.2 15 15 50 30 15 75 15

Vitamin B2 (mg)

16 15 4.8 15 15 50 30 15 10 15

Vitamin B3 (mg)

180 50 54 50 50 50 30 50 100 50

Vitamin B5

(mg) - 23 18 23 23 68.7 64.13 23 68.7 23

Vitamin B6 (mg)

18.15 10 6 10 10 41.14 24.68 8.25 25 10

Vitamin B7 (µg)

- 150 450 150 150 50 50 150 20 150

Vitamin B9 (µg)

400 400 600 400 400 500 500 - 150 -

Vitamin B12 (µg)

30 10 3 10 10 50 30 10 30 10

Vitamin D3 (µg)

- - 5 - - 200IU 200IU - -

Vitamin C (mg)

600 500 180 500 500 165.2 165.2 1000 130 100

Vitamin E (mg)

91 - 10 50IU 50IU - 50IU -

Calcium (mg) - 100 120 100 100 42 21 100 100 100 Magnesium (mg)

- 100 45 100 100 47.16 57.89 100 140 100

Chromium (µg)

- - 25 - - - - - - -

Zinc (mg) - 10 8 10 10 5 6 - - - Selenium (µg) - - 55 - - 26 26 - - -

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Five trials specifically investigated self-rated stress (Carroll, Ring et al., 2000;

Schlebusch, Bosch et al., 2000; Kennedy, Veasey et al., 2010; Kennedy, Veasey et al.,

2011; Stough, Scholey et al., 2011). Four of these studies reported beneficial reductions

in stress and personal strain after MVM supplementation, while one did not (Kennedy,

Veasey et al., 2011). Interestingly, a number of the studies found that responses to

laboratory stressors or cognitively demanding tasks were attenuated following MVM

supplementation. For example, Willemsen et al. (1997) found that MVM

supplementation attenuated the response to a laboratory stressor in a small group of

participants. Similarly, Haskell et al. (2010) observed that MVM use helped to

attenuate fatigue and improve aspects of cognitive performance after performance on a

cognitively demanding multi-tasking task. Subsequent work by Kennedy et al. (2011)

has shown that multivitamin and mineral supplementation can improve measures of

alertness, mental and physical stamina and concentration, in healthy younger males in

full-time employment. Additionally, they were able to show that the MVM group

reported better concentration and mental stamina at the end of the working day, rather

than in the morning before work commenced. Conversely, work by our group

(Pipingas, Camfield et al., 2013) did not find any stress attenuating effects of 16-weeks

MVM supplementation after completing a similar task to the participants in the Haskell

et al (2010) study.

Of particular interest is recent research from our laboratory, in a group of 138 young

healthy adults. The study did not reveal any significant chronic effects of 16 week

MVM supplementation on mood, which is at odds with our study in an older group, that

found that 63 days of MVM supplementation benefited mood, in men with a sedentary

lifestyle (Harris, Kirk et al., 2011). However, reductions in stress, physical fatigue and

anxiety were observed in the MVM group on at-home mobile phone assessments that

were completed soon after consuming the supplement suggesting a potential acute effect

of MVMs on aspects of mood (Pipingas, Camfield et al., 2013).

To summarise, while there is more data available in younger groups, it is still not

possible to make a solid conclusion regarding the effects of MVM supplementation on

mood. As such, common themes seem to be emerging in the literature, particularly

regarding perceived stress. Four of the nine studies reviewed found improvements in

measures of stress, indicating that MVM supplementation may help to reduce the

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amount of stress experienced by an individual. Furthermore, reductions in fatigue were

observed in two of the studies after a cognitively demanding task, suggesting a

somewhat protective effect of MVMs against combatting fatigue.

4.2.4 Acute Effects of Multivitamin Supplementation: Results from RCTs The above sections (4.2.2 and 4.2.3), detailed the results of studies that have

investigated the chronic benefits of MVMs supplementation on mood. This section will

describe the potential effects that an acute MVM dose (single-dose) may have on mood.

The findings from our recent study in young adults revealed a potential acute effect of

MVMs on mood (Pipingas, Camfield et al., 2013). When recorded in the home with a

mobile phone device, within hours after taking the daily supplement, participants in the

MVM group reported better mood, however this effect was not translated in the

laboratory setting. In the laboratory, participants were asked to abstain from taking the

supplement on the morning of testing so that the chronic (16-week) cumulative effects

of taking the supplement, without potential acute morning effects, could be investigated.

The studies reported in the section below, all administered a single MVM dose and

assessed changes in mood 1-2 hours after ingestion. These studies provide important

information regarding the actions of MVMs. Many of the studies described in the

sections above do not report if participants consume their daily MVM on the day of the

return visit, meaning that potential acute effects on mood may be captured rather than

the long-term (chronic) effects.

To date, only 3 studies were identified in the literature that have investigated the acute

effects of MVM supplementation on mood. Importantly, all of these studies have been

conducted in young children or young adults. The first study conducted by Haskell et al.

(2008) in a group of 81, healthy young children did not find any effects on mood, of a

single dose multivitamin and mineral supplement, as measured by visual analogue

scales and the Chalder fatigue scale.

By comparison, two studies have examined the acute effects of a MVM preparation

with added guaraná. Kennedy et al. (2008) found that the MVM/guaraná preparation

reduced ratings of mental fatigue induced by a cognitively demanding task. Similarly,

Scholey et al. (2013) found that the same MVM/guaraná preparation enhanced self-

rated contentment following a cognitively demanding task. The same effect was not

observed when supplemented with the MVM preparation without the guaraná.

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However, due to the small number of studies that have investigated the acute effects of

MVMs on mood, it is not possible to elucidate if the positive mood benefits described in

both the Kennedy et al. and Scholey et al. papers are due to the effects of guaraná on

mood, or the MVM. Guaraná has long been known to possess neurocognitive effects

(Scholey and Haskell, 2008), as well as increase self-ratings of alertness and calmness

when administered acutely (Haskell, Kennedy et al., 2007). To date, the acute effects of

MVMs on mood have not been explored in an elderly sample.

4.2.5 Summary of Multivitamin RCT Findings In summary, there is a paucity of evidence from multivitamin and mineral trials in the

elderly to draw solid conclusions regarding the influence of supplementation on mood

outcomes. Despite this, the results that are available seem to suggest that mood may be

improved by the addition of a MVM supplement to the diet. This has recently been

confirmed in a meta-analysis published by Long and Benton (2013). They concluded

that across the eight studies included, MVMs had the potential to improve mild

psychiatric symptoms and aspects of mood such as subclinical anxiety and stress in non-

clinical samples.

As to whether these results are due to the characteristics of the participant sample, or

differences in supplement composition remains to be seen. The results from younger

samples are inconsistent. However, some general themes are emerging in the available

literature. A common finding across the studies is a reduction in perceived stress, as

well as an attenuation of fatigue after a cognitively demanding task. Again, differences

in participant characteristics and supplement composition may be influencing the results

seen in these studies.

Regarding acute supplementation of MVMs, the scarcity of evidence from RCTs does

not allow for solid conclusions. Furthermore, the existing positive evidence of mood

effects cannot be attributed to MVMs alone, as the supplements used in past studies

have contained guaraná extracts.

4.3 Summary

In summary, very few randomised controlled trials have investigated the benefits of

supplementing with B vitamins on mood, and the results from this research is limited.

However, the effectiveness of folate in ameliorating depressive symptoms when

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combined with traditional antidepressants is a consistent finding in the clinical

literature.

While there is only a small body of evidence of the mood effects of MVMs in the

elderly, the results are somewhat encouraging. Multivitamin and mineral supplements

have the potential to improve numerous health outcomes, some of which may contribute

to mood improvements. The reduction of oxidative stress, cardiovascular risk and

homocysteine levels, as well as increasing nutrient status may all have an influence on

the mood effects sometimes observed in the literature.

4.4 Thesis aims and rationale

The overall aim of this thesis was to examine the effects of multivitamins and

minerals on mood in a healthy sample of older individuals. There has been very

little research into multi-nutrient interventions in the elderly. Epidemiological research

suggested that B vitamins and other vitamin and minerals are associated with mood. In

terms of individual vitamin supplements, RCT evidence is inconsistent. Evidence from

MVM research suggests that those classified as ‘at risk’ demonstrate mood

improvements after chronic MVM supplementation, however only one study has

investigated mood benefits of MVMs in a healthy group, whereby no benefits were

observed. The inconsistencies in the available data can possibly be explained by the

heterogeneity in sample characteristics, supplements and tools of measurement across

the four studies conducted in the elderly. Acute benefits of MVMs have yet to be

studied in an elderly sample. Additionally, the positive data from acute MVM studies

cannot be attributed to MVMs alone, as the studies that found benefits on mood used

supplements that contained guaraná extracts. Therefore, these results may be due to the

caffeine content contained in guaraná, rather than the MVM. This has yet to be studied

in the literature. With this in mind, the current thesis aimed to investigate both the

chronic and acute effects of MVM supplementation in healthy older individuals. More

specific aims and hypotheses will be provided in each experimental chapter (Chapters 5

and 6).

Another aim of this thesis was to examine the effect of multivitamins on

biochemical and cardiovascular health parameters as potential mechanisms of

action. Previous research has demonstrated numerous benefits of MVMs on the

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cardiovascular system, including reducing oxidative stress, inflammation, and

cholesterol and improving endothelial function. Additionally, cardiovascular health is

closely tied to mood. Therefore, improving cardiovascular health, could in turn

improve mood outcomes. To date only one study has investigated the role of B

vitamins in improving arterial stiffness. The current studies (Chapters 5 and 6) aimed to

address the lack of information regarding MVMs and their effects on cardiovascular

function. Other benefits to health such as increasing the levels of B vitamins and

reducing homocysteine levels may also benefit mood and general health. Both

epidemiological and randomised controlled trials have shown that homocysteine is

consistently reduced with B vitamin or MVM interventions. Reductions in

homocysteine have many health advantages, such as reducing cardiovascular risk,

improving mood, and limiting the rate of cognitive decline. The study contained in

Chapter 5 aimed to investigate the effects of a multivitamin, mineral and herbal

supplement on biochemical markers. More specific aims and hypothesis are outlined in

Chapter 5.

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Chapter 5 The Effects of Chronic Multivitamin Supplementation

in Healthy Older Adults: Mood, Cardiovascular Function and

Blood Biomarkers

5.1 Introduction

Depressive and anxiety disorders are common in the elderly, particularly subthreshold

disorders. Both depression and anxiety cause significant impairment to physical, social

and daily functioning (Blazer, 2003). Furthermore, some argue that both depression and

anxiety manifest differently in the elderly (Flint, 2005a, b), suggesting that the current

diagnostic criteria should be modified for the elderly population. The exposure to and

the impact of risk factors change with age, and therefore the patterns of comorbidity

differ in the elderly (Beekman, de Beurs et al., 2000). In later life, deteriorating health

and cognitive decline are among the most prominent risk factors for the development of

anxiety and depressive disorders (Vink, Aartsen et al., 2008).

Along with mood dysfunction, another common health problem in the elderly is

cardiovascular disease (CVD). In 2008, CVD was the leading cause of death in

Australia (AIHW, 2011). Data suggests that approximately 90% of all Australian adults

have at least one cardiovascular disease risk factor, and 60% of older adults have some

type of vascular illness (AIHW, 2004). Furthermore, patients with depression have

been shown to be two to four times more likely to develop CVD (Ford, Mead et al.,

1998; Penninx, Beekman et al., 2001), and depression remains a risk factor for CVD for

decades after the onset of the first clinical episode (Ford, Mead et al., 1998).

Cardiovascular disease risk may be reduced by a diet rich in fruits and vegetables. The

Nurses’ Health Study and the Health Professionals’ Follow-up Study data shows that

increasing fruit and vegetable intake by 1 serving per day lowered the risk of coronary

heart disease by 4%. These associations were mostly attributed to leafy green vegetables

and vitamin C rich fruits (Joshipura, Hu et al., 2001). These data are supported by a

recent systematic review by Mente (2009), who reported strong associations between a

high-quality dietary pattern and protection against coronary heart disease.

Many links between nutritional status and the manifestation of mood and anxiety

disorders in the elderly have been identified in the literature (Selhub, Bagley et al.,

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2000). However, as shown in the previous chapter, modifying nutritional status through

diet or vitamin supplements can potentially benefit, not only those with clinical mood

disturbances, but also seemingly healthy individuals that may or may not have

suboptimal vitamin status.

As discussed in Chapter 3, research has focused mainly on the B vitamins, due to their

role in one-carbon metabolism, monoamine synthesis, and the regulation of

homocysteine (Mattson and Shea, 2003). Deficiencies of B12, folate and/or B6 can

result in an increase in total homocysteine, which has been associated with many poor

health outcomes, such as cardiovascular disease, stroke, cognitive impairment,

dementia, depression, osteoporotic fractures and functional decline (Nygård, Vollset et

al., 1995; Bottiglieri, 2005; Kuo, Sorond et al., 2005). Epidemiological and prospective

studies have identified links between B vitamin and antioxidant status and mood

dysfunction in the elderly (Kim, Stewart et al., 2008). The findings of these studies

suggest that supplementing the diet may be able to improve mood outcomes in the

elderly.

Mood dysfunction has been linked to lower levels of B12, folate and to a lesser extent

B6, as well as higher levels of homocysteine. Furthermore, homocysteine levels

increase with age and in the majority of cases, homocysteine increase, as well as B

vitamin deficiency can be avoided by the addition of dietary intervention, most often in

the form of supplements. Despite these findings, very few supplementation trials have

been conducted with B vitamins in the healthy elderly. The available evidence from B

vitamin interventional trials is mixed.

In the human body, vitamins, minerals and antioxidants do not work in isolation. As

discussed in Chapter 4 of this thesis, the administration of a combination of vitamins,

minerals and antioxidants, like a MVM supplement, may have a more potent effect on

mood then when vitamins are administered in isolation. Results from MVM trials in

elderly groups, show that supplementation can lead to improvements in mood, although

not all studies have shown this. For example, Cockle et al. (2000) did not observe any

mood effects in their sample. While Gariballa and Forster (2007b), found that

supplementing acutely ill elderly in a hospital with a MVM drink lead to improvements

in both nutritional status, and a subsequent reduction in depression scores. Furthermore,

Gosney et al. (2008) found that a combination of vitamin C, selenium and folate

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reduced levels of depression in a subgroup of their sample with high scores on the

HADS. Findings from our research group have demonstrated supplementation with a

MVM, mineral, antioxidant and herbal supplement can lead to improvements in a

number of aspects of mood and stress in a group of older males (Harris, Kirk et al.,

2011). It is possible that the conflicting findings in the literature may be due to

differences in the specific formulations of the MVM supplements utilised. Due to the

synergistic effects that vitamins have in the body, the simple combinations of vitamins

without the addition of minerals and antioxidants, such as that employed in the Gosney

et al. (2008) and Cockle et al. (2000) studies, may not have been potent enough to exert

a large enough effect on mood. While Gosney et al. (2008) reported an improvement in

a subgroup of individuals, perhaps the effect may have been larger if more vitamins

and/or minerals and antioxidants were included in the supplement. Additionally,

heterogeneity in the characteristics of the sample may also explain the inconsistencies in

the literature. All of the multivitamin and mineral RCTs in older individuals have used

groups that can be characterised as “at risk”, except for the study by Cockle et al.

(2000), that utilised a healthy sample. However, as mentioned above, the supplement

under investigation in this study did not contain any minerals.

Data from trials in younger populations have also yielded mixed results. However, a

trend towards mood improvements is emerging in the literature. Similarly, the data

indicate that MVMs may also be beneficial for combating fatigue, particularly after

performing a cognitively demanding task (Haskell, Robertson et al., 2010). Another

common finding amongst MVM studies in younger groups is the potential of MVMs to

improve symptoms of anxiety and stress (Carroll, Ring et al., 2000; Kennedy, Veasey et

al., 2010), a finding which has been recently confirmed in a meta-analysis of 8 clinical

trials (Long and Benton, 2013).

Multivitamin and mineral supplements have also been shown to have a beneficial effect

on the cardiovascular system. MVM use improves serum concentrations of nutrients,

lowers disease risk, improves levels of homocysteine, C-reactive protein and cholesterol

and markers of oxidative stress and lowers blood pressure. Furthermore, the

cardiovascular parameters that are influenced by MVM supplementation also have

direct or indirect mood effects. Specifically, lowering concentrations of serum

homocysteine has been shown to improve mood, as well as cardiovascular outcomes.

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Likewise, increases in serum concentrations of nutrients discussed in Chapter 3 may

also benefit both mood and cardiovascular health. It is therefore conceivable that

improvements in cardiovascular health may be contributing to the improvements in

mood that are often observed after MVM supplementation.

In summary, there is a lack of research regarding the effects of MVMs and minerals on

mood in healthy older individuals. To date the majority of research in the elderly has

been conducted in ‘at-risk’ groups, or those with clinical mood disorders. The findings

suggest a potential role for MVMs in improving mood in more vulnerable groups,

however whether this is also true for healthy groups is still unclear. Therefore, the

current study aimed to address the lack of information regarding MVM supplementation

on mood in a healthy group of older individuals.

5.2 Aims and hypotheses:

The overall aim of this study was to examine the effects of supplementation with a

combined multivitamin, mineral and herbal supplement for 16 weeks in healthy older

adults. Measures of mood, blood nutrients and biomarkers of health, and indices of

cardiovascular function were investigated.

The primary outcome for the study was mood improvements as measured on the

Depression, Anxiety and Stress Scale (DASS). The DASS has previously shown to

benefit from 8-weeks MVM supplementation in a group of older men (Harris, Kirk et

al., 2011), suggesting that this scale sensitive to nutritional intervention. Therefore, it

was hypothesised that ratings on the DASS would improve after MVM

supplementation. The remaining mood scales were examined as secondary outcomes.

Additionally, the effect of MVM supplementation on the response to stress was

explored. This is the first study to examine the effect of MVM s in attenuating the

response to a laboratory stressor in older individuals. Conflicting evidence for MVMs

and stress response is available in younger samples therefore this analysis was

exploratory.

A secondary outcome was the assessment of cardiovascular function. The effect of

MVM supplementation on arterial stiffness indices was explored. The measures of

arterial stiffness used in the current investigation were augmentation index and

augmentation pressure. As described previously (Chapter 2, section 2.8), arterial

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stiffness increases with age, and has been linked to negative mood states in past

research (Seldenrijk, van Hout et al., 2011). Additionally, there is evidence in the

literature to suggest that elevated homocysteine is associated with increased arterial

stiffness (Tayama, Munakata et al., 2006). While there are no previous reports of MVM

supplementation on augmentation index, there is a small body of evidence suggesting a

potential role of antioxidant vitamins for improving arterial stiffness (Mullan, Young et

al., 2002; Plantinga, Ghiadoni et al., 2007; Rasool, Rahman et al., 2008) . It was

expected that the MVM supplement would improve indices of arterial stiffness after 16

weeks of supplementation. Additional cardiovascular health parameters such as

brachial and central blood pressure were also examined.

Blood nutrient and biomarkers were assessed to provide information about potential

mechanisms of action, as well as the physiological effects of MVM supplementation.

Firstly, in order to establish any baseline relationships between mood and individual

nutrients, correlations between B12, folate, B6, homocysteine, vitamin E and zinc and

mood measures were carried out. Epidemiological research has previously identified

associations between measures of depression and B vitamin and homocysteine status in

both clinical and non-clinical research settings (Bottiglieri, 2005; Sachdev, Parslow et

al., 2005). It was expected that lower B vitamin and higher homocysteine levels would

be correlated with higher levels of mood disturbance in the current sample of older

individuals. As described in Chapter 4, MVM supplementation benefits a number of

biochemical indicators such as inflammation, oxidative stress, cholesterol levels and

endothelial function. In the current study it was hypothesised that the MVM would

significantly improve vitamin B12, B6 and folate levels and significantly lower

homocysteine levels. It was also expected that other blood nutrient and inflammatory

markers would be improved with the supplement.

5.3 Methods

The following section will provide a detailed description of the clinical trial methods,

including information regarding the mood and general health instruments,

cardiovascular and biochemical measures. A description of the baseline characteristics

of the participants and an overview of the statistical analysis plan is provided.

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The trial was registered at the Australian New Zealand Clinical Trials Registry

(ACTRN12612000334808). Ethical approval was obtained from the Swinburne

University Human Research Ethics Committee (SUHREC; Appendix B).

5.4 Participant Characteristics

5.4.1 Screening

5.4.1.1 Inclusion and Exclusion criteria

The sample was made up of community dwelling male and female participants aged

over 50 years. The sample was limited to healthy, non-smoking, right-handed

individuals. Left-handed individuals were excluded from the sample in order to control

for differences in the organisation and functioning of the cerebral hemispheres of the

brain, this formed a component of the study that is not reported in this thesis.

Other exclusion criteria included a history of neurological or psychiatric conditions,

alcohol or drug abuse and dementia. All participants were English speaking, although

English was a second language for 11 participants. Furthermore, those using

antidepressants or antianxiety medications, anticoagulants, anticholinergic or

anticholinesterase inhibitors were not included in the study. Additionally, the use of

MVMs, B vitamins, fish oils, ginkgo biloba, antioxidants or other cognitive enhancing

supplements were not permitted during the study. Those using supplements prior to

enrolment were asked to discontinue use for at least 30 days prior to commencement of

the study protocol, and for the remainder of the trial period.

5.4.1.2 Recruitment

Participants were recruited from the community through newspaper advertisements,

website advertising and email. 11 participants were recruited through a clinical trials

registry company that specialise in clinical trial recruitment. Advertisements were

placed in local newspapers and asked for healthy males and females ages over 50 years,

not currently taking vitamins, blood thinners or antidepressants. Additionally, study

information was placed on the Swinburne research website, and emails were sent to

individuals on the Centre for Human Psychopharmacology participant database.

Participants were compensated with $70 for their time and travel costs.

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5.4.1.3 Screening procedure

Potential participants were screened by telephone, using a screening questionnaire,

made up of questions regarding the inclusion/exclusion criteria. Information regarding

the study protocol was emailed or posted to participants. Eligible participants were

invited to participate in the study. Screening was conducted during the baseline session.

All participants were provided with an explanatory statement and provided written

informed consent (Appendix A). The number of participants recruited and screened for

the study is shown in Figure 5-1.

Figure 5-1. Participant recruitment flowchart

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5.4.2 Screening Measures

5.4.2.1 Mini-Mental State Examination

The Mini-Mental State Examination (MMSE; Folstein, Folstein et al., 1975) is a brief

interview comprising 11 questions used to measure aspects of cognitive function. It is

commonly used in assessment of cognitive impairment and dementia. In the current

study, the MMSE was used to screen for potential memory and cognitive decline, rather

than an outcome of cognitive function. Participants with a score of 27/30 or less were

excluded from the study. Two participants in the current study did not complete the

MMSE, due to hearing impairments, which made administration of the test difficult.

Means and standard deviations for all participants are shown in Table 5-1.

5.4.2.2 National Adult Reading Test - Revised

The National Adult Reading Test – Revised (NART-R; Blair and Spreen, 1989) was

used to control for the potential confounding effects of intelligence. The NART-R gives

a brief, reliable estimate of IQ (NART-R IQ). Participants read a series of difficult or

unusual English words, with the number of errors in pronunciation corresponding to

Full-Scale IQ score. Eleven participants in the current study were unable to complete

the NART-R, as English was a second language, and would confound the results.

Means and standard deviations for all participants are shown in Table 5-1.

5.4.3 Participant baseline demographics and morphometrics

A total of 84 participants were enrolled in the study (46 female). As is shown in Table

5-1 below, the average age of participants was 61.43 (SD = 7.98). Male participants

were slightly older, on average than female participants, but this difference was not

significant (t(82)= 1.801, p=.075). Similarly, there were no significant differences

between male and female participants with regards to education (t(78)= -.20, p=.843),

MMSE scores (t(80)=-.90, p=.372), NART-R IQ (t(71)=.51, p=.610) or Body Mass

Index (BMI (t(80)=1.11, p=.269)).

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Table 5-1 Participant demographics and morphometrics at baseline

Male Female Total

Demographics N M SD Range N M SD Range N M SD Range

Age 38 63.13 8.43 50-78 46 60.02 7.39 50-78 84 61.43 7.98 50-78

Education (Yrs) 37 14.97 3.61 9-22 43 15.16 4.73 8-30 80 15.07 4.22 8-30

MMSE 37 29.03 1.24 27-30 45 29.24 0.96 27-30 82 29.15 1.09 27-30

NART-R IQ 33 117.15 7.74 92-127 40 116.10 9.47 85-128 73 116.58 8.69 85-128

BMI 36 27.10 3.90 21-39.7 46 26.09 4.25 17.9-34.3 82 26.52 4.10 17.9-39.7

5.5 Trial design, randomisation and blinding procedures

The study was a randomised, double-blind, placebo-controlled, parallel-groups trial.

Participants were supplemented with either the MVM preparation or placebo for 16

weeks. Participants were randomised in blocks of 6, with a ratio of 1:1.

5.5.1 Treatment

The multivitamin, mineral and herbal preparations used in the current trial were the

Swisse Ultivite Men’s 50+TM, and Women’s 50+TM multivitamin formulas. These

products are widely available in Australia and have been registered with the Australian

Therapeutic Goods Administration (TGA; ARTG numbers: Men’s 140129, Women’s

140130). The preparations contain vitamins, minerals antioxidants and a number of

herbs. Table 5-2 and Table 5-3 list the ingredients and daily doses for the men’s and

women’s formulations. Participants were asked to consume one tablet per day with

food, which is the standard recommendation defined by the manufacturer. The

appearance of the placebo treatment was identical to the active treatment, and contained

trace amounts of riboflavin (2mg) to produce a “vitamin smell” and to colour the urine,

making a more convincing placebo.

5.5.1.1 Compliance

In order to assess compliance, all participants were required to return all unused tablets

to be counted. In the current study, a limit of 80% compliance was used. One male

participant was excluded from the follow-up analysis due to poor compliance.

5.5.1.2 Determination of Sample Size Previous research conducted at the Centre for Human Psychopharmacology examining

the effects of a similar MVM preparation in 60 older male participants found significant

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improvements in mood and memory. In this previous study, 8 weeks of

supplementation with Swisse Ultivite 50+ displayed an interaction effect size on overall

DASS scores (a measure of clinical mood disturbance) of Hedges’ ĝ= 0.601 (95% CI: -

0.004, 1.21), this being an interaction effect size over and above placebo. Therefore, an

a priori power analysis to determine the number of participants required to replicate the

significant result, with a power of 0.8 and conducting one-tailed tests with 95%

confidence suggested that 34 participants per group would be required if the true effect

size is 0.601. A total of 84 participants will be included in the study in order to account

for a 20% attrition rate.

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Table 5-2: Ingredients of the multivitamin and daily doses for Men

Component Daily Dose RDI Retinyl Acetate (equiv. To 2500 IU of vitamin A) 862.5 µg 900µg Cirtus Bioflavonoids extract 20 mg D-alpha-tocopheryl acid succinate (equiv. Vitamin e 30.25 IU) 25 mg 10mg* Lactobacillius Rhamnosus 80 million

organisms Thiamine Hydrochloride (vitamin B1) 35 mg 1.2mg Lactobacillus Acidophilus 80 million

organisms Riboflavine (vitamin B2) 35 mg 1.3-1.6mg Bifidobacterium Longum 35 million

organisms Nicotinamide (vitamin B3) 25 mg 16mg Vaccinium Macrocarpon Fruit Dry (patented cranberry pacran) 1000 mg Calcium Pantothenate (vitamin B5)(equiv. Pantothenic acid 68.7mg)

75 mg 6mg* Silybum Marianum Dry Fruit (St. Mary’s thistle) (equiv. Flavanolignans calculated as silybin 19.43mg)

1700 mg

Pyridoxine Hydrochloride (vitamin B6)(equiv. Pyridoxine 20.56mg)

25 mg 1.7mg Ginkgo Biloba Leaf Dry (Maidenhair tree) (equiv. Ginkgo flavonglycosides 4.8mg and ginkgolides and bilobalide 1.2mg)

1000 mg

Cyanocobalamin (vitamin B12) 120 µg 2.4µg Tribulus Terrestris Fruit & Root Dry (Tribulus) 1000 mg Cholecalciferol (vitamin D3) (equiv. Vitamin D 200 IU) 5µg 10-15µg* Dulacia Inopiflora Root Dry (Muirapuama) 200 mg Biotin (vitamin H) 200 µg 30µg* Scutellaria Lateriflora Herb Dry (skullcap) 50 mg Folic Acid 500 µg 400µg Vitis Vinifera Dry Seed (Grape seed) (equiv. Procyanidins 7.9mg) 1000 mg Calcium Ascorbate Dihydrate (vitamin C) (equiv. Ascorbic acid 165.3mg)

200 mg 45mg Serenoa Repens Fruit Dry (Saw palmetto) (equiv. Fatty acids 27mg) 300 mg

Phytomenadione (vitamin K) 70 µg 70µg* Urtica Dioica Leaf Dry (nettle) 50 mg Zinc Amino Acid Chelate (equiv. Zinc 20mg) 100 mg 14mg Ubidecarenone (Co-enzyme Q10) (from patented Ultrasome coq10) 3 mg Calcium Orotate (equiv. Calcium 10mg) 100 mg 1,000-

1300mg Cynara Scolymus Leaf Dry (Globe artichoke) 50 mg

Magnesium Aspartate Dihydrate (equiv. Magnesium 6.74mg) 100 mg 420µg Crataegus Monogyna Fruit Dry (Hawthorn) 120 mg Selenomethionine (equiv. Selenium 26mcg) 65 µg 70µg Lecithin Powder – Soy Phosphatidylserine Enriched Soy (equiv.

Phosphatidylserine 2mg) 10 mg

Molybdenum Trioxide (equiv. Molybdenum 45mcg) 67.5 µg 45µg Spearmint Oil 2 mg Chromium Picolinate (equiv. Chromium 50 mcg) 402 µg 35µg* Vaccinium Myrtillus Fruit Dry (Bilberry) (equiv. Anthocyanosides 324mcg) 100 mg Manganese Amino Acid Chelate (equiv. Manganese 4mg) 40 mg 5.5mg* Tagetes Erecta Flower Dry (Marigold)

(Lutein esters calculated as lutein (of Tagetes erecta) 1mg). 100 mg

Ferrous Fumerate (equiv. Iron 5mg) 16.01 mg 8mg Copper Gluconate (equiv. Copper 1.7mg) 12.14 mg 1.7mg* Potassium Iodide (equiv. Iodine 149.83mcg) (equiv. Potassium 46.18mcg)

196 mcg 150µg

RDI = Recommended Daily Intake for Australian women aged over 51. Where two values are shown, the higher refers to RDI for women aged <70. *=Adequate intake (AI)

where RDI was not available. RDI and AI data was obtained from the National Health and Medical Research Council guidelines (2006).

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Table 5-3: Ingredients of the multivitamin and daily doses for women

Component Daily Dose RDI Retinyl Acetate (equiv. To 2500 IU of vitamin A) 862.5 µg 700µg Lactobacillius Rhamnosus 80 million

organisms D-alpha-tocopheryl acid succinate (equiv. Vitamin e 30.25 IU) 20 mg 7mg* Lactobacillus Acidophilus 80 million

organisms Thiamine Hydrochloride (vitamin B1) 30 mg 1.2mg Bifidobacterium Longum 35 million

organisms Riboflavine (vitamin B2) 30 mg 1.1-1.3mg Cirtus Bioflavonoids extract 20 mg Nicotinamide (vitamin B3) 20 mg 14mg Vaccinium Macrocarpon Fruit Dry (patented cranberry pacran) 800 mg Calcium Pantothenate (vitamin B5)(equiv. Pantothenic acid 68.7mg)

70 mg 4mg* Silybum Marianum Dry Fruit (St. Mary’s thistle) (equiv. flavanolignans calculated as silybin 17.14mg)

1500 mg



1000 mg

Cyanocobalamin (vitamin B12) 115 µg 2.4µg Tunera Diffusa Leaf Dry (Damiana) 500 mg Cholecalciferol (vitamin D3) (equiv. Vitamin D 200 IU) 5 µg 10-15µg* Scutellaria Lateriflora Herb Dry (Skullcap) 50 mg Biotin (vitamin H) 150 µg 25µg* Vitis Vinifera Dry Seed (Grape seed) (equiv. procyanidins 7.9mg) 1000 mg Folic Acid 500 µg 400µg Urtica Dioica Leaf Dry (Nettle) 100 mg Calcium Ascorbate Dihydrate (vitamin C) (equiv. Ascorbic acid 165.3mg)

200 mg 45mg Ubidecarenone (Co-enzyme Q10) (from patented Ultrasome CoQ10) 2 mg

Phytomenadione (vitamin K) 60 µg 60µg* Cynara Scolymus Leaf Dry (Globe artichoke) 50 mg Zinc Amino Acid Chelate (equiv. Zinc 20mg) 75 mg 8mg Cimicifuga Racemosa Root & Rhizome Dry (Black cohosh) 200 mg Calcium Orotate (equiv. Calcium 10mg) 100 mg 1300mg Curcuma Longa Rhizome Dry (Turmeric) 100 mg Magnesium Aspartate Dihydrate (equiv. Magnesium 6.74mg) 100 mg 320µg Withania Somnifera Root Dry (Ashwagandha) 500 mg Selenomethionine (equiv. Selenium 26mcg) 65 µg 60µg* Crataegus Monogyna Fruit Dry (Hawthorn) 100 mg Molybdenum Trioxide (equiv. Molybdenum 45 µg) 67.5 µg 45µg* Silica Colloidal Anhydrous (equiv. silicon 9.35mg) 20 mg Chromium Picolinate (equiv. Chromium 50 µg) 402 µg 25µg* Bacopa Monnieri Whole Plant Dry (Bacopa) (equiv. bacosides calculated

as bacoside A 1.125mg) 50 mg

Manganese Amino Acid Chelate (equiv. Manganese 4mg) 40 mg 5mg* Lecithin Powder – Soy Phosphatidylserine Enriched Soy (equiv. phosphatidylserine 2mg)

10 mg

Ferrous Fumerate (equiv. Iron 5mg) 16.01 mg 8mg Spearmint Oil 2 mg Copper Gluconate (equiv. Copper 1.7mg) 8.57 mg 1.2mg* Vaccinium Myrtillus Fruit Dry (Bilberry)

(equiv. anthocyanosides 324mcg) 100 mg

Potassium Iodide (equiv. Iodine 149.83mcg) (equiv. Potassium 46.18mcg)

196 µg 150µg Tagetes Erecta Flower Dry (Marigold) (Lutein esters calculated as lutein (of Tagetes erecta) 1mg)

100 mg

RDI = Recommended Daily Intake for Australian women aged over 51. Where two values are shown, the higher refers to RDI for women aged <70. *=Adequate intake (AI)

where RDI was not available. RDI and AI data was obtained from the National Health and Medical Research Council guidelines (2006).

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5.6 Measures

A number of mood measures were used in the current study in order to gain an overall

picture of mood in the sample. Both standardised clinical instruments, as well as tools

often used in the general population were utilised. Previous work from our research

group has indicated that commonly used mood scales often measure different aspects of

mood (Harris, Kirk et al., 2011). The scales used in the current study are detailed in the

sections below.

5.6.1 The Depression, Anxiety and Stress Scale The Depression, Anxiety and Stress scale (DASS; Lovibond and Lovibond, 1995), is a

21-item questionnaire that is split into three factors: depression, anxiety and stress. The

DASS is relevant for both clinical and non-clinical populations, and has adequate

reliability and validity. The DASS is made up of affect-related questions pertaining to

both physical (eg ‘dry mouth’) and mood symptoms (eg ‘down-hearted’). Each item is

scored on a 4-point scale from 0 to 3, with higher scores indicating a higher degree of

dysfunction. It is important to note that lower scores reflect a lack of symptoms and not

a more positive mood. Furthermore, as the experience of such symptoms is common in

every-day life, the DASS is considered suitable for use in non-clinical settings.

5.6.2 The Beck Depression Inventory The Beck Depression Inventory (BDI-II; Beck, Ward et al., 1961) is a 21-item; self-

report inventory designed to measure the severity of depressive symptoms. The BDI-II

is one of the most widely used depression inventories in both clinical and research

settings. The BDI-II asks participants to rate how they have felt over the past 2 weeks

on a scale of 0 (no symptoms) to 3 (severe symptoms). Higher scores on the BDI-II

indicate more severe depressive symptoms. The BDI-II has adequate test-retest

reliability and high internal consistency. Furthermore, the BDI has been shown to be

effective in measuring depressive symptoms in older populations (Gallagher, Nies et al.,

1982).

5.6.3 The Beck Anxiety Inventory The Beck Anxiety Inventory (BAI; Beck, Epstein et al., 1988) is a 21-item self-report

measure of the severity of anxiety symptomology in adults. Items cover somatic,

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cognitive and behavioural manifestations of anxiety. Participants were asked to rate the

degree to which they have felt particular symptoms “in the past week, including today”

on a scale of 0 (“not at all”) to 3 (“severely, I could barely stand it”). Few studies have

used the BAI in older samples, but one noteworthy study found that the BAI was

effective in assessing symptoms of anxiety in older adults (Morin, 1999).

5.6.4 The Hospital Anxiety and Depression Scale The Hospital Anxiety and Depression scale (HADS; Zigmond and Snaith, 1983) is a

brief (14 item) measure of the severity of anxiety and depression, with seven items

representing each subscale. Participants were asked to indicate which reply reflects best

their mood over the past week. Higher scores on each trait subscale indicate more

severe anxiety or depression. The HADS is one of the most widely used measures for

assessing anxiety and depression in research settings. Furthermore, the scale has been

shown to be affective in measuring symptoms of anxiety and depression in both

psychiatric and general community samples (Bjelland, Dahl et al., 2002).

5.6.5 The Perceived Stress Scale The Perceived Stress scale (PSS; Cohen, Kamarck et al., 1983) measures the degree to

which respondents view situations in their life as stressful. The PSS is made up of 10

items, scored on a 5-point scale, ranging from ‘never’ to ‘very often’. Higher scores on

the PSS are associated with higher levels of perceived stress, and lower scores reflecting

effective coping.

5.6.6 The General Health Questionnaire The 28-item version of the General Health Questionnaire (GHQ-28; Goldberg, 1978)

was used to provide an overall measure of psychological distress. The scale consists of

four subscales: somatic symptoms; anxiety and insomnia; social dysfunction; severe

depression. The GHQ-28 is widely used in research settings and is both reliable and

valid in both clinical settings and in the general population.

5.6.7 The Chalder Fatigue Scale The Chalder fatigue scale (Chalder, Berelowitz et al., 1993) is a widely used scale

designed to measure the severity of fatigue. The 14-item scale measures both physical

and mental fatigue on a 4 point scale ranging from ‘better than usual’ to ‘much worse

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than usual’. The Fatigue Scale has an internal consistency reliability coefficient

(Cronbach's alpha) of .845 for the physical symptoms scale and .821 for the mental

symptoms scale (Chalder, Berelowitz et al., 1993). The outcome for this measure will

be total fatigue rating.

5.6.8 Pittsburgh Sleep Quality Index The Pittsburgh Sleep Quality Index (PSQI; Buysse, Reynolds et al., 1989) was

originally designed to measure sleep quality and disturbance in clinical populations, and

has been subsequently utilized in a number of research settings. The PSQI is a self-

rated scale measured over a one-month interval. The scale is comprised of 19

individual items that generate 7 “component” scores: subjective sleep quality, sleep

latency, sleep duration, habitual sleep efficiency, sleep disturbance, use of sleep

medications, and daytime dysfunction. The scale also has five items to be answered by

a bed partner, if applicable, but these answers are not included in the scoring of the

scale. For the purpose of the current study these five questions will be removed from

the scale. The PSQI has been shown to be effective in distinguishing good sleepers

from poor sleepers.

5.6.9 The State-Trait Anxiety Inventory The State-Trait Anxiety Inventory (STAI; Spielberger, 1983) is a widely used

instrument designed to measure both fluctuating levels of anxiety (State) and more

general, stable levels of anxiety (Trait). The ‘State’ subscale contains 20 items, and

requires participants to rate how much they feel like each item at the time of response.

The scale is scored on a 4-point scale ranging from ‘not at all’ to ‘very much so’. The

‘trait’ subscale also contains 20 items, and participants are asked to rate how they

generally feel with regards to each item. The scale is scored on a 4-point scale ranging

from ‘almost never’ to ‘almost always’. Scores on both subscales range from 20 to 80,

with higher scores indicating higher levels of anxiety. Participants will be required to

complete the state version of the STAI twice, once before the commencement of the

stressor battery, and once at completion of the stressor battery. The trait version of the

STAI will be completed only once per session.

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5.6.10 The Bond-Lader Visual analogue scales The Bond-Lader Visual Analogue Scales (Bond and Lader, 1974) requires participants

to mark the appropriate position on a 100mm horizontal line separating two adjective

pairs; such as Happy-Sad or Sociable-Withdrawn, related to how they are feeling at the

present moment. The visual analogue scales are a measure of subjective mood

experience and is included to assess normal (non-disordered) mood. Stroke distance

from the left (mm) is manually calculated for the 16 items and total score is derived

from overall distance (mm), allowing a potential range of 0-1600. Higher scores are

indicative of more desirable mood states. This is completed twice in each session, once

before the stressor battery, and once after the stressor battery is complete.

5.6.11 Stress and fatigue visual analogue scales The Stress/Fatigue Visual Analogue Scale consists of a single 100 mm line with end-

points labelled ‘Not at all’ and ‘Very much so’. Participants are instructed to mark the

line, depending on how “stressed” or “fatigued” they feel at that point in time. This is

completed twice in each session, once prior to the stressor battery, and once after the

stressor battery is complete.

5.6.12 The NASA Task Load Index The NASA Task Load Index (NASA-TLX; Hart and Staveland, 1988) is a multi-

dimensional rating scale designed to measure an estimate of workload from participants

during or immediately after completion of a task. The NASA-TLX provides an overall

workload score based on the averages of six subscales: Mental demands, physical

demands, temporal demands, performance, effort, and frustration. Higher scores

represent a higher experience of workload. In the current study, participants will

complete the NASA-TLX after completing the Purple multi-tasking Framework.

5.6.13 Purple Multitasking Research Framework

The Purple Multi-Tasking Framework (MTF; Purple Research Solutions Ltd, UK) is

designed to induce stress in participants. The program requires participants to attend to

four tasks, presented on a split screen, simultaneously, thereby increasing stress

response (Figure 5-2). Previous research has shown that the Purple Framework

increases self-ratings of negative mood, arousal and stress-related psychological

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response (Kennedy, Little et al., 2004; Wetherell and Sidgreaves, 2005). ‘Medium’

intensity setting was used, in order to induce higher levels of stress. This task was used

in order to determine if the MVM was effective in protecting against the stress response

induced by the task.

The tasks include:

5.6.13.1 Mental arithmetic

This task requires participants to perform a series of arithmetic (additions) problems.

Using a number pad on the right, participants use the mouse to click on the number in

which they thought should go in the right column, and work through the sum,

completing all columns, and pressing done. Participants are awarded 10 points for a

correct answer and 10 points subtracted for an incorrect answer.

5.6.13.2 Stroop

The Stroop task is a classic psychological test of selective attention and response

inhibition. In this task, a series of words are presented (Red, Blue, Yellow and Green)

in differing colours (Red, Blue, Yellow and Green). Participants are asked to click one

of four coloured blocks on the right hand side of the task in response to the colour of the

font, regardless of the meaning of the word. For example, if the colour name ‘blue’

appeared in red font, the correct response was to click on the ‘Red’ colour block on the

right. 10 points are awarded for every colour word that was correctly identified, and 10

points are subtracted for each incorrect answer, or for not making a response in the

allotted time period (a ‘timeout’).

5.6.13.3 Memory Search

An array of letters is presented the participants to remember. The letters disappear after

4 seconds but can be viewed again by clicking on “retrieve list” button. Approximately

every 10 seconds, a single target letter appears. Participants are instructed to indicate

whether the target letter had appeared in the original list of four letters by clicking on

the “yes” or “no” buttons. Ten points are awarded for a correct answer, 10 points

deducted for an incorrect answer or no response, and 5 points are deducted every time

the list is retrieved.

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5.6.13.4 Visual Tracking

This task assesses psychomotor ability. A small dot drifts outwards from the centre of a

target comprising five concentric circles. The participants are instructed to allow the dot

to travel as far out of the centre as possible, without letting it hit the edge of the target,

before clicking on the “reset” button. Two points are added to the running total for

every circle that the dot passed through (with a maximum of 10 points), with a penalty

of 10 points for every half second that passes between the dot hitting the outer edge and

the participant clicking on the “reset” button.

Figure 5-2: Screenshot of the Purple Multi-tasking Framework

5.6.14 Cardiovascular and Haematological measures

5.6.14.1 Blood pressure, Heart rate and Body Mass Index

Blood pressure, heart rate and body mass index (BMI) were taken for all participants.

5.6.14.2 Blood tests

Blood samples were collected from participants at the beginning of both visits in order

to assess changes in cardiovascular health due to MVM supplementation. Samples were

analysed by a pathology laboratory in Melbourne, according to the standard operating

procedures for the lab. The tests conducted are outlined below.

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5.6.14.2.1 B vitamins

Vitamin B status was assessed by determining levels of Vitamin B12, B6, folate and

homocysteine in the blood. B12, B6 and folate are required by the body in order to

maintain healthy levels of homocysteine. As reviewed in Chapter 3, the methylation

cycle requires B12, folate and B6 for the remethylation of homocysteine to methionine or

cysteine (Huskisson, Maggini et al., 2007a). Deficiencies of any of these vitamins may

result in higher levels of circulating homocysteine, which has been implicated in

cognitive decline, cardiovascular disease and depression (Almeida, McCaul et al.,

2008). Similarly, lower levels of folate, B12 and B6 have also been associated with

depressive symptoms (Bottiglieri, Hyland et al., 1992; Penninx, Kritchevsky et al.,

2003).

Total homocysteine was measured in serum. Levels below 10µmol/L (micromoles per

litre) were considered desirable.

Vitamin B12 was measured in serum. B12 levels above 180 pmol/L (picomoles per litre)

were considered normal and deficiency defined as levels below 150 pmol/L. Recent

research has suggested that in an older population, a healthy B12 level for those aged 65

to 70 is 279 pmol/L and 268 pmol/L for those aged 75 to 80 years (Wahlin, Bäckman et

al., 2002).

Folate was measured in red blood cells (RBC). It has been suggested that RBC folate is

more reflective of body stores of folate, and more representative of CNS folate, as it

fluctuates much less than serum folate (Paul, McDonnell et al., 2004). Concentrations

above 400 nmol/L (nanomoles per litre) were considered normal, whereas levels below

300 nmol/L indicated deficiency.

Vitamin B6 was measured in whole blood, as Pyroxidal-5’-phosphate, the active

coenzyme form of vitamin B6. The reference range for B6 levels was between 35-110

nmol/L.

5.6.14.2.2 Vitamin E and Zinc.

Vitamin E is one of the most important antioxidants within the brain. It helps to reduce

free radical damage and oxidative stress, as well as protecting the brain from ageing,

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and reducing the risk of dementia (Bourre, 2006). Furthermore, recent research has

associated lower vitamin E levels with major depression (Maes, De Vos et al., 2000).

Vitamin E (total tocopherol) was determined from serum. The normal range for vitamin

E levels was between 12-46 µmol/L.

Zinc is an essential trace element in the human body (Nowak and Szewczyk, 2002).

Zinc is an important cofactor for several enzymes, essential for DNA synthesis and

membrane stability (Maes, D'Haese et al., 1994). Furthermore, zinc deficiency has been

linked to clinical depression. Patients with major depression have been shown to have

lower levels of zinc than control patients (Levenson, 2006). Zinc was measured in

serum. Zinc levels between 9-18 µmol/L were considered normal.

5.6.14.2.3 High-sensitivity C-Reactive Protein and Fibrinogen

C-Reactive protein (CRP) levels in the blood rise in response to inflammation.

Research has indicated that elevated levels of high sensitive C-Reactive protein

(hsCRP) are associated with an increased risk of cardiovascular disease (Ridker,

Hennekens et al., 2000). Recently, higher hsCRP levels have been associated with

depression, both in clinical and non-clinical samples (Howren, Lamkin et al., 2009) .

Furthermore, a recent study has indicated that MVM supplementation can reduce C-

Reactive protein levels in people without inflammatory conditions (Church, Earnest et

al., 2003). hsCRP was measured in serum. hsCRP levels below 1.0 mg/L (milligrams

per litre) were associated with a low cardiovascular risk, while high cardiovascular risk

was associated with levels above 3.0 mg/L.

Fibrinogen, an acute-phase protein and homeostatic factor, is involved in blood

coagulation and endothelial function. Levels of fibrinogen increase in response to

inflammation, and it when elevated in associated with increased risk of cardiovascular

disease (Stec, Silbershatz et al., 2000). Fibrinogen is also a strong marker of

atherosclerosis (Zoccali, Benedetto et al., 2003), and has recently been linked to

increased arterial stiffness and systolic dysfunction in individual without coronary heart

disease (Palmieri, Celentano et al., 2001). Furthermore, increased depressive symptoms

have been associated with elevated fibrinogen (Panagiotakos, Pitsavos et al., 2004), and

anxiety levels may also been influences by fibrinogen levels (Pitsavos, Panagiotakos et

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al., 2006). In the current study, fibrinogen was measures in citrated plasma. Normal

fibrinogen levels were between 2.0-4.0 g/L (grams per litre).

5.6.14.2.4 Cholesterol and Lipid Profile Total blood lipid analysis was conducted at both sessions. Higher levels of blood

cholesterol and other lipids have been associated with cardiovascular disease. The

relationship between mood and lipid profile is more complex, with some evidence

suggesting that lower levels of high-density lipoprotein (HDL; the “good” cholesterol)

is associated with major depression (Maes, Smith et al., 1997).

Total cholesterol, HDL, low-density lipoprotein (LDL), and triglycerides were measure

in the serum. LDL cholesterol concentrations below 2.5 mmol/L (millimoles per litre)

were considered normal. Additionally, HDL concentrations above 1.0 mmol/L and

triglyceride levels below 1.5 mmol/L were deemed normal.

5.6.14.2.5 Safety measures

Electrolytes, Renal Function and Liver Function tests were conducted in order to ensure

participants ability to tolerate the supplements and in order to gain a measure of general

health. The kidney and liver function tests were also used as safety parameters. These

tests were used to monitor the effect of the supplement on these blood safety

parameters. Additionally, analysis of the safety measures will determine if the

supplement is safe for daily use in older participants.

5.6.14.3 Indices of Arterial stiffness

The effect of MVM supplementation on arterial stiffness was tested using the

SphygmoCor aortic blood pressure waveform analysis system (AtCor, Sydney

Australia). This device adheres to the necessary Australian safety standards and is

commonly used to assess and manage cardiovascular health. The SphygmoCor system

derives the ascending aortic pressure wave from a snapshot of the radial arterial

pressure wave. This waveform was measured from each participant’s left wrist. The

resulting measurements included aortic augmentation index, augmentation pressure and

pulse rate. Aortic augmentation index is an indirect measurement of systemic arterial

stiffness, which has been associated with cognitive decline (Hanon, Haulon et al.,

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2005), cardiovascular disease (Mattace-Raso, van der Cammen et al., 2006), and more

recently with depression in the elderly (Tiemeier, 2003; Tiemeier, van Dijck et al.,

2004). Furthermore, individuals with anxiety have also been found to have increased

arterial stiffness when compared to controls (Yeragani, Tancer et al., 2006).

5.6.14.4 Framingham Risk Score The Framingham Risk Score (D’Agostino, Vasan et al., 2008) is a gender-specific

algorithm that can be used to assess the 10-year CVD risk of an individual. The score is

calculated with a number of variables; gender, age, total and HDL cholesterol, systolic

blood pressure, hypertension treatment status, as well as smoking and diabetes status.

This score was calculated for all participants at both visits.

5.7 Pre- and Post-treatment testing procedure

Participants attended two sessions at the Centre for Human Psychopharmacology at

Swinburne University. They were required to fast from midnight the previous night,

and to refrain from drinking tea or coffee the morning of both sessions. Fasting blood

samples were obtained from all participants at the beginning of each testing session.

After blood was taken, a light breakfast was provided prior to the commencement of the

session.

At the baseline session, participants provided demographic information and completed

the screening questionnaires. Following this, the pen and paper questionnaires were

completed and cardiovascular measures were taken. Prior to completing the Purple

Multi-tasking framework, a short practice of the task was provided to ensure that

participants were able to complete the task competently. The full task ran for 20

minutes. The state version of the STAI and the Bond-Lader and stress and fatigue

visual analogue scales were completed before and after the MTF. The first testing

session followed the procedure below:

1. Screening period:

• Obtain written informed consent

• Review of inclusion and exclusion criteria

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• Obtain demographic information

• Obtain basic medical history and review of concomitant medications

• Obtain MMSE and NART-R scores

2. Baseline session:

• Obtain fasting blood sample

• Standardised breakfast provided

• Completion of mood and wellbeing questionnaires

• Completion of pre-MTF scales

• Completion of MTF

• Completion of post-MTF scales

• Obtain cardiovascular function measures.

• Instructions for the 16-week supplementation period.

The post-supplementation session occurred approximately 16 weeks after the baseline

session. Compliance was assessed by the return of all unused supplements. The post-

treatment session followed a similar procedure as the baseline session, which is outlined

below:

3. 16-week session:

• Review of inclusion and exclusion criteria and adverse events

• Review of basic medical history and concomitant medications

• Obtain fasting blood sample

• Standardised breakfast provided


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• Completion of pre-MTF scales

• Completion of MTF

• Completion of post-MTF scales


5.8 Statistical analysis

IBM SPSS, version 22.0 (IBM Corp., 2013) was used to analyse all mood, stress and

health data. Data was screened for outliers and out of range values. Data that was more

than 3 standard deviations from the mean were classified as outliers and removed from

subsequent analyses. The assumption of normality was assessed with the Shapiro-

Wilks statistic and via visual examination of histograms. Positively skewed data was

transformed with logX transformations. In order to assess the main outcome a

2(treatment: MVM, placebo) x 2(time: baseline, post-treatment) mixed design analysis

of variance (ANOVA) was conducted on the data. Subsequent analysis of individual

scales was also assessed by mixed design ANOVA. Where there were violations of

ANOVA assumptions change from baseline scores were calculated, and univariate

AVOVA was used to assess differences between the groups.

Due to sample size constraints, males and females were analysed together for all

analyses. While the supplements for male and female participants were slightly

different formulations, they were designed to meet the different daily requirements for

males and females. One-way ANOVA was conducted on the change in B vitamin status

(B12, folate and B6) in order to assess gender differences in absorption of the MVM. No

significant gender differences were found, suggesting that male and female participants

did not respond significantly differently to the supplements. Nevertheless, gender was

added a covariate in all subsequent analyses in order to control for any other active

constituents of the MVM that were not actively assessed.

The significance level was set at p<0.05 for analysis of the primary outcomes. A more

conservative criterion was set for the exploratory aims of p<.01.

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5.9 Results

5.9.1 Participant Demographics

Of the 84 participants originally enrolled in the study, 76 participants completed the

trial. One participant was excluded due to protocol violation, two were lost to follow-

up, two had surgery during trial, one started high dose pain killers, one discontinued

treatment due to stomach issues unrelated to the treatment, and one participant in the

placebo group reported side effects possibly related to the treatment, so was advised to

discontinue treatment. Participant demographics are shown in Table 5-4 below.

Independent samples t-tests indicated that there were no significant differences between

the groups on any of the demographic measures. It is important to note that the group of

participants in the current study were all highly educated with a high NART-R IQ

levels.

Table 5-4 – Baseline multivitamin and placebo group demographics.

Male Female Total Demographic Group N M SD N M SD N M SD Age Multivitamin 19 64.42 8.90 23 61.65 7.85 42 62.90 8.35 Placebo 19 61.84 7.96 23 58.39 6.67 42 59.95 7.40 Education (years) Multivitamin 19 14.37 3.45 20 14.75 4.54 39 14.56 4.00 Placebo 18 15.61 3.76 23 15.52 4.95 41 15.56 4.42 MMSE Multivitamin 19 28.84 1.17 22 29.14 0.94 41 29.00 1.05 Placebo 18 29.22 1.31 23 29.35 0.98 41 29.29 1.12 NART- R IQ Multivitamin 16 117.19 8.89 21 116.24 6.56 37 116.65 7.56 Placebo 17 117.12 6.75 19 115.95 12.10 36 116.50 9.83 BMI Multivitamin 18 25.87 2.46 23 26.31 3.69 41 26.11 3.18 Placebo 18 28.34 4.69 23 25.87 4.81 41 26.95 4.86 MMSE= Mini-Mental State Examination; NART- R IQ = National Adult Reading Test Revised Predicted IQ; BMI= Body Mass Index.

5.9.2 Concurrent medications and supplements

In the current study, 45 participants were taking concurrent medication. The most

common forms of medications were for the treatment of hypertension (N=16) and

cholesterol (N=10).

5.9.3 Compliance

All participants were asked to return any unused treatment in order to assess

compliance. Compliance was calculated by comparing the number of returned

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treatments to the number expected. A cut-off of 80% compliance was used for the

study. Compliance in the current study ranged from 86% to 113%. Mean compliance

was 98%. Only one participant was excluded from analysis due to poor compliance

(65%).

5.9.4 Treatment Evaluation Of the 76 participants, 72 were asked to guess what supplement they believed they were

taking at the end of the 16-week period. 12 correctly guessed that they were taking the

multi vitamin, 10 correctly identified the placebo, 17 were incorrect and 41 were unsure

of their treatment allocation. A Pearson’s chi square test indicated that the difference

between the correct, incorrect and unsure guesses did not significantly differ among the

MVM and placebo groups (p=.156)

5.9.5 Treatment side effects

Overall, both the treatment and placebo were well tolerated. Only one participant in the

placebo group experienced possible side effects of the treatment, reporting extreme

thirst, dizziness and light-headedness. This participant was advised to discontinue the

treatment, and when followed-up a week later all symptoms had disappeared.

5.10 Baseline Biochemical results

A series of Pearson’s correlations were conducted on the baseline levels of B12, folate,

B6 homocysteine, vitamin E and zinc and mood measures in order to examine any

relationships at the baseline visit. In order to correct for positive skew, log

transformations were applied to a number of the mood scales, including, DASS total

score, and all subscales; the BDI and BAI; the Anxiety/Insomnia and Depression

subscales of the GHQ; and both the depression and anxiety subscales of the HADS. It

is important to note, that this analysis generated a large number of correlations (see

Table 5-5), therefore, the criterion of significance was set at p<.01.

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Table 5-5 Correlation Coefficients (r) for Baseline Mood and Biochemical measures

Correlation Coefficients Scale B12 Folate B6 HCY Zinc Vitamin E DASS Total .025 -.136 .023 -.065 .182 .162 DASS Depression -.069 -.140 -.024 .029 -.038 .043 DASS Anxiety .125 .134 .040 -.073 -.051 .290* DASS Stress -.029 -.069 -.052 -.162 .156 .161 BDI .027 .129 .024 -.142 -.044 .239 BAI .117 .201 -.034 -.233 .036 .254 GHQ Total .087 .083 .026 -.195 .012 .218 GHQ Anxiety Insomnia

.079 .063 -.039 -.285 .016 .067

GHQ Depression -.073 .117 .058 .207 -.127 .042 GHQ Somatic .151 .058 -.110 -.247 .121 .302* GHQ Social Dysfunction

.050 .106 .124 -.032 .011 .255

HADS Anxiety .024 .138 .093 -.321* -.025 .148 HADS Depression .026 .000 -.055 .017 .047 -.007 CFS Total .100 .019 .074 -.176 -.126 .153 CFS Mental .156 .070 .097 -.195 -.058 .132 CFS Physical .042 -.024 .043 -.131 -.157 .143 PSS Total .117 .048 .084 -.106 .062 .082 STAI-Trait .065 .137 .095 -.172 -.014 -.016 PSQI Total .009 .066 -.053 -.066 -.097 .188 *= p<.01 DASS – Depression Anxiety Stress Scale; GHQ – General Health Questionnaire; BDI – Beck Depression Inventory; BAI – Beck Anxiety Inventory; HADS – Hospital Anxiety and Depression Scale; CFS – Chalder Fatigue Scale; PSS – Perceived Stress Scale; STAI – State-Trait Anxiety Inventory; PSQI – Pittsburgh Sleep Quality Index

The baseline scores on the anxiety subscale of the DASS were positively correlated with

vitamin E levels (r=.290, p=.008). Further, scores on the GHQ somatic subscale were

positively correlated with vitamin E (r=.302, p=.006). Scores on the anxiety subscale of

the HADS were negatively correlated with homocysteine (r=-.289, p=.009). No other

significant correlations were observed. Visual examination of scatterplots revealed that

these relationships were all influenced by scores of zero on each of the scales.

Furthermore, for the GHQ somatic subscale and vitamin E levels, there seemed to be 2

other influential points on the scatterplot. Those with ‘0’ scores were excluded from the

analysis in order to examine the relationships between the bloods and those with some

level of mood disturbance. When zero scores and potential influential points were

removed from the analysis, these relationships were no longer significant.

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5.11 The Treatment Effects of Multivitamin Supplementation

A series of independent samples t-tests were conducted to investigate any differences

between the treatment groups at baseline. At baseline there was a significant difference

between the groups on the BDI (MVM M=2.81, placebo M= 4.79, p=.026), the DASS

total scale (MVM M=7.35, placebo M=9.54, p=.039) and the DASS depression subscale

(MVM M=1.24, placebo M=2.51, p=.045). There were no other statistically significant

differences between the treatment groups on any of the mood measures at baseline.

There was a trend towards a difference at baseline on the physical subscale of the

Chalder Fatigue Scale (MVM M=7.19, placebo M=8.32, p=.057). A 2(treatment:

MVM, placebo) x 2(time: baseline, post-treatment) mixed design ANOVA, with gender

as a covariate, was conducted on all scales to assess the effect of MVM

supplementation. In order to correct for positive skew, log transformations were applied

to a number of the scales: DASS total score, and all subscales; the BDI and BAI; the

Anxiety/Insomnia and Depression subscales of the GHQ; and both the depression and

anxiety subscales of the HADS. For the main outcome (total DASS scores), a

significance level of p<.05 was set. For the analysis of the other mood scales, the

criterion was set at p<.01.

5.11.1.1 Effects of the treatment on mood measures

A significant treatment effect was found for on the DASS total scale (F(1,66)=5.15,

p=.026, partial η2=.07), with scores in the placebo group reducing. Due to the

differences in the groups at the baseline session, Univariate Analysis of Covariance

(ANCOVA), with the follow-up score as the dependant variable and the baseline score

as the covariate, was applied to the data. When controlling for the baseline differences

between the groups, the effect of treatment at follow-up was no longer significant

(F(1,63=1.54, p=.220, partial η2=.02). No effects of treatment were observed on the

depression or anxiety subscales of the DASS. Further analysis of the DASS subscales

showed a trend towards a significant treatment effect on the stress subscale

(F(1,67)=3.68, p=.059, partial η2=.05). This effect was due to a reduction in stress

scores in the placebo group.

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A significant treatment effect was found on the BDI (F(1, 66)=8.42, p=.005, partial

η2=.11). Scores in the placebo group reduced, while the scores remained stable in the

MVM group. This result could be partially driven by the significant difference between

the baseline scores. To assess this, ANCOVA, with the follow-up score as the

dependant variable and the baseline score as the covariate, was applied to the data.

When covarying for baseline scores, the difference between the groups was no longer

significant (F(1,65)=2.28, p=.135, partial η2=.03).

A significant treatment effect was found on both the HADS Anxiety (F(1,70)=11.11,

p=.001, partial η2=.14) and Depression (F(1,70)=8.51, p=.005, partial η2=.11)

subscales. The placebo group demonstrated improvements on both scales, as shown in

Figure 5-3 and Figure 5-4 below.

There were no other significant treatment effects observed on any of the mood scales.

Table 5-6 shows the means, standard deviations and time x treatment interactions for

both of the treatment groups.

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Figure 5-3. Estimated marginal means for HADS anxiety scale

Figure 5-4. Estimated marginal means for HADS depression scale

2

2.5

3

3.5

4

4.5

Baseline Post treatment

Multivitamin

Placebo

11.21.41.61.8

22.22.4

Baseline Post treatment

Multivitamin

Placebo

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Table 5-6 – Means, standard deviations and interaction values for the mood, stress and fatigue scales

Scale Group Baseline Post-treatment Interaction values N M SD M SD F p Chalder Fatigue Scale Total Multivitamin 38 13.62 4.74 13.70 3.23 .378 .541 Placebo 37 14.82 4.01 14.29 3.29 Physical Multivitamin 37 7.19 2.95 7.89 2.49 2.996 .088 Placebo 38 8.32 2.55 7.79 2.09 Mental Multivitamin 37 6.43 2.18 5.81 1.13 1.655 .202 Placebo 38 6.50 1.87 6.50 1.62 Depression Anxiety and Stress Scale Total Multivitamin 34 7.35 7.73 9.82 10.59 5.152 .026 Placebo 35 9.54 7.90 7.26 7.69 Depression Multivitamin 34 1.24 2.03 1.59 2.24 2.358 .129 Placebo 35 2.51 3.44 1.49 2.02 Anxiety Multivitamin 37 2.59 4.11 2.76 3.21 2.683 .106 Placebo 37 2.76 3.95 1.95 2.69 Stress Multivitamin 34 4.65 5.56 4.76 5.16 3.681 .059 Placebo 36 5.50 4.88 3.67 4.34 The General Health Questionnaire Total Multivitamin 36 14.22 7.12 13.42 6.33 1.657 .202 Placebo 38 14.84 6.49 12.00 5.66 Somatic Multivitamin 37 3.73 2.78 3.43 2.82 1.567 .215 Placebo 37 4.16 3.32 2.92 2.17 Anxiety/Insomnia Multivitamin 37 2.97 3.10 3.62 3.47 2.277 .136 Placebo 37 3.32 2.97 2.76 2.88 Social Dysfunction Multivitamin 35 6.86 1.38 5.87 2.08 1.557 .216 Placebo 36 7.28 1.72 5.64 2.57 Depression Multivitamin 35 0.54 1.40 0.54 1.17 .002 .964 Placebo 38 0.24 0.63 0.26 0.72 Hospital Anxiety Depression Scale Depression Multivitamin 36 1.94 2.14 2.22 2.10 8.505 .005* Placebo 37 2.32 2.19 1.46 2.05 Anxiety Multivitamin 37 3.57 3.43 4.08 3.25 11.106 .001* Placebo 36 3.75 3.42 2.56 2.53 Beck Depression Inventory Multivitamin 31 2.81 3.79 2.90 3.29 8.421 .005 Placebo 38 4.79 4.17 2.79 3.25 Beck Anxiety Inventory Multivitamin 37 3.51 4.44 2.65 3.48 .269 .606 Placebo 37 3.11 3.67 1.89 2.50 Perceived Stress Scale Multivitamin 37 18.08 8.82 17.11 7.78 .003 .955 Placebo 38 16.84 7.60 15.97 6.98 Pittsburgh Sleep Quality Index Multivitamin 37 5.32 4.01 5.16 3.23 0.51 .882 Placebo 38 5.08 4.06 4.79 3.48 State Trait Anxiety Inventory - Trait Multivitamin 35 34.43 9.71 33.80 9.47 2.156 .147 Placebo 37 33.86 8.43 31.24 7.99

N= represents participants included in the pre to post treatment analysis * = Significant time x treatment interaction (p<.01). Interaction values represent the time x treatment analysis.

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5.11.2 The Effect of Multivitamins on Stress Reaction.

An independent samples t-test was conducted on the scores from the Purple

Multitasking Framework (MTF) in order to assess any baseline differences between the

two treatment groups. At baseline, scores on the MTF did not significantly differ

between the groups. Additionally, independent samples t-tests were conducted on all

pre stressor scores at both sessions in order to assess any baseline differences between

the groups. No baseline differences were observed on any of the scales. To assess the

effects of the treatment on reactions to the stressor, change scores were calculated for

the stress scales, taking the pre scores from the post scores. Due to the exploratory

nature of these analyses, the significance levels was set at p<.01.

Independent t-tests conducted on the baseline change scores showed a trend towards a

group difference was observed on the contentedness scale of the Bond-Lader scale

(t(1,78)=5.76, p=.019), with the placebo groups demonstrating a significantly greater

decrease in contentedness than the MVM group.

A 2(treatment: MVM, placebo) x 2(time: baseline change, follow-up change) mixed

design ANOVA, with gender as a covariate, was used to assess the effect of the MVM

treatment on MTF scores. No significant treatment effects were observed.

A 2(treatment: MVM, placebo) x 2(time: baseline change, follow-up change) mixed

design ANOVA, with gender as a covariate, was conducted on all change scores to

assess the effect of treatment on reaction to the stressor. No treatment x time effects

were observed on any of the change scores.

Regardless of treatment group, paired samples t-tests revealed that the MTF was

effective in inducing a stress response. While scores of alertness did not change with the

stressor, ratings of calmness and contentedness reduced at the baseline session (Content:

t(79)=2.64, p=.010; Calm: t(79)=3.94, p<.001) and calmness was also reduced at the

follow up session (t(70)=6.82, p<.001) sessions. At the baseline session, the MTF

resulted in participants reporting greater stress (t(79)=-3.08, p=.003) and greater fatigue

(t(79)=-3.88, p<.001) after completing the MTF, there were no differences in these

ratings at the follow-up session. No differences were observed on the state version of

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the STAI or the NASA Task Load Index. Table 5-7 shows the means and standard

deviations of the pre and post stressor measures and the NASA-tlx.

Table 5-7. Means and Standard Deviations of the pre- and post-stressor measures

N= represents participants included in the pre to post treatment analysis Interaction values represent the time x treatment analysis.

5.11.3 Haematological Biomarkers

A series of independent samples t-tests were conducted to investigate any differences

between the treatment groups at baseline. A significant group difference was found for

levels of hsCRP at baseline (MVM M=0.82, placebo M=2.29, p=.001), in which the

placebo group had significantly higher levels of hsCRP. Additionally, the MVM group

had significantly higher levels of homocysteine at baseline, compared to the placebo

Measure Group N Baseline Follow-up Interaction values M SD M SD F p Visual Analogue Scales Alert (pre battery) Multivitamin 33 70.03 15.87 68.27 14.79 .029 .865 Placebo 37 71.05 17.24 70.90 14.14 Alert (post battery) Multivitamin 33 73.40 11.30 71.10 11.79 Placebo 37 68.35 15.95 68.00 14.89 Content (Pre battery) Multivitamin 33 76.35 11.42 73.95 14.74 .068 .795 Placebo 37 80.59 11.26 80.31 10.75 Content (post battery) Multivitamin 33 75.55 11.28 73.31 13.27 Placebo 37 74.02 15.03 74.54 14.31 Calm (pre battery) Multivitamin 33 69.23 16.49 70.45 14.44 .389 .535 Placebo 37 74.54 16.91 74.18 13.69 Calm (post battery) Multivitamin 33 59.15 21.83 57.55 18.62 Placebo 37 60.68 19.65 60.57 20.02 Stress (pre battery) Multivitamin 38 20.26 17.99 31.37 22.46 .232 .631 Placebo 41 27.37 23.87 35.20 25.36 Stress (post battery) Multivitamin 38 32.52 21.66 42.45 27.42 Placebo 40 34.14 25.59 35.03 26.94 Fatigue (pre battery) Multivitamin 38 26.53 24.18 33.29 24.85 3.58 .063 Placebo 41 29.00 25.01 42.78 26.55 Fatigue (post battery Multivitamin 38 34.33 24.14 38.97 19.68 Placebo 41 40.24 26.64 33.38 24.19 State-Trait Anxiety Inventory – State version STAI (pre battery) Multivitamin 35 29.11 8.67 30.40 9.22 .112 .739 Placebo 37 30.03 9.58 28.95 9.21 STAI (post battery) Multivitamin 35 30.42 7.82 30.54 9.00 Placebo 37 31.72 9.90 30.25 10.28 NASA-TLX Multivitamin 35 53.49 13.98 52.61 12.99 .001 .974 Placebo 37 49.74 15.94 48.97 13.30

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group (MVM M=13.51, placebo M=11.88, p=.027). The placebo group had slightly

higher levels of Fibrinogen at baseline, but this failed to reach significance (MVM

M=2.76, placebo M=2.97, p=0.075). There were no other group differences found at

baseline.

No group differences were found on any of the blood safety measures at baseline,

although there was a slight trend towards the MVM group having higher levels of

sodium at baseline (MVM M=141.30, placebo M=140.38, p=.068). The significance

level was set at p<.05 for the analysis of the B vitamins and homocysteine. For all other

analyses, the significance level was set at p<.01.

5.11.3.1 The effect of supplementation on haematological safety measures

Multiple biochemical analysis, liver and renal functions tests were conducted at both

visits to ensure the safety and tolerability of the MVM supplements. Table 5-8 below

shows the means and standard deviations of the haematological safety measures.

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Table 5-8 - Means and Standard Deviations of Haematological Safety Measures at Baseline and

Post-Treatment

Biochemical measure

Treatment Group

N Baseline Post-Treatment Interaction values M SD M SD F p

Sodium mmol/L Multivitamin 36 141.30 2.16 140.44 1.87 12.21 .001* Placebo 38 140.38 1.95 140.97 2.09

Potassium mmol/L Multivitamin 37 4.47 0.30 4.46 0.36 1.15 .287 Placebo 38 4.41 0.35 4.48 0.29

Chloride mmol/L Multivitamin 37 105.41 2.34 105.05 1.78 3.52 .065 Placebo 38 105.05 1.82 105.47 2.13

Bicarbonate mmol/L Multivitamin 37 30.65 2.24 30.22 2.29 .139 .710 Placebo 38 30.89 2.18 30.24 2.05

Urea mmol/L Multivitamin 37 5.74 1.54 5.98 1.24 .999 .321 Placebo 38 6.17 1.82 6.16 1.53

Creatinine µmol/L Multivitamin 36 82.72 12.92 84.08 14.29 .000 .990 Placebo 38 79.37 16.75 80.42 16.36

eGFR g/L Multivitamin 35 70.77 9.78 69.45 11.04 .077 .782 Placebo 31 74.90 12.35 73.48 12.02

T. Protein g/L Multivitamin 37 72.30 4.62 71.38 4.39 .179 .674 Placebo 38 72.29 3.60 71.71 3.15

Albumin g/L Multivitamin 37 41.62 2.67 41.86 2.21 .293 .590 Placebo 38 40.79 2.81 40.74 2.33

ALP U/L Multivitamin 36 74.74 16.35 69.80 15.99 3.40 .070 Placebo 38 72.76 17.62 71.68 17.10

Bilirubin µmol/L Multivitamin 36 11.31 4.39 11.44 3.88 .031 .861 Placebo 37 10.92 3.60 11.00 4.52

GGT U/L Multivitamin 36 25.92 17.18 24.22 12.75 .863 .356 Placebo 38 33.34 24.65 29.63 19.43

AST U/L Multivitamin 36 21.72 3.53 23.06 4.82 6.02 .017 Placebo 37 22.41 4.74 21.81 3.53

ALT U/L Multivitamin 36 23.22 7.34 24.78 7.19 2.16 .146 Placebo 37 24.08 8.47 23.59 8.68

N= represents participants included in the pre to post treatment analysis * = Significant time x treatment interaction (p<.01). Interaction values represent the time x treatment analysis.

Liver and Renal function

There were no effects of treatment on any of the other liver or renal function measures.

A trend towards an increase in AST in the multivitamin group was observed

(F(1,69)=6.02 p=.017, partial η2=.08), but this failed to reach significance. The slight

increase in AST may represent a harder working liver.

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Multiple Biochemical analysis

A significant treatment effect was found for sodium levels (F(1,71)=12.21 p=.001,

partial η2=.15), with the MVM group demonstrating a small decrease in sodium levels

and the placebo group a slight increase.

No treatment effects were found for any of the other electrolytes studied.

5.11.3.2 The effect of supplementation on haematological vitamin measures In order to observe the change in vitamin status after MVM supplementation, blood

vitamin measures for a number of vitamins and mineral were assessed at both study

visits.

The B vitamins and homocysteine Table 5-8 presents the means and standard deviations for the B vitamins and

homocysteine.

Table 5-9. Means and Standard Deviations for the B vitamins and homocysteine at baseline and

post-treatment. Biochemical measure Treatment group N Baseline Post Treatment Interaction values

M SD M SD F P Vitamin B12 pmol/L Multivitamin 35 276.57 90.03 361.49 99.49 23.26 <.000* Placebo 37 316.62 98.67 324.16 100.94 Folate nmol/L Multivitamin 32 929.00 161.30 1316.94 300.03 18.52 <.000* Placebo 34 996.32 225.57 1099.53 244.33 Vitamin B6 nmol/L Multivitamin 34 95.54 36.08 533.94 240.29 96.58 <.000* Placebo 35 157.77 147.95 126.27 103.76 Homocysteine µmol/L Multivitamin 35 13.51 3.91 11.66 2.81 11.66 .001* Placebo 38 11.88 2.60 11.69 2.65

N= represents participants included in the pre to post treatment analysis *=significant time x treatment interaction (p<.05) Interaction values represent the time x treatment analysis.

Vitamin B12

There was a significant treatment effect for vitamin B12 (F(1,69)=23.26, p<.000, partial

η2=.25), with concentrations increasing in the MVM group. Figure 5-5 shows the mean

vitamin B12 concentrations at baseline and follow-up for the different treatment groups.

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Figure 5-5. Mean Vitamin B12 concentrations for the multivitamin and placebo groups. Error

bars show ± 1 standard error.

Red Blood Cell Folate

A significant treatment effect was observed on folate levels (F(1,63)=18.52, p<.000,

partial η2=.23), where significant increases were observed in the MVM group. Figure

5-6 shows the mean folate concentrations at baseline and follow-up for the different

treatment groups.

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Figure 5-6. Mean Folate concentrations for the multivitamin and placebo groups. Error bars

show ± 1 standard error.

Vitamin B6

The results for Vitamin B6 levels indicated a significant treatment effect

(F(1,62)=96.58, p<.000, partial η2=.61). As shown in Figure 5-7 the mean

concentrations of B6 significantly increased in the MVM group.

Figure 5-7. Mean B6 concentrations for the multivitamin and placebo groups. Error bars show ±

1 standard error.

155

Homocysteine

A significant effect of supplementation was found for homocysteine (F(1,70)=11.66,

p=.001, partial η2=.14), despite the MVM group starting with higher homocysteine

levels at baseline. Homocysteine levels in the MVM group significantly decreased after

16 weeks of supplementation. Due to the differences in the groups at the baseline

session, Univariate Analysis of Covariance (ANCOVA), with the follow-up level as the

dependant variable and the baseline levels as the covariate, was applied to the data.

Controlling for the baseline differences still resulted in a significant effect of MVM

treatment (F(1,69)=6.56, p=.013, partial η2=.09). Figure 5-8 shows the mean

concentrations of homocysteine for both treatment groups, across the two testing

sessions.

Figure 5-8. Mean homocysteine concentrations for the multivitamin and placebo groups. Error

bars show ± 1 standard error.

Zinc and Vitamin E

The means and standard deviations for the blood measurements of zinc and vitamin E

are presented in Table 5-9.

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Table 5-10. Zinc and Vitamin E: means and standard deviations at baseline and follow-up

Biochemical measure

Treatment group

N Baseline Post Treatment Interaction values

M SD M SD F p Zinc µmol/L Multivitamin 35 13.98 2.49 14.14 2.64 .324 .571

Placebo 38 13.64 1.97 13.47 1.65 Vitamin E µmol/L Multivitamin 37 35.42 10.21 36.31 8.52 .382 .539

Placebo 36 36.24 9.99 35.58 7.31 N= represents participants included in the pre to post treatment analysis Interaction values represent the time x treatment analysis.

No significant time x treatment effects were observed for vitamin E or zinc levels after

MVM supplementation.

HsCRP, fibrinogen and Cholesterol Profile

Table 5-10 presents the means and standard deviations of blood inflammatory markers

and lipid profile at baseline and follow-up sessions.

Table 5-11. Inflammation and Cholesterol Profile: Means and Standard Deviations

Biochemical measure

Treatment group

N Baseline Post Treatment Interaction values

M SD M SD F p hsCRP mg/L Multivitamin 35 0.82 0.96 1.49 2.00 5.61 .021

Placebo 35 2.37 2.44 2.08 2.44 Fibrinogen g/L Multivitamin 36 2.76 0.53 2.79 0.58 1.78 .186

Placebo 38 2.97 0.60 2.89 0.56 Total Cholesterol mmol/L

Multivitamin 36 5.48 0.92 5.28 0.85 .051 .821 Placebo 38 5.72 1.00 5.48 0.78

HDL Cholesterol mmol/L


LDL Cholesterol mmol/L

Multivitamin 36 3.19 0.80 2.96 0.69 0.15 .902 Placebo 38 3.55 0.84 3.34 0.71

Triglyceride mmol/L



No treatment effects were found for hsCRP, fibrinogen or any of the cholesterol

measurements.

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5.11.4 The change in blood biomarkers verses the change in mood. Individuals respond differently to multivitamin supplements, and the uptake and

absorption of ingredients may vary from person to person. In order to investigate the

potential confounding effects of individual differences in the uptake of MVM

constituents and the resulting mood effects an additional analysis was conducted on the

data. These differences can often be masked in standard ANOVA tests when the means

of the 2 groups are compared. We would predict that those individuals showing much

greater change from baseline in their uptake of vitamins (or change in health

parameters) would show a corresponding improvement in mood.

Therefore, in order to assess the potential contribution of the change in blood

biomarkers on the change in mood, change scores from baseline were calculated for the

B vitamin and homocysteine measures, the inflammatory markers (hsCRP and

fibrinogen), as well as the mood and stress questionnaires.

A series of Persons correlations were applied to the change from baseline scores in

order to determine the relationships between the changes in blood markers in relation to

the change in mood (Table 5-12). Due to the exploratory nature of this investigation,

the criterion was set at p<.01.

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Table 5-12. Correlation Coefficients (r) for the change from baseline scores

Correlation Coefficients Change Score B12 Folate B6 Hcy HsCRP Fibrinogen DASS total -.204 .109 .233 -.139 -.155 -.098 DASS Depression .064 .056 .052 -.145 -.145 .011 DASS Anxiety .78 .055 .260 -.222 -.164 .007 DASS Stress -.019 .165 .292 -.249 .001 -.023 CFS Total .085 -.230 .080 -.159 -.018 .069 CFS Physical .204 -.104 .167 -.150 .043 .122 CFS Mental -.111 -.321* -.078 -.114 -.100 -.036 GHQ total .055 .065 .135 -.156 .006 -.049 GHQ somatic .127 .078 .182 -.153 .045 .039 GHQ Anxiety Insomnia

-.165 .060 .095 .029 -.178 -.137

GHQ Social Dysfunction

.267 -.058 .189 -.148 .124 .043

GHQ Depression -.062 .241 .130 -.144 -.125 -.138 BDI .129 .216 .278 -.183 -.026 -.115 BAI -.011 .149 .047 -.205 .173 .000 PSS -.127 -.077 .084 .059 -.134 -.116 HADS Depression .226 .089 .216 -.187 -.085 .097 HADS anxiety .088 .058 .242 -.143 -.028 -.099 STAI-T .116 .228 .148 -.193 .060 .079 *=p<.01 DASS – Depression Anxiety Stress Scale; GHQ – General Health Questionnaire; BDI – Beck Depression Inventory; BAI – Beck Anxiety Inventory; HADS – Hospital Anxiety and Depression Scale; CFS – Chalder Fatigue Scale; PSS – Perceived Stress Scale; STAI – State-Trait Anxiety Inventory; PSQI – Pittsburgh Sleep Quality Index

The change in inflammatory markers, hsCRP and fibrinogen were not significantly

correlated with change scores for any of the mood measures.

The change in folate was significantly associated with the change in the mental fatigue

subscale of the Chalder Fatigue Scale (r=-.321, p=.009), whereby a positive change

(increase) in folate was associated with a negative change (improvement) on the mental

fatigue subscale (See Figure 5-9).

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Figure 5-9. Scatterplot of the relationship between the change in red blood cell folate and the change in mental fatigue.

5.11.5 Cardiovascular Results

A series of independent samples t-tests were conducted on the data to determine

differences between the treatment groups at baseline. No significant baseline

differences were observed on any of the cardiovascular measurements. Table 5-11

below shows the means and standard deviations for the cardiovascular parameters.

-8

-6

-4

-2

0

2

4

6

-500 0 500 1000

Chan

ge in

Men

tal f

atig

ue

Change in Folate

Change in Folate vs Change in Mental Fatigue

160

Table 5-13 - Means and standard deviations for cardiovascular measurements at

baseline and follow-up.

Cardiovascular measure

Treatment group

Baseline Post Treatment

Interaction Values

N M SD M SD F p

Peripheral measures Brachial Systolic pressure

Multivitamin 34 133.50 19.52 127.50 17.66 .030 .863

Placebo 33 135.33 16.88 129.94 15.88 Brachial Diastolic pressure

Multivitamin 34 80.41 10.76 79.03 11.52 .013 .908

Placebo 33 83.67 11.33 82.55 10.77 Brachial pulse pressure

Multivitamin 34 53.09 13.45 48.47 11.20 .016 .899

Placebo 33 51.67 11.31 47.39 11.03 Central measures Central systolic pressure

Multivitamin 30 121.70 20.11 115.07 17.05 .047 .830

Placebo 26 126.81 14.29 120.92 14.92 Central diastolic pressure

Multivitamin 30 81.47 11.00 85.92 11.49 .001 .979

Placebo 26 79.77 11.83 84.27 10.58 Central pulse pressure

Multivitamin 30 40.23 12.66 35.30 8.94 .089 .767

Placebo 26 40.88 8.28 36.65 9.44 Augmentation pressure

Multivitamin 30 10.27 6.55 9.00 5.38 .165 .687

Placebo 24 11.29 5.79 9.46 4.93 Augmentation Index Multivitamin 32 23.43 11.21 25.07 10.82 .734 .395 Placebo 26 25.27 10.86 24.38 9.71 Cardiovascular risk Framingham Risk Score

Multivitamin 36 12.98 8.60 11.96 8.46 .132 .718

Placebo 37 13.00 7.95 11.66 7.50 Interaction values represent the time x treatment interaction analysis.

5.11.5.1 Changes in Peripheral Blood pressure There were no significant treatment effects found on peripheral blood pressure

measurements. Table 5-11 displays the means and standard deviations for the blood

pressure measurements at baseline and follow-up.

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5.11.5.2 Changes in Central Cardiovascular Measurements. There were no significant effects of treatment found on any of the central blood pressure

parameters. Additionally, no significant effects of treatment were found on

augmentation pressure or augmentation index. See Table 5-11 for means and standard

deviations from the baseline and follow-up sessions.

5.11.5.3 Cardiovascular Risk score As can be seen from Table 5-11, no significant treatment effects were observed on the

Framingham risk scores.

5.12 Discussion

The current study investigated the effects of 16-weeks of chronic supplementation of a

multivitamin, mineral and herbal preparation on mood and cardiovascular health in a

group of healthy, community-dwelling, older adults aged 50 to 78 years. No significant

effects of chronic MVM supplementation on mood were observed. However, significant

improvements on one mood scale were observed for participants in the placebo group.

Therefore, the primary hypothesis that MVM supplementation would improve mood,

was not supported. The secondary hypothesis that the MVM would improve blood

vitamin levels and reduce homocysteine was supported. However, no other

cardiovascular outcomes were influenced by MVM supplementation. An exploratory

analysis showed that greater folate levels due to MVM supplementation were associated

with reduced mental fatigue.

The study aimed to examine the mood effects of MVM supplementation in an older,

healthy group. But can the group be characterised as healthy? To answer this, a

number of measures were assessed in order to determine the underlying health, and any

improvements to these parameters due to the MVM. With regards to cognitive health,

the Mini Mental Stare Examination (MMSE) was used in order to obtain a global

measure of cognitive health. In order for a participant to be eligible for the study, they

were required to score 27 or above on the MMSE. This cut-off is more rigid than the

trial reported in the following chapter (Chapter 6), but assured that all participants were

cognitively intact, with minimal cognitive decline. The average BMI of the group was

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26.52 kg/m2, but ranged widely from 17.9 to 39.7 kg/m2. According to standard cut-

offs, this would mean that the group were on average, slightly overweight. However,

this seems to be a contentious point in the literature, with some suggesting that the

current BMI classifications are overly restrictive for older groups, and should be slightly

relaxed (Janssen, 2007). Likewise, cholesterol levels were slightly elevated in the

group. Average HDL and triglyceride levels were within the reference for each

measure, however LDL levels were slightly above the cut-off. With regards to

cardiovascular health parameters, such as blood pressure and cardiovascular disease

risk, the group was relatively healthy. Systolic blood pressure was slightly above the

norm, on average, but still fell below the range of hypertension. Furthermore,

cardiovascular risk, as measure by the Framingham Risk calculation, was low in the

group (i.e. Mean of 12 = risk of 1%). Taken together, the current group was classified

as healthy, free from cognitive impairment, cardiovascular disease and mood disorder.

5.12.1 The Relationship between Blood Nutrient Levels and Mood at Baseline Fasting blood samples were collected from all participants at both study visits in order

to examine the changes in blood vitamin and nutrient status post supplementation.

Baseline blood nutrient levels were correlated with baseline mood scores in order to

identify any relationships between mood and bloods at the beginning of the study. The

results revealed very few significant relationships between the baseline blood and mood

measures. Further to this, when scatterplots of the relationships were examined, it

appeared that scores of zero on the mood scales were influencing these relationships. In

order to address this concern, all participants that reported a zero score were removed

from the correlational analysis. Additionally, the relationship between vitamin E levels

and the somatic subscale of the GHQ looked to be influenced by 2 points on the

scatterplot. When these points, along with the scores of zero were removed from the

analysis, the relationships were no longer significant.

Surprisingly, the B vitamin measures were not significantly associated with any of the

mood measures at baseline. This is inconsistent with the literature that has observed

significant correlations between B vitamins, in particular B12 and folate, and mood

measures (See chapter 3, section 3.5 for a review). The lack of significant correlations

163

between B vitamins and mood could be due to the lack of deficiency in the sample. For

instance, according to standard cut-offs, only one participant was classified as B12

deficient, with 4 in the equivocal deficiency range. Regarding folate, all participants

had levels above normal. This could be due to mandatory folate fortification that now

takes place in Australia (Food Standards Australia New Zealand, 2009). Vitamin B6

levels were also well within the preferred range for all participants. Despite the

relatively good B vitamin status of the participants, homocysteine levels tended to be

slightly higher than is desired. As described in Chapter 3 (section 3.4.4), homocysteine

is dependent on B vitamins, particularly B12 and folate, for both its formation and

removal. Higher levels of homocysteine have been associated with increased

cardiovascular risk (Wald, Law et al., 2002), as well as depression and anxiety

(Bottiglieri, Laundy et al., 2000). However, in the current study, homocysteine levels

were not significantly associated with mood.

Previous research has found associations between B vitamins and mood symptoms have

mostly observed these relationships in participants that are deficient (Sachdev, Parslow

et al., 2005; Forti, Rietti et al., 2010). Furthermore, the vast majority of these

relationships are also observed in samples with clinical levels of mood disorder, rather

than in healthy samples (Carney, Chary et al., 1990; Bottiglieri, Hyland et al., 1992).

Nevertheless, there have still been studies that have found significant correlations

between mood symptoms and B vitamin levels (see section 3.5 for an overview). The

results from the current study do not support the relationship between B vitamins and

mood symptoms in a group of healthy, older individuals.

5.12.2 Effects of multivitamin supplementation on mood In the current study, the hypothesis that MVM supplementation would improve mood

was not supported. No significant effects of the MVM treatment were observed on any

of the mood scales. However, improvements were found on the HADS anxiety and

depression scales in the placebo group. This is inconsistent with past research that has

found that supplementation with MVMs for as little as 2 months can improve measures

of mood in an older population. For example, mood improvements due to MVM

supplementation, in a similar age group, with a very similar supplement, have

164

previously been reported by our group (Harris, Kirk et al., 2011). The participants in

the current study scored slightly lower on the DASS than the group in our earlier study.

Additionally, the group in our previous study was classified as ‘at-risk’, indicating that

there may have been more potential for improvement compared to the current sample.

Other groups have found similar mood improvements in their samples (Gariballa and

Forster, 2007b; Gosney, Hammond et al., 2008). However, the results of the present

study are in line with the results reported by Cockle et al (2000), who found no effects

of MVM supplementation on mood in their sample of healthy older adults. An

important note is that, particularly on the DASS, the MVM group in the current study

scored lower than the placebo group at the baseline session. This indicates that the

active treatment group seemed to be healthier, with fewer mood symptoms than the

placebo group, which may have confounded the results. In order to address this

problem, to some extent, an analysis of the individual levels of vitamins and associated

improvements in mood were examined.

As discussed in Chapter 4, past research in younger groups has yielded mixed results.

Like the current study, some researchers have reported no beneficial effects of MVM

supplementation (Willemsen, Petchot-Bacqué et al., 1997; Haskell, Robertson et al.,

2010). A previous report from our group also did not uncover any chronic effects of

MVM supplementation on mood in younger adults, however when measured in-home

with a mobile phone, reductions in stress, fatigue and anxiety were observed soon after

consuming the supplement (Pipingas, Camfield et al., 2013), suggesting a potential

acute effect of MVMs on aspects of mood.

The lack of significant treatment effects in this study is also in contrast with the findings

of Kennedy et al. (2010). In this study, scores on the GHQ-12 and the PSS were

significantly reduced in the MVM group. In the current study, no treatment effects were

observed on either of these scales. Similarly, Carroll et al. (2000) found benefits of

MVM supplementation on GHQ-28 scores, the HADS anxiety scale and the PSS, which

is also at odds with the current results. However, it should be noted that these findings

were observed in a younger sample of participants, and therefore may not be

generalizable to an elderly sample.

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The MVM supplements used in the current study contained a broad range of vitamins,

minerals and antioxidants. The supplements are designed to counteract the nutritional

deficiencies commonly observed in older participant groups. Compliance in the study

was adequate, with only one participant found to be non-compliant; this was supported

by both retuned tablet counts as well as significant increases in blood vitamin levels in

the MVM group. Therefore, the finding that the MVM supplementation did not

improve mood in this healthier group of older adults is bolstered by the rigour of

monitoring a high compliance to the study intervention.

In the current investigation, participants were instructed not to consume their

supplements the morning of the follow-up session in order to eliminate potential acute

effects of the MVM on mood outcomes, consistent with the design of our previous work

(Pipingas, Camfield et al., 2013). However, the majority of previous studies (except for

Haskell, Robertson et al. (2010)) did not report stopping treatment the day of the follow-

up testing session, meaning that they measured both chronic and acute effects of the

supplements on the day of testing. Since the participants in the MVM group had

adapted to consuming a MVM daily, the lack of positive findings could be attributed to

a ‘withdrawal’ from the MVM on the morning of the testing session. This effect would

not be evident in the placebo group, as they would not have experienced the benefits of

the MVM over the course of the treatment intervention period. In order to test this

hypothesis, research using an acute as well as chronic dosing regimen, like that

described in the following chapter, is needed.

5.12.3 Multivitamins and Stress reaction The exploratory aim of investigating the effects of MVM supplementation on the

reaction to the MTF did not reveal any significant effects. Previously only two other

studies have investigated the effects of MVM supplementation on changes in mood in

response to the MTF with conflicting results. Importantly, both of these studies were

conducted with younger adults, and as such, no data exists for elderly groups.

Haskell et al. (2010) found that MVM supplementation in a group of healthy, young

individuals, attenuated physical fatigue ratings and a trend towards an attenuation of

alertness in the MVM group. However, our group recently reported no effects of MVM

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supplementation, in a young healthy group, and response to MTF (Pipingas, Camfield et

al., 2013). In the current study, while the MTF was found to decrease calmness and

contentedness, and increase levels of self-reported stress, the MVM did not attenuate the

response to the MTF.

Studies using other interventions, particularly herbs such as Valerian, sage and lemon

balm, have found the MTF to be sensitive to nutraceutical interventions, suggesting that

task performance has the potential to be modified by natural substances (Kennedy,

Little et al., 2004; Kennedy, Little et al., 2006). Furthermore, an investigation by

Wetherell and Sidgreaves (2005) found that the MTF increased rating of stress and was

also found to stimulate the secretion of cortisol, a hormone that is released/produced

during the stress response. These results suggest that the MTF has the potential to

induce a stress response in a laboratory setting. The results of the current investigation

support the findings of Wetherell and Sidgreaves (2005). The MTF reduced levels of

calmness and contentedness at both study visits, and self-reported stress and fatigue

were increased at the baseline session.

The lack of evidence from previous MVM studies, combined with the results from the

current study, makes it difficult to form any solid conclusions regarding the efficacy of

MVM supplements in attenuating the response to a laboratory stressor. These findings

are in contrast to more real world investigations. Novel research from New Zealand,

where an earthquake occurred in 2010, has shown that micronutrient interventions have

the potential to mediate the response to acute stress. Rucklidge et al. (2011), who were

part way through investigating the effects of MVMs in the treatment of Attention-

Deficit/Hyperactivity Disorder (ADHD), found that the MVM group reported

significantly less anxiety and stress following the earthquake when compared to the

control group. These results were confirmed in another study, which compared

different MVM formulations, as a way to reduce acute stress following the 2011

earthquake in Christchurch, New Zealand. The results of this study also found that

MVMs were effective in combating the acute stress associated with living through a

natural disaster (Rucklidge, Andridge et al., 2012). Kaplan et al. (2015) also found that

multi-nutrient interventions were effective in reducing stress and anxiety after the

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Alberta, Canada flooding’s in 2013. The results of these three trials suggest that MVMs

are effective in reducing the high levels of stress and anxiety following a natural

disaster. It could be that the stress induced in the laboratory is not severe enough to be

influenced by MVM intervention.

5.12.4 Multivitamin Supplementation and Blood Biomarkers While no effects on mood or stress reaction were observed in the current study, a

number of significant changes were observed with regards to blood biomarkers

suggesting that MVM supplementation was effective in improving blood vitamin status.

Additionally, analysis of blood safety markers indicated that the MVM was well

tolerated and had no detrimental effects to the functioning of the kidneys or liver.

5.12.4.1 Blood Safety Markers: the influence of multivitamins In order to assess the safety and tolerability of the MVM supplements, a number of

blood safety biomarkers were assessed. Liver and renal function tests, as well as

multiple biochemical metabolite analysis (eg. Sodium, potassium) were carried out at

the baseline and follow-up sessions.

An important finding of the current study was that there were no significant changes

observed on any of the blood safety measures after treatment indicating that the MVM

was well tolerated and had no detrimental effects on general health biomarkers.

A slight decrease in serum sodium was observed in the MVM group. It is important to

note, the sodium levels in both groups were within the normal range outlined by the

pathology company, and remained so after supplementation. It is likely that this small

decrease in sodium is a metabolic change in response to the MVM and of little

importance.

To the best of our knowledge, no other research groups have investigated the direct

effects of multivitamin and mineral supplements on the liver and kidneys in a healthy,

elderly cohort, free from disorders. One other paper identified in the literature, was

research from our group that also found no negative effects of the same multivitamin

preparation on kidney and liver function (Macpherson, Ellis et al., 2012). The results of

the current study, combined with the results of Macpherson et al. (2012), indicate that

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the multivitamin and mineral preparation under investigation had no detrimental effects

on the function of the kidneys and liver, in this group of healthy participants over the

supplementation period. In recent years, controversy has surrounded the use of MVM

supplements since a paper published by Mursu et al. (2011) suggested that MVM use

was associated with increased mortality. This paper has since been challenged by the

results of a meta-analysis of RCTs that did not find any associations between mortality

and MVM supplementation (Macpherson, Pipingas et al., 2013). The current study

provides further evidence of the safety and tolerability of MVM supplementation.

5.12.4.2 Blood vitamin biomarkers and multivitamin supplementation The multivitamin and mineral treatment significantly increased the levels of vitamins

B12, B6 and folate in the blood, which contributed to a reduction of homocysteine.

These findings are consistent with past research that has demonstrated reductions in

homocysteine after as little as 8 weeks of MVM supplementation (Haskell, Robertson et

al., 2010; Harris, Macpherson et al., 2012). Modifying homocysteine is a possible

pathway through which mood improvements may occur, as homocysteine has

consistently been shown to be a risk factor for cardiovascular disease and depression

(Nygård, Vollset et al., 1995; Bottiglieri, 2005). Homocysteine reduction in the current

investigation was significant, with the MVM group demonstrating over a 13% reduction

in homocysteine.

Significant increases in vitamin B12, B6 and folate were also observed in the current

study. B12 increased in the MVM group by over 30%. Furthermore, folate levels in the

MVM group increased by almost 42%. Of significant note is the increase in vitamin B6.

B6 levels in the MVM group increases by well over 400%. Despite the significant

increases in B vitamin levels in the MVM group, mood was not changed. Vitamins B12,

folate and B6 are crucial for one-carbon metabolism, a process through which SAMe is

formed. SAMe, the major methyl donor in the body is critical for the production of the

neurotransmitters serotonin, norepinephrine and dopamine (Spillmann and Fava, 1996).

These neurotransmitters have long been associated with mood modulation. However, in

the current study these benefits on blood vitamin status were not translated into mood

improvements. Perhaps in order to observe changes in mood in a healthy sample with

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only slight mood symptoms, a longer duration of supplementation is required to see any

benefit to mood.

No changes in vitamin E levels were observed in the current investigation. Vitamin E is

primarily transported in the blood via lipids, particularly triglycerides and LDL

cholesterol (Maes, De Vos et al., 2000). It is possible that increases in serum levels of

vitamin E were not observed in the current study, as levels of LDL cholesterol were

reduced in both groups after the intervention. Vitamin E is considered a powerful, fat-

soluble antioxidant, with important actions within the brain. Vitamin E, in combination

with selenium, protects the brain against ageing, and aids in the maintenance of cellular

structures within the brain (Bourre, 2006). Furthermore, the antioxidant capacities of

vitamin E protect the brain against the detrimental effects of oxidative stress (Gómez-

Pinilla, 2008). While no researchers have investigated the influence of vitamin E on

mood with a RCT design, depressed patients have been shown to have lower serum

levels of vitamin E (Maes, De Vos et al., 2000), and impaired antioxidant defences and

oxidative stress have been proposed to be a mechanism through which depression is

manifested (Maes, Yirmyia et al., 2009; Gawryluk, Wang et al., 2011).

Zinc status was not modified by the MVM. Zinc is an essential trace element required

by over 100 enzymes in the human body (Nowak and Szewczyk, 2002). Zinc levels in

patients with major depressive disorder (MDD) are often lower, and zinc status has been

linked to the severity of depressive illness (Nowak, Szewczyk et al., 2005; Levenson,

2006). Furthermore, zinc has been suggested to exert its antidepressant effects via a

similar pathway as traditional antidepressant therapies (Dickerman and Liu, 2011).

Zinc also has an important role in the maintenance of cardiovascular health. Zinc

maintains the health of the endothelium, and lower levels of zinc can lead to

deficiencies of zinc in the endothelial barrier, which can impair the endothelial barrier

function (Meerarani, Ramadass et al., 2000). Adequate zinc intake protects against and

inhibits the progression of cardiovascular disease processes, most likely due to its

antioxidant capacity (Little, Bhattacharya et al., 2010). The elderly are particularly

susceptible to the build-up of inflammatory markers, such as C-Reactive Protein (CRP)

and pro-inflammatory cytokines, and zinc, as a powerful antioxidant, targets free-

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radicals that cause inflammation (Wong and Ho, 2012). As described in Chapter 2,

depression is associated with neurodegeneration of the brain, which has been linked to

inflammatory processes (Maes, Yirmyia et al., 2009).

It is important to note that serum zinc measurement is a relatively poor measure of true

zinc status (Braun and Cohen, 2009). The majority of zinc within the body is found

intracellularly, while only a small amount is present in circulation (Wood, 2000). The

amount of zinc in plasma can be affected by the body’s homeostatic system, as well as

stress, diurnal rhythm, infection and plasma protein levels, and is often not an accurate

reflection of true zinc status (Wood, 2000). It is possible that serum zinc levels were

not modified in the current investigation due to absorption by tissue rather than plasma

proteins. Furthermore, participants in both groups began the study with adequate serum

zinc levels, leaving only a small window of improvement due to vitamin

supplementation.

The inflammatory markers, hsCRP and fibrinogen were not modified by the MVM in

the current study. Levels of fibrinogen increase during inflammation (Stec, Silbershatz

et al., 2000), and as such elevated levels have been associated with cardiovascular risk

factors, cardiovascular disease and mortality (Smith, Harbord et al., 2005; Mora, Rifai

et al., 2006). Furthermore, fibrinogen is a strong predictor of atherosclerosis (Zoccali,

Benedetto et al., 2003), and links between increased arterial stiffness and systolic

dysfunction have been observed in individuals without coronary heart disease (Palmieri,

Celentano et al., 2001). Recently, elevated fibrinogen has been associated with

increased depressive symptoms (Panagiotakos, Pitsavos et al., 2004), and there is some

evidence to suggest that anxiety symptoms can be influenced by fibrinogen levels

(Pitsavos, Panagiotakos et al., 2006). Like fibrinogen, levels of hsCRP increase in

response to inflammation (Koenig, Sund et al., 1999). Furthermore, hsCRP has been

identified as an independent risk factor for CVD. Ridker et al. (2000) found that hsCRP

was the strongest predictor of cardiovascular events in post-menopausal women. Results

from a recent meta-analysis observed associations between depression and hsCRP in

both clinical and non-clinical samples (Howren, Lamkin et al., 2009). Little research

exists for the role of nutritional interventions in improving inflammatory markers.

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Church et al. (2003) found that a MVM intervention was effective in reducing CRP

levels after 6 months of supplementation. Similarly, Castillio et al. (2011) observed

reductions in hsCRP in cardiac patients after supplementing with antioxidant vitamins C

and E, combined with omega-3 fish oil for 7 days prior to heart surgery. Conversely,

Bae et al (2009) found no effects of four weeks of antioxidant treatment (Vitamin C and

quercetin) on CRP in patients with rheumatoid arthritis.

5.12.4.3 The influence of the Change in blood vitamin status on changes in mood Despite the lack of positive mood findings in the current investigation, an analysis of

the relationships between the change in biological markers of B vitamin status and

inflammation and the change in mood were assessed. This analysis was conducted in

order to investigate the potential confounding effects of individual differences in the

uptake of MVM constituents and the resulting mood effects. It was predicted that

individuals with much greater change from baseline in their uptake of vitamins (or

change in health parameters) would show a corresponding improvement in mood.

Changes in the inflammatory markers, hsCRP and fibrinogen, were not associated with

changes in mood. This is most likely because there was very little change in the

inflammatory markers. Only one other study was identified in the literature that has

investigated the role of MVMs on CRP levels. This study found that six months of

MVM supplementation lead to a significant reduction in CRP levels (Church, Earnest et

al., 2003). The current study does not support the role of MVMs in reducing

inflammation.

With regards to the B vitamin measures, changes in blood levels of B12 and B6 were not

associated with changes in any of the mood variables assessed. However, changes in

folate were significantly related to changes in mental fatigue (Chalder Fatigue Scale). A

positive change in folate levels equated to increased red cell folate levels in the blood,

while negative change on the mental fatigue subscale equated to a reduction in self-

rated mental fatigue. The negative correlation that was observed indicated that

increasing folate was associated with a decrease in mental fatigue. The graph (Figure 5-

9) shows that individuals that showed larger increases in folate were those that showed

greater reductions in mental fatigue. While the nature of fatigue is relatively unclear,

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for the purposes of the current study, mental fatigue was defined as a decrease in

cognitive performance, resulting from long periods of mental activity. Previous

research has shown that supplements that contain folic acid, in the form of a MVM, are

effective in improving fatigue ratings in younger groups (Kennedy, Haskell et al., 2008;

Haskell, Robertson et al., 2010). It could be that a longer duration of supplementation

or a larger dose of folate may result in greater effects to mood and fatigue. This has yet

to be studied in the literature, however, a UK group has identified improvements to

cognitive function and reductions in brain atrophy in patients with Mild Cognitive

Impairment (MCI), suggesting that high dose B vitamins, over a longer period of time

(2 years) provide benefits to brain health (Smith, Smith et al., 2010).

The current results suggest that, even though mood was not modified by the MVM

supplementation, individual components of the supplement can contribute to changes in

mood. Perhaps with a longer intervention period, more pronounced effects would have

been observed.

5.12.5 Multivitamins and Cardiovascular Health. The effect of MVM supplementation on cardiovascular function was assessed by a

number of measures in the current study. Both peripheral and central (aortic) measures

for blood pressure were recorded. Additionally, central augmentation pressure and

augmentation index were assessed.

In the current study, cardiovascular variables were not changed by MVM

supplementation. Several vitamins have been shown to be effective in reducing blood

pressure. A combination of vitamin D and calcium effectively reduced systolic blood

pressure by 5mm/Hg or more in an eight-week RCT of elderly women (Pfeifer,

Begerow et al., 2001). Additionally, supplementation with vitamin C has been shown to

reduce blood pressure in a number of studies. Fotherby et al (2000) found that 500mg

per day of vitamin C reduced systolic blood pressure in healthy older adults. Vitamin C

has also been demonstrated to reduce blood pressure in hypertensive patients (Duffy,

Gokce et al., 1999; Ward, Hodgson et al., 2005).

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Antioxidant vitamins have been shown to influence measures of arterial stiffness. For

example, previous work has demonstrated improvements in arterial stiffness measures

after supplementation with vitamin E (Rasool, Rahman et al., 2008), vitamin C (Mullan,

Young et al., 2002) and combinations of both (Plantinga, Ghiadoni et al., 2007), while

others have found no effect (Kelly, Poo Yeo et al., 2008).

Chronic supplementation with vitamin C has also been shown to reduce augmentation

index. Mullan et al. (2002) found that 4 weeks supplementation with 500mg/day of

vitamin reduced augmentation index, in patients with type 2 diabetes. While Plantinga

et al. (2007) observed a reduction in augmentation index in a group of patients with

untreated essential hypertension, after 8 weeks of supplementation with a combination

on vitamin C and vitamin E. However, this improvement failed to reach statistical

significance. Rasool et al (2008) found a marginally significant reduction in

augmentation index after 2 months of supplementation with vitamin E in a group of

healthy males.

With regards to the effects of B vitamins on arterial stiffness, the research is lacking.

Koyama (2010) found that co-administration of folate and methylcobalamin was more

effective in reducing augmentation index than folate alone, in patients on

haemodialysis. However, results from the Atherosclerosis and Folic Acid

Supplementation Trial (ASFAST) did not find any significant effect of folic acid

supplementation on indices of arterial stiffness in chronic renal failure patients

(Zoungas, McGrath et al., 2006)

The lack of positive findings in the current study could be due to the differences in

group demographics and health, compared to the other studies. For instance, the studies

that have reported beneficial effects of vitamin C and folate were all found in patients

with hypertension, chronic renal issues or diabetes, rather than a healthy sample.

Furthermore, the supplements used in the current study only contained a small amount

of vitamins C and E (200mg and 20-25mg respectively), which may have not been great

enough to see any beneficial effects on arterial stiffness indices. An additional

explanation could be differences in arterial stiffness itself. For instance, in patient

groups, the arterial stiffness that is often observed is a result of disease processes, and is

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therefore of a functional nature (Wilkinson, Hall et al., 2002; Wilkinson, Qasem et al.,

2002). Functional arterial stiffness is more amenable to improvement with treatment

interventions (Pase, Grima et al., 2011). Conversely, in healthy, older adults, arterial

stiffness is more likely to be age-related, and often not reversible (O'Rourke, 1995).

The participants in the current investigation likely fall into the age-related arterial

stiffness group, and therefore improvements due to supplementation were not observed.

Also, it could be that a longer duration of supplementation is required to see

improvements in arterial stiffness measures in healthy older individuals.

5.12.6 The Action of Multivitamins on Neurotransmitter Production. As previously discussed (section 5.9.4.2), 16-weeks MVM supplementation increased

levels of B12, B6 and folate in the blood. Chapter 3 provided in more detail the

relationship between the B vitamins and homocysteine. Briefly, B12 and folate are

required for the methylation of homocysteine to methionine, and B6 is required for the

methylation of homocysteine to cysteine. Cysteine is a precursor for the major

endogenous antioxidant, glutathione, whereas methionine is essential for the production

of SAMe, which is vital for one-carbon metabolism (Mattson and Shea, 2003).

Additionally, SAMe is involved in several methyl group transfers within the body, and

is the methyl donor in reactions that involve the production of proteins, membrane

phospholipids, DNA synthesis and repair, myelin and in the synthesis of

neurotransmitters (Selhub, Bagley et al., 2000). Furthermore, the synthesis of the

neurotransmitters serotonin, noradrenaline and dopamine, requires an adequate supply

of the B complex vitamins, particularly B12, folate and B6 (Huskisson, Maggini et al.,

2007a).

Increasing neurotransmitter production, and therefore an improvement in the general

functioning of the nervous system could account for any mood benefits of MVMs.

These improvements would be expected to be exerted across a range of mood facets, but

this was not evident in the current investigation. However, as discussed in chapter 2

(section 2.2.2), increasing neurotransmitters is not always an effective way of

combating depression.

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5.13 Limitations and future directions

A limitation in the current study was that due to sample size constraints, male and

female participants were assessed as one group. Males and females have different daily

requirements of nutrients, and may respond to supplementation differently. However, to

counteract these differences in requirements, the supplements used in the current study

were tailored to the daily nutritional requirements of males and females resulting in

each gender receiving a similar daily allowance of vitamins and minerals. An analysis

of the change in B vitamin levels after supplementation did not differ between the

genders, suggesting that there were no differences in the way that male and female

participants responded to the supplement. Despite this, future research should aim to

investigate the effects of MVMs on mood in separate gender groups.

Additionally, a larger sample of participants would have allowed for an analysis of

subgroups within the study population, such as a comparison between those with poorer

baseline health to those with good health, as well as a comparison between those with

poor verses good mental health at baseline. The participants in the current study were

all in good health, highly educated and were within the “optimal” range for baseline

vitamin status. Many of the previous investigations in older groups were conducted in

groups that had poorer general health than those studied in the current trial. Both the

nonclinical sample, and good baseline health may have limited the findings. As

discussed in chapter 4, the majority of evidence for the benefits of MVMs on mood

comes from samples comprised of ‘at-risk’ individuals. Future research may benefit

from investigating the actions of MVMs in samples with compromised health.

Another limitation of the current study was the use of multiple mood questionnaires.

The HADS was specifically designed to avoid somatic symptoms of anxiety and

depression, such as fatigue, insomnia and hypersomnia. The other scales, such as

DASS, BDI/BAI and STAI, all include items that assess somatic symptoms of anxiety

and depression. Whether this was the reason why a difference was observed in the

placebo group on the HADS is unclear. As such, the findings of the current study were

interpreted cautiously.

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Finally, the absence of measures of vitamin C and oxidative stress markers in the

current investigation is another limitation. Levels of vitamin C have previously been

found to be increased by MVM intervention (Cockle, Haller et al., 2000), although the

MVM in the current study contained considerably less vitamin C. Furthermore, vitamin

C has the potential to most effectively protect against inflammation and oxidative stress

(Block, Norkus et al., 2001) and is a considerable limitation in the current investigation.

Future researchers would benefit with the inclusion of other measures of antioxidant

status, such as vitamin A, and oxidative stress markers in order to investigate additional

underlying mechanisms of which MVMs may contribute to mood modification.

Vitamin C, apart from being a major antioxidant in the human body, has been proposed

to be involved in a range of functions within the brain and nervous system (Harrison

and May, 2009). It is well known that vitamin C interacts synergistically with the B

complex vitamins, and is found in abundance in the human brain (Huskisson, Maggini

et al., 2007a). It is well established that vitamin C is an essential co-factor for the

conversion of dopamine to noradrenaline (Bourre, 2006). Furthermore, it has been

suggested that vitamin C may also function as a neuromodulator in neurotransmission

mediated by both dopamine and glutamate (Harrison and May, 2009). It is possible that

increasing vitamin C levels through MVM supplementation may have also contributed

to increased neurotransmitter production and neurotransmission; however this was not

translated into mood improvements in the current investigations. However, as Vitamin

C was not measured, it is not possible to determine if the MVM was successful in

increasing levels of vitamin C.


In summary, the results suggest that 16-weeks supplementation with a combined

multivitamin, mineral and herbal supplement did not improve ratings of mood in a

healthy elderly sample. Specifically, ratings on the Depression, Anxiety and Stress

Scale (DASS) were not improved by the MVM intervention. Additionally, attenuation

of the stress response was not achieved by MVM supplementation in the current study.

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The current study identified significant increases in B vitamin levels and a decreased in

homocysteine after MVM supplementation, however these improvements were not

reflected in mood or cardiovascular changes. Improvements in these biomarkers may

benefit mood and cardiovascular function, but this was not evident in the current study.

Interestingly, when inter-individual differences were investigated by correlational

analyses of change scores, individuals with the largest increases in folate showed a

significant reduction in mental fatigue. It is suggested that this approach has merit and

should be considered in future research in older individuals where potentially high

variability in uptake needs to be accounted for. Particularly in smaller samples, an

ANOVA approach, comparing means may be restrictive. Having blood biomarkers of

vitamin levels presents a useful reference for the observation of mood effects.

In conclusion, while the current study did not find any benefits of MVM

supplementation on mood, the improvements observed on the blood biomarkers suggest

that chronic MVM supplementation is an effective way to improve aspects of health,

such as increasing B vitamin status and reducing levels of homocysteine. More

importantly, this finding is in the absence of acute effects, as this was properly

controlled by the research design.

The following chapter investigates both the acute and chronic effects of MVM

supplementation in a group of healthy elderly women.

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Chapter 6 The Acute and Chronic effects of Multivitamin

Supplements: The BEMS study in women.

6.1 Introduction

The elderly are a population most at risk for nutritional deficiencies (Brownie, 2006).

In older groups, vitamin deficiencies, particularly B vitamin deficiency, can lead to

neurological dysfunction (Selhub, Bagley et al., 2000). Mild psychiatric disturbance

and mood disorders have been linked to poor intake of vitamins and minerals such as

folate, vitamin B12 and zinc (Maes, D'Haese et al., 1994; Coppen and Bolander-

Gouaille, 2005; Marcellini, Giuli et al., 2006; Long and Benton, 2013). The health and

functioning of the central nervous system is heavily reliant on optimal nutrient intake

(Gómez-Pinilla, 2008). B vitamins are essential for many reactions within the body.

Neurotransmitter production, the regulation of homocysteine and one-carbon

metabolism, essential for DNA synthesis and repair, all require an adequate supply of B

vitamins, particularly B12 and folate (Mattson and Shea, 2003). B vitamin deficiencies,

which impair methylation reactions in the body, have been implicated in mood

dysfunction (Reynolds, Carney et al., 1984; Bottiglieri, Laundy et al., 2000).

Multivitamin and mineral supplements contain a range of vitamins, particularly B

vitamins, along with minerals, and often antioxidants, which influence many reactions

in the central nervous system. B vitamins are essential for the synthesis of

neurotransmitters, the production of SAMe and the maintenance of homocysteine

(Selhub, 1999; Mattson and Shea, 2003). Increasingly, evidence is emerging suggesting

that chronic MVM supplementation (between 2 to 4 months) can benefit various aspects

of mood (Long and Benton, 2013). Chapter 4 of this thesis described the results from

numerous randomised controlled trials, with many demonstrating positive effects of

MVM supplementation on mood. A recent meta-analysis (Long and Benton, 2013) has

supported the positive mood enhancing effects of chronic MVM supplementation. The

findings from this meta-analysis suggest MVM supplements have the potential to

improve mild psychiatric symptoms, stress and subclinical anxiety. The findings from

past research are at odds with the results from the study reported in the previous chapter,

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which did not reveal any chronic effects of MVM supplementation on aspects of mood

and stress.

Research from our laboratory, investigating the chronic effects of MVMs in a younger

group of 138, healthy individuals did not uncover any benefits of MVM

supplementation on mood after 16 weeks (Pipingas, Camfield et al., 2013). However,

when mood was assessed in the home, via a mobile phone device, reductions in stress,

physical fatigue, and anxiety were observed. These reductions were most pronounced

soon after the participant had consumed their supplement, suggesting a potential acute

role for MVMs in mood modulation. The home-based mood changes were interpreted

to reflect much more rapid changes in mood following the daily MVM dose. The

participants were instructed not to consume their daily supplement on the morning of

the return visit, and could explain the lack of mood effects.

Very few studies have investigated the acute effects of MVMs. Of the studies that have

investigated the potential mood modulating effects of MVMs, only supplements that

contain the plant extract guaraná have been utilised, rather than typical multivitamin and

mineral preparations, with the exception of the Haskell et al. (2008) study that used a

standard MVM preparation for children. Haskell et al. (2008) did not observe any acute

mood effects of MVM supplementation in a group of healthy children aged from 8 to 12

years. Conversely, Kennedy et al. (2008) found that mental fatigue, induced by a

cognitively demanding computerised battery, was attenuated by the

multivitamin/guaraná preparation in their sample of healthy younger adults. Similarly,

Scholey et al. (2013) found that a MVM with added guaraná significantly increased

contentment after completing a cognitively demanding task. With this small number of

studies available in the literature, it is not possible to determine if the mood effects

observed are due to the actions of the vitamins, or due to the effects of the guaraná

extract. Guaraná has long been known to enhance neurocognitive performance,

including increased alertness and calmness, along with improving memory performance

(Scholey and Haskell, 2008). However, the evidence from these studies comes from

children and young adults, and therefore it is not known if mood would be improved in

older adults after a single dose of MVMs. While the acute actions of MVMs on mood is

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relatively unknown, studies have shown that the B vitamin content of these supplements

are rapidly absorbed, and peak in the blood within 3 hours of ingestions (Bor, Refsum et

al., 2003; Dainty, Bullock et al., 2007; Mönch, Netzel et al., 2010). Coupled with

improvements in mitochondrial function and vascular endothelial function (Kennedy,

Haskell et al., 2008), improved blood flow and vasodilation may increase the

availability of metabolites in the brain and result in acute mood improvements (Scholey,

Harper et al., 2001).

6.2 Aims and hypotheses:

The overall aim of this experiment was to investigate the effects of a combined

multivitamin, mineral and herbal formulation in a group of healthy older women. The

study was limited to females as there is a lack of research in older female groups

(Comerford, 2013; Long and Benton, 2013). Specifically, both the acute (single dose)

and chronic (4-week) effects of the supplement were examined.

The results presented in the current chapter are part of a larger study conducted at the

Centre for Human Psychopharmacology. The focus of this chapter is to examine only

the acute (1-hour) and chronic (4-week) effects of MVMs on mood and cardiovascular

function. The larger study also examined the acute and chronic actions of MVMs on

cognitive performance both in the lab and through the use of mobile phone devices in

the home. The author was involved in the study design, as well as data collection and

analysis.

The primary outcome for the study was chronic mood improvements as measured by the

General Health Questionnaire (GHQ). The GHQ has been shown to be sensitive to

nutritional interventions. In a previous report in a group of elderly men, reductions in

GHQ ratings were achieved after 8 weeks MVM supplementation (Harris, Kirk et al.,

2011). It was specifically hypothesised that ratings on the GHQ would improve after

MVM supplementation for 4-weeks. The remaining retrospective mood scales were

examined at 4 weeks as secondary outcomes.

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A secondary outcome was the acute actions of MVMs on mood. Acute mood was

assessed 1-2 hours post supplementation. This time point was chosen in order to

capture any potential changes in mood as blood vitamin levels increased after MVM

ingestion. The main outcome for acute mood was measured using a modified version of

the Depression, Anxiety and Stress Scale (DASS). The DASS has previously been

shown to be sensitive to MVM interventions, whereby reductions on the scale were

achieved after 8 weeks of supplementation in a group of older men (Harris, Kirk et al.,

2011). The current study is the first to assess the acute actions of a MVM supplement

on mood in an elderly group. Evidence from RCTs in younger samples provide

conflicting results, with reports of improvements in mood and fatigue after a single dose

of a multivitamin containing added guaraná (Kennedy, Haskell et al., 2008; Scholey,

Bauer et al., 2013), while a study conducted in children found no acute benefits

(Haskell, Scholey et al., 2008). It was hypothesised that a single MVM dose would

improve ratings on the DASS. The remaining mood measures (both pen and paper, and

in-lab mobile phone assessments) were examined as secondary acute outcomes.

The final outcome of the study was the assessment of cardiovascular function. The

chronic effect of MVM supplementation on arterial stiffness was examined. In the

current investigation, augmentation index and augmented pressure were the measures of

arterial stiffness that were explored. The effect of MVM supplementation on arterial

stiffness has not been explored in the literature, however there is a growing literature

suggesting the benefits of the antioxidant vitamins, vitamin C and E, for improving

arterial stiffness measures (Rasool, Yuen et al., 2006; Plantinga, Ghiadoni et al., 2007;

Rasool, Rahman et al., 2008). Furthermore, arterial stiffness increases with advancing

age, and increased arterial stiffness has previously been associated with negative mood

states (Tiemeier, 2003; Tiemeier, van Dijck et al., 2004). It was expected that the MVM

supplement would improve indices of arterial stiffness after 4 weeks of

supplementation. Additional cardiovascular health parameters such as peripheral and

central blood pressure were also examined.

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6.3 Methods

The following section will provide a detailed description of the clinical trial methods,

including information regarding the mood and general health instruments, mobile phone

assessments and cardiovascular measures. A description of the baseline characteristics

of the participants and an overview of the statistical analysis plan is provided.

The trial was registered at the Australian New Zealand Clinical Trials Registry

(ACTRN12613001087741). Ethical approval was obtained from the Swinburne

University Human Research Ethics Committee (SUHREC; Appendix D).

6.4 Participant Characteristics

6.4.1 Screening

6.4.1.1 Inclusion and Exclusion criteria

The sample was made up of community dwelling females aged between 50-75 years of

age. The sample was limited to healthy, non-smokers, who were not full-time workers,

were English speaking, and free from medical conditions that may have affected their

ability to participate in the study.

Other exclusion criteria included a history of neurological or psychiatric conditions,

alcohol or drug abuse and dementia. Furthermore, those using antidepressants or

antianxiety medications, anticoagulants, anticholinerigics or anticholinesterase

inhibitors were not included in the study. Additionally, the use of MVMs, B vitamins,

fish oils, ginkgo biloba, antioxidants or other cognitive enhancing supplements were

exclusions for the study. Those using supplements prior to enrolment were asked to

abstain for at least 30 days prior to commencement and duration of the study protocol.

6.4.1.2 Recruitment

Participants were recruited from the community through newspaper advertisements,

website advertising and email. Advertisements were placed in local newspapers and

asked for healthy female’s ages over 50 years, not currently taking vitamins, blood

thinners or antidepressants. Additionally, study information was placed on the

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Swinburne University research website, and emails were sent to individuals who had

given prior consent to be contacted in the Centre for Human Psychopharmacology

participant database. Furthermore, 11 participants were recruited through the

Computer Assisted Telephone Interviewing (CATI) facility, based at Swinburne

University. Participants that completed the trial were compensated $50 for their time.

Furthermore, 11 participants had previously completed the trial reported in Chapter 5.

Any participants that experienced side effects in the previous study were not enrolled

into the current study.

6.4.1.3 Screening procedure

Potential participants were screened over the phone with a basic telephone screen.

Participants that fulfilled the eligibility criteria were invited to attend the first session

where the initial screening and baseline data was collected. An explanatory statement,

regarding the study protocol was emailed or posted to participants. All participants

provided written informed consent (Appendix C). The number of participants recruited

and screened for the study is shown in Figure 6-1.

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Figure 6-1. Participant recruitment flowchart

6.4.2 Screening Measures

6.4.2.1 Mini-Mental State Examination

The Mini-Mental State Examination (MMSE; Folstein, Folstein et al., 1975) is a brief

interview comprising 11 questions used to measure aspects of cognitive function. It is

commonly used in assessment of cognitive impairment and dementia. Participants that

scored less than 25/30 were excluded from the study. Means and standard deviations for

all participants are shown in Table 6-1 below.

6.4.2.2 National Adult Reading Test – Revised

The National Adult Reading Test – Revised (NART-R; Blair and Spreen, 1989) was

used to control for the potential confounding effects of intelligence. The NART-R gives

a brief, reliable estimate of IQ (NART-R IQ). Participants read a series of difficult or

unusual English words, with the number of errors in pronunciation corresponding to

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Full-Scale IQ score. Predicted IQ scores were used as a demographic measure and not

as inclusion/exclusion criteria. Means and standard deviations for all participants are

shown in Table 6-1 below. There was one participant that was unable to reliably

complete the NART-R, due to English being her second language.

6.4.3 Participant baseline demographics

A total of 76 female participants were enrolled in the study. As is shown in Table 6-1

below, the average age of participants was 63.62 (SD = 6.35) years.

Table 6-1 - Participant demographics and morphometrics at baseline

Demographics N M SD Range Age 76 63.62 6.35 50-75 Years Education 76 16.21 3.42 7-26 MMSE 76 29.37 0.81 26-30 NART-R IQ 75 117.59 6.73 90-127 STAI-T 76 32.47 9.70 20-51 Height 74 163.57 6.50 150-178 Weight 74 67.85 12.35 44-94 BMI 74 25.36 4.42 17.1-37.9 MMSE= Mini-Mental State Examination; NART- R IQ = National Adult Reading Test Revised Predicted IQ; STAI-T= State Trait Anxiety Inventory-Trait version; BMI= Body Mass Index

6.5 Trial design, randomisation and blinding procedures

This study was a double-blind, placebo-controlled, randomised, parallel-groups trial.

Participants were randomly assigned to receive either the MVM or placebo treatment

for four weeks. Participants were randomised in blocks of 4, with a ratio of 1:1 using a

computer-generated sequence. All testing procedures were carried out at the Centre for

Human Psychopharmacology, Swinburne University at baseline, 1-hour post

supplementation (acute) and 4-weeks post-supplementation (chronic).

6.5.1 Treatment

The multivitamin, mineral and herbal preparation used in the current trial was the

Swisse Women’s 50+ Ultivite™ (Australian Register of Therapeutic Goods ID:

187121). The MVM contains vitamins, minerals, antioxidants and a number of herbs.

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The ingredients of the Swisse Women’s 50+ Ultivite™ and nutrient recommended daily

intakes for elderly women are shown below in Table 6-2.

On the first day of testing, participants were given one MVM capsule or placebo with

food, after the completion of all baseline measurements. Participants were instructed to

consume one MVM capsule or placebo daily with food for 4 weeks. The placebo

capsules, provided by Swisse Vitamins were matched for appearance and taste, and

contained starch and a small amount of riboflavin (2mg) to give them a similar smell

and coloration of the urine. Participants were asked to abstain from the treatment on the

day of post-treatment testing.

6.5.1.1 Compliance

In order to assess compliance, all participants were required to return all unused tablets

to be counted. In the current study, a limit of 80% compliance was used.

6.5.2 Determination of Sample size A recent meta-analysis (Long and Benton, 2013) had indicated that MVMs exert small

to medium sized effects on measures of perceived stress and fatigue (standard mean

difference = .29). The MVM formulation used in the current study has comparable

levels of B vitamins to those used in the meta-analysis. The power analysis was

conducted using G*Power 3.1.3. In order to have an 80% chance of detecting an effect

size of this magnitude (F=.15), in a two arm study (MVM, placebo), with at 3 time

points (baseline, 1-hour post treatment, 1-month post treatment), a total of 75

participants would be required for the sample (alpha level p=.05). A total of 86

participants were included in the study in order to account for a 15% drop out rate.

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Table 6-2 - Constituents of the multivitamin treatment Component Daily Dose RDI Retinyl Acetate (equiv. To 2500 IU of vitamin A) 862.5 µg 700µg Lactobacillius Rhamnosus 80 million

organisms D-alpha-tocopheryl acid succinate (equiv. Vitamin E 30.25 IU) 20 mg 7mg* Lactobacillus Acidophilus 80 million

organisms Thiamine Hydrochloride (vitamin B1) 30 mg 1.2mg Bifidobacterium Longum 35 million

organisms Riboflavine (vitamin B2) 30 mg 1.1-1.3mg Cirtus Bioflavonoids extract 20 mg Nicotinamide (vitamin B3) 20 mg 14mg Vaccinium Macrocarpon Fruit Dry (patented cranberry pacran) 800 mg Calcium Pantothenate (vitamin B5)(equiv. Pantothenic acid 68.7mg)

70 mg 4mg* Silybum Marianum Dry Fruit (St. Mary’s thistle) (equiv. flavanolignans calculated as silybin 17.14mg)

1500 mg



1000 mg

Cyanocobalamin (vitamin B12) 115 µg 2.4µg Tunera Diffusa Leaf Dry (Damiana) 500 mg Cholecalciferol (vitamin D3) (equiv. Vitamin D 200 IU) 5 µg 10-15µg* Scutellaria Lateriflora Herb Dry (Skullcap) 50 mg Biotin (vitamin H) 150 µg 25µg* Vitis Vinifera Dry Seed (Grape seed) (equiv. procyanidins 7.9mg) 1000 mg Folic Acid 500 µg 400µg Urtica Dioica Leaf Dry (Nettle) 100 mg Calcium Ascorbate Dihydrate (vitamin C) (equiv. Ascorbic acid 165.3mg)

200 mg 45mg Ubidecarenone (Co-enzyme Q10) (from patented Ultrasome CoQ10) 2 mg

Phytomenadione (vitamin K) 60 µg 60µg* Cynara Scolymus Leaf Dry (Globe artichoke) 50 mg Zinc Amino Acid Chelate (equiv. Zinc 20mg) 75 mg 8mg Cimicifuga Racemosa Root & Rhizome Dry (Black cohosh) 200 mg Calcium Orotate (equiv. Calcium 10mg) 100 mg 1300mg Curcuma Longa Rhizome Dry (Turmeric) 100 mg Magnesium Aspartate Dihydrate (equiv. Magnesium 6.74mg) 100 mg 320µg Withania Somnifera Root Dry (Ashwagandha) 500 mg Selenomethionine (equiv. Selenium 26mcg) 65 µg 60µg* Crataegus Monogyna Fruit Dry (Hawthorn) 100 mg Molybdenum Trioxide (equiv. Molybdenum 45 µg) 67.5 µg 45µg* Silica Colloidal Anhydrous (equiv. silicon 9.35mg) 20 mg Chromium Picolinate (equiv. Chromium 50 µg) 402 µg 25µg* Bacopa Monnieri Whole Plant Dry (Bacopa) (equiv. bacosides calculated

as bacoside A 1.125mg) 50 mg

Manganese Amino Acid Chelate (equiv. Manganese 4mg) 40 mg 5mg* Lecithin Powder – Soy Phosphatidylserine Enriched Soy (equiv. phosphatidylserine 2mg)

10 mg

Ferrous Fumerate (equiv. Iron 5mg) 16.01 mg 8mg Spearmint Oil 2 mg Copper Gluconate (equiv. Copper 1.7mg) 8.57 mg 1.2mg* Vaccinium Myrtillus Fruit Dry (Bilberry) (equiv. anthocyanosides

324mcg) 100 mg

Potassium Iodide (equiv. Iodine 149.83mcg) (equiv. Potassium 46.18mcg)

196 µg 150µg Tagetes Erecta Flower Dry (Marigold) (Lutein esters calculated as lutein (of Tagetes erecta) 1mg)

100 mg

RDI = recommended daily intake for Australian women aged 51 or above. Where two values are shown higher value refers to separate RDI for women >70 years of age. * =

Adequate intake where RDI values were not available. RDI and adequate intake values obtained from National Health and Medical research Council (2006).

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6.6 Measures

6.6.1 Mobile phone measures

The following measures delivered via mobile phone were assessed at baseline, 1-hour

post-treatment, on 8 days over the four-week intervention period and at the 1-month

post-treatment assessment. The mobile phone tasks also contained a cognitive

assessment battery that is not reported in this thesis, but are presented elsewhere

(Macpherson, Rowsell et al., 2015). Therefore, only the mood data obtained from the

devices will be reported. Participants were given sufficient training on the mobile

phone tasks prior to the baseline recording. Detailed instructions were also provided to

participants on how to complete the weekly tasks at home. Three time points were of

interest in the current study: baseline, 1-hour post dose (acute), and the 1-month follow-

up (chronic).

6.6.1.1 Bond-Lader Visual Analogue Scale

The Bond-Lader Visual Analogue Scales (VAS; Bond and Lader, 1974) requires

participants to mark the appropriate position on a horizontal line separating two

adjective pairs. The VAS is a measure of subjective mood experience and is included to

assess normal (non-disordered) mood. Lower scores are indicative of more desirable

mood states. Analysis of the VAS results in three subscales: Alert, Calm and Content.

6.6.1.2 Visual Analogue Scales (Stress, Anxiety, Concentration, Fatigue -

Physical/Mental)

The Visual Analogue Scale consists of a single line for each item with end-points

labelled ‘Not at all’ and ‘Very much so’. Participants are instructed to indicate on the

line how they feel at that point in time.

6.6.2 Mood measures

6.6.2.1 The Depression, Anxiety and Stress Scale

The Depression, Anxiety and Stress scale (DASS; Lovibond and Lovibond, 1995) is a

short questionnaire has three sub-factors: depression, anxiety and stress. The DASS is

relevant for both clinical and non-clinical populations and has adequate reliability and

validity. The 21 items comprise affect related symptoms, pertaining to possible

dysfunction or disorder, on a 4-point scale from 0 to 3, thus yielding a possible range

from 0 to 63. Higher scores indicate a higher degree of dysfunction and less desirable

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affect experience. A score of zero does not indicate positive mood, but rather the lack

of presence of symptoms pertaining to dysphoric mood. Nevertheless, the DASS is

considered suitable for normal populations as some experience of such symptoms is

considered normal in day-to day-life. In the current study, the DASS was slightly

modified to ask participants how they were feeling at that moment in time, rather than

over the past week. The modified DASS was completed at baseline, 1-hour post-

treatment and at the 1-month post-treatment assessment.

6.6.2.2 Hospital Anxiety and Depression Scale

The Hospital Anxiety and depression scale (HADS; Zigmond and Snaith, 1983) is a

brief (14 item) measure of the severity of anxiety and depression, with seven items

representing each subscale. Participants are asked to indicate which reply reflects best

their mood over the past week. Higher scores on each trait subscale indicate more

severe anxiety or depression. The HADS is one of the most widely used measures for

assessing anxiety and depression in research settings. The HADS was completed at

baseline and at the 1-month post-treatment assessment.

6.6.2.3 Perceived Stress Scale

The Perceived Stress Scale (PSS; Cohen, Kamarck et al., 1983) measures the degree to

which respondents view situations in their life as stressful. The PSS is made up of 14

items, scored on a 5-point scale, ranging from ‘never’ to ‘very often’. Higher scores on

the PSS are associated with higher levels of perceived stress. The PSS will be

completed at baseline and at the 1-month post-treatment assessment.

6.6.2.4 State-Trait Anxiety Inventory

The State-Trait Anxiety Inventory (STAI; Spielberger, 1983) is a widely used

instrument designed to measure both fluctuating levels of anxiety (State) and more

general, stable levels of anxiety (Trait). The ‘State’ subscale contains 20 items, and

requires participants to rate how much they feel like each item at the time of response.

The scale is scored on a 4-point scale ranging from ‘not at all’ to ‘very much so’. The

‘trait’ subscale also contains 20 items, and participants are asked to rate how they

generally feel with regards to each item. The scale is scored on a 4-point scale ranging

from ‘almost never’ to ‘almost always’. Scores on both subscales range from 20 to 80,

with higher scores indicating higher levels of anxiety. Participants were required to

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complete the state version of the STAI at baseline, 1 hour post-treatment and at the 1-

month post-treatment assessment.

6.6.3 Wellbeing and energy

6.6.3.1 General Health Questionnaire

The General Health Questionnaire (GHQ; Goldberg, 1978) comprises of 28 health-

related quality of life items [e.g. life satisfaction, medical complaints, on a four-point

likert scale ranging from much less than usual [0] to much more than usual [3]. The

product provides a score with a possible range of 0-84, where lower scores are

indicative of better health related quality of life. The GHQ was completed at baseline, at

home after 2 weeks (midpoint) and at the 1-month post-treatment assessment.

6.6.3.2 Chalder Fatigue Scale

The Chalder Fatigue Scale (Chalder, Berelowitz et al., 1993) is a widely used scale

designed to measure the severity of fatigue. The 14-item scale measures both physical

and mental fatigue on a 4 point scale ranging from ‘better than usual’ to ‘much worse

than usual’. \ The Fatigue Scale has an internal consistency reliability coefficient

(Cronbach's alpha) of .845 for the physical symptoms scale and .821 for the mental

symptoms scale (Chalder, Berelowitz et al., 1993). The outcome for this measure will

be total fatigue rating. The Chalder Fatigue Scale was completed at baseline and at the

1-month post-treatment assessment.

6.6.4 Cardiovascular Measures

Non-invasive assessment of peripheral and central blood pressure and pulse wave

reflections were assessed in order to examine the effect of MVM supplementation on

cardiovascular health. These measurements were recorded using the SphygmoCor

XCEL device (AtCor, Sydney Australia). This device adheres to the necessary

Australian safety standards and is commonly used to assess and manage cardiovascular

health.

6.6.4.1 Peripheral Blood Pressure and Heart Rate Peripheral blood pressure was recorded using the SphygmoCor XCEL device. After a

short rest period, an appropriately sized cuff was placed on the participant’s non-

dominant arm. The SphygmoCor device automatically records three successive

measurements, resulting in an average peripheral blood pressure recording.

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6.6.4.2 Arterial Stiffness and Central Blood Pressure Once the peripheral blood pressure recordings have been calculated, the SphygmoCor

XCEL inflates and the aortic pressure waveform is derived from the radial artery. From

this waveform, indices of cardiovascular health including aortic augmentation pressure

and aortic augmentation index are calculated. The indices of aortic pressure and wave

reflection provide indirect estimates of arterial stiffness. Aortic augmentation index

indirectly measures systemic arterial stiffness. Arterial stiffness has been associated

with cognitive decline (Hanon, Haulon et al., 2005), cardiovascular disease (Mattace-

Raso, van der Cammen et al., 2006) and mood disorder in the elderly (Tiemeier, 2003;

Tiemeier, van Dijck et al., 2004; Yeragani, Tancer et al., 2006).

6.7 Procedures

Participant attended two study visits at the Centre for Human Psychopharmacology at

Swinburne University. A mobile phone device was given to participants at the baseline

session, and was used to record mood, energy levels and cognitive performance on 8

additional occasions over the course of the supplementation period (data not reported in

this thesis).

After completing the baseline measures at the first study visit, participants were

randomly assigned to receive the MVM treatment or placebo, and were given one

supplement with a standardised snack. The snack was 1-2 slices of toast with a choice

of either peanut butter or vegemite. The acute testing session was conducted 1-hour

after the supplement was taken. The first testing session included the following:

1. Screening period:

• Obtain written informed consent


• Obtain demographic information

• Obtain basic medical history and review of concomitant medications

• Obtain MMSE and NART-R scores

2. Baseline session:

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• Completion of Computerised Cognitive tasks (results not presented in this

thesis)

• Completion of mobile phone task (only the mood data is reported)


• Treatment administered to participant

3. Acute (1-hour post-dose) session:



thesis)

• Completion of mobile phone tasks (only the mood data is reported)

• Instructions for the 4-week supplementation period, mid-point GHQ, and mobile

phone tasks.

During the 4-week supplementation period, participants were required to take the

supplements daily, with breakfast. The mobile phone tasks were completed twice per

week, at different times of the day, to report on their mood, and perform the cognitive

tasks. The GHQ was completed at home, approximately midway (2 weeks) through the

supplementation period. Participants were instructed to abstain for the study treatment

on the day of post-treatment testing. The 4-week visit included the following:

4. 4-week post-treatment session:


• Review of Adverse events (if applicable)

• Review of medical history and concomitant medications


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thesis)

• Completion of mobile phone tasks (only the mood data is reported)


6.8 Statistical analysis

IBM SPSS, version 22.0 (IBM Corp., 2013), was used to analyse all mood, stress and

health data. Data was screened for outliers and out of range values. Data that was more

than 3 standard deviations from the mean were classified as outliers and removed from

subsequent analyses. The assumption of normality was assessed with the Shapiro-

Wilks statistic and via visual examination of histograms. Positively skewed data was

transformed with logX transformations. Chronic mood data was assessed by

2(treatment: MVM, placebo) x 2(time: baseline, post-treatment) mixed design analysis

of variance (ANOVA) models, except for the GHQ measure where an additional time

point was added to account for the at-home assessment. Where there were violations of

ANOVA assumptions change from baseline scores were calculated, and univariate

AVOVA was used to assess differences between the groups.

Acute data was assessed with 2(treatment: MVM, placebo) x 2 (time: pre dose

(baseline), post dose) x 2 (task: pre task performance, post task performance). Where a

significant treatment x time interaction was identified, post hoc t-tests were used to

assess the differences between the groups on the baseline and post treatment measures.

The significance level was set at p<0.05 for analysis of the main chronic (GHQ) and

acute (DASS) outcomes. A more conservative criterion was set for the exploratory aims

of p<.01.

6.9 Results

6.9.1 Participant demographics

73 of the 76 participants enrolled in the study, completed the trial. Of the participants

that did not complete the trial, one participant required surgery during the trial period,

one withdrew due to family commitments and the other experienced mild side effects of

the treatment, so was advised to discontinue treatment. Baseline participant

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demographics are shown in Table 6-3 below. Independent samples t-tests indicated that

the groups did not differ in terms of age, MMSE score, or trait anxiety scores at

baseline. However, there was a significant difference between the groups on NART-IQ

scores and years of education, with the MVM group having significantly higher IQ

(t=2.40, p=.019) and more years of education (t=2.19, p=.032) than the placebo group.

Additional correlations revealed that IQ and education were not significantly related to

any of the mood measures. Additionally, there were no significant differences between

the groups on measures of height, weight or body mass index.

Table 6-3 - Baseline multivitamin and placebo group demographics and morphometrics

Demographic Treatment N M SD Range Age Multivitamin 39 64.38 6.34 53-75 Placebo 37 62.81 6.35 50-74 NART- R IQ Multivitamin 38 119.37 5.33 103-126 Placebo 37 115.76 7.56 90-127 Years Education Multivitamin 39 17.03 3.37 11-26 Placebo 37 15.35 3.30 7-22 MMSE Multivitamin 39 29.33 0.70 28-30 Placebo 37 29.41 0.93 26-30 STAI-T Multivitamin 39 32.54 8.54 20-51 Placebo 37 23.41 10.92 20-51 Height Multivitamin 37 163.82 6.63 150-178 Placebo 37 163.32 6.45 150-173 Weight Multivitamin 37 65.59 10.29 47-90 Placebo 37 70.11 13.88 44-94 BMI Multivitamin 3 24.43 3.53 18.4-31.4 Placebo 37 26.27 5.05 17.1-37.9 MMSE= Mini-Mental State Examination; NART- R IQ = National Adult Reading Test Revised Predicted IQ; STAI-T= State Trait Anxiety Inventory-Trait version; BMI= Body Mass Index

6.9.1.1 Concurrent medications

In the current study, 43 participants were taking concurrent medication during the study

period. The most common forms of medications were for the treatment of cardiac

related issues (N=23) and arthritis (N=7). Those that were taking vitamin or herbal

supplements were asked to stop the supplements for 30 days prior to the first session,

and for the duration of the trial period.

6.9.1.2 Compliance

Compliance for the study was good. Participants were asked to return all unused

treatments to be counted in order to assess compliance. Compliance was calculated by

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comparing the number of returned treatments to the number expected. Compliance

ranged from 89% to 108%. Mean compliance was 99%.

6.9.1.3 Treatment side effects

One participant experienced adverse side effects while on the MVM treatment. The

participant reported skin tingling, hot flushes and dizziness. The participant was

advised to discontinue with the treatment and at follow-up a week later all symptoms

had disappeared. This was documented as an Adverse Event (AE). Consultation with

the Centre for Human Psychopharmacology Research Nurse determined that the AE

was not classified as a Serious Adverse Event.

6.9.2 Chronic Treatment effects

6.9.2.1 Mood Results

A series of independent samples t-tests were conducted on the data in order to determine

any differences between the treatment groups at baseline. Means, standard deviations

and interaction values for the baseline and post treatment chronic mood assessments are

shown in Table 6-4 below. Analysis did not reveal any significant differences between

the groups.

Assessment of the primary outcome, the effect of MVM on mood, as measured by the

GHQ total score did not reveal any significant time x treatment effects. No significant

time x treatment interactions observed on the remaining subscales of the GHQ, Chalder

Fatigue Scale, HADS scale or the PSS.

Regardless of treatment group, significant reductions over time were observed on a

number of measures. Significant time effects were observed on the following scales:

the GHQ-28 total score (F(2,130) = 3.66, p = .029, partial ɳ2= .05), GHQ social

dysfunction subscale (F(2,132) = 7.40, p = .001, partial ɳ2= .10), Chalder fatigue total

score (F(1,71) = 17.10, p < .001, partial ɳ2= .19), Chalder mental fatigue (F(1,71) =

18.95, p < .001, partial ɳ2= .21), Chalder physical fatigue (F(1,71) = 9.99, p = .002,

partial ɳ2= .13), and HADS depression score (F(1,70) = 18.22, p = .002, partial ɳ2=

.21).

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Table 6-4. Means,Standard Deviations and Interaction Values for the Chronic Mood Measurements

Measure Group Baseline Midpoint Post-Treatment Interaction values

N M SD M SD M SD F p General Health Questionnaire Total Multivitamin 35 15.05 6.65 14.31 5.86 14.47 5.48 1.236 .294 Placebo 32 14.68 6.03 12.41 5.03 12.09 4.33 Somatic Multivitamin 35 3.60 2.76 4.03 3.22 4.29 3.04 3.520 .032 Placebo 33 4.33 3.01 3.64 3.20 3.21 2.38 Anxiety Multivitamin 35 3.57 2.76 3.42 2.52 3.20 2.58 .224 .800 Placebo 33 3.48 2.58 2.97 2.56 3.00 2.52 Social Dysfunction Multivitamin 35 6.83 1.67 6.23 1.68 6.51 1.40 .531 .589 Placebo 33 6.82 1.89 5.89 1.58 6.12 1.52 Depression Multivitamin 35 1.06 2.09 0.63 1.33 0.46 1.12 1.590 .208 Placebo 33 0.61 1.52 0.52 1.56 0.45 1.50 Chalder Fatigue Scale Total Multivitamin 37 16.00 4.33 13.35 3.22 1.480 .228 Placebo 36 14.47 3.75 13.03 3.20 Physical Multivitamin 37 8.83 2.63 7.47 1.66 .657 .420 Placebo 36 8.11 2.61 7.31 2.19 Mental Multivitamin 37 7.05 2.17 5.62 1.40 2.781 .100 Placebo 36 6.36 1.53 5.72 1.39 Hospital Anxiety and Depression Scale Anxiety Multivitamin 37 4.46 2.30 3.81 2.08 .537 .466 Placebo 36 4.33 2.69 4.03 3.15 Depression Multivitamin 37 2.16 2.10 1.35 1.57 .001 .977 Placebo 36 2.23 1.75 1.42 2.00 Perceived Stress Scale Multivitamin 37 19.05 3.21 18.70 1.90 .201 .655

Placebo 35 18.40 2.08 17.74 2.00 N= represents participants included in the pre to post treatment analysis * = significant time x treatment interaction (p<.05) Interaction values represent the time x treatment analysis.

6.9.2.2 Cardiovascular results

A series of independent samples t-tests were conducted on the data to determine if there

were any differences between the treatment groups at baseline. Analysis revealed a

significant difference between the treatment groups on brachial systolic pressure

(t(73)=-2.413, p=.018), and brachial diastolic pressure (t(73)=-2.843, p=.006) at the

baseline visit. Additionally, baseline differences were found on measures of central

systolic pressure (t(73)=-2.229, p=.029) and central diastolic blood pressure (t(73)=-

3.032, p=.003), as well as mean augmented pressure (t(73)=-2.552, p=.013). There

were no other baseline differences on any of the cardiovascular outcomes.

Means and standard deviations, as well as the interaction values for the baseline and

post treatment cardiovascular assessments are shown in Table 6-5. Results revealed no

significant effects of the treatment on any of the cardiovascular parameters.

Furthermore, analysis did not reveal any significant time effects.

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Table 6-5 - Means and Standard Deviations and Interaction Values for Cardiovascular

Parameters pre and post treatment

Cardiovascular measure

Group Baseline Post Treatment Interaction values

N M SD M SD F p Peripheral Measures Brachial Systolic pressure

Multivitamin 36 119.72 14.61 120.64 15.98 .642 .426

Placebo 36 128.64 14.13 127.61 14.01 Brachial Diastolic pressure

Multivitamin 36 69.97 9.60 69.75 8.94 .430 .514

Placebo 36 77.81 11.05 76.58 9.45 Brachial pulse pressure Multivitamin 36 49.61 9.85 50.72 11.20 .551 .461 Placebo 36 51.42 8.45 51.06 11.45 Central measures Central systolic pressure

Multivitamin 36 108.61 12.22 109.06 13.61 .222 .639

Placebo 36 116.36 14.36 115.75 12.83 Central diastolic pressure

Multivitamin 36 70.06 8.64 69.83 8.77 .451 .504

Placebo 36 78.17 11.84 76.83 9.81 Mean arterial pressure Multivitamin 36 85.22 9.84 85.28 10.44 .158 .692 Placebo 36 92.94 12.84 92.31 10.56 Central pulse pressure Multivitamin 36 38.47 8.04 39.33 9.12 .329 .568 Placebo 36 39.03 9.07 38.89 9.93 Augmentation pressure Multivitamin 35 11.74 5.16 12.37 6.06 .882 .775 Placebo 34 11.44 6.33 11.71 7.18 Augmentation Index Multivitamin 35 0.30 0.11 0.30 0.11 .014 .905 Placebo 35 0.30 0.13 0.30 0.14


6.9.3 Acute effects of Treatment on Mood Independent samples t-tests did not reveal any significant differences between the

groups on any of the acute mood measures at baseline. The means and standard

deviations and the interaction values for the acute mood scales are displayed in Table

6-6. In order to correct for a positive skew, a log transformation was applied to the

DASS total score, and the depression and anxiety subscales.

A significant time x treatment interaction was found for the DASS total scale (F(1,

72)=5.54, p=.021, partial η2=.07). Post hoc t-tests revealed a significant reduction in

DASS scores for the MVM group (p=.001), but not the placebo group (p=.373). A

significant time x treatment effect was discovered on the DASS stress subscale

(F(1,72)=6.97, p=.01, partial η2=.09). Post hoc t-tests indicated a significant revealed a

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significant reduction in DASS stress scores in the MVM group (p=.001), but not the

placebo group (p=.812).

Analysis of the Visual Analogue Scales indicated a trend towards a time x treatment

interaction on the Bond-Lader calmness subscale (F(1,71)=5.37, p=.023, partial

η2=.07). Post hoc t-tests indicated an almost significant increase in calmness for the

MVM group only (p=.024). A significant time x treatment interaction was observed on

the stress VAS (F(1,71)=7.44, p=.008, partial η2=.10). Post hoc t-tests indicated a trend

towards a reduction in stress scores only in the MVM group (p=.028). A trend towards

a time x treatment interaction was identified on the VAS anxiety score (F(1,71)=4.38,

p=.04, partial η2=.06). Post hoc t-tests indicated that the reduction in anxiety was not

significant in either group.

No significant time x treatment effects were observed on the STAI-State measures.

Table 6-6. Means, Standard Deviations and Interaction Values for Acute Mood Assessments

Measure Group N Baseline Post Dose Interaction Values

M SD M SD F p Depression Anxiety and Stress Scale Total (pre battery) Multivitamin 38 10.37 12.16 6.74 9.85 5.54 .021* Placebo 36 7.56 9.94 6.44 8.53 Total (post battery) Multivitamin 38 10.05 10.65 6.68 8.81 Placebo 36 8.28 9.98 7.44 10.65 Depression (pre battery) Multivitamin 38 2.42 4.16 1.58 3.26 2.75 .102 Placebo 36 1.61 3.47 1.22 3.07 Depression (post battery) Multivitamin 38 2.00 3.74 1.11 2.70 Placebo 36 1.72 3.48 1.61 4.38 Anxiety (pre battery) Multivitamin 38 2.11 3.54 1.37 2.28 0.26 .609 Placebo 36 1.50 2.68 1.33 1.85 Anxiety (post battery) Multivitamin 38 1.79 2.36 1.37 2.55 Placebo 36 1.83 2.92 1.28 2.25 Stress (pre battery) Multivitamin 38 5.84 5.81 3.79 5.26 6.97 .010* Placebo 36 4.44 4.99 3.89 5.30 Stress (post battery) Multivitamin 38 6.26 5.92 4.21 5.09 Placebo 36 4.72 4.97 4.56 5.55 Visual Analogue Scales Alert (pre battery) Multivitamin 37 68.09 17.98 68.23 18.50 1.05 .309 Placebo 36 72.45 15.30 71.51 17.44 Alert (post battery) Multivitamin 37 57.67 17.99 56.50 18.08 Placebo 36 61.00 15.62 56.59 15.94 Content (Pre battery) Multivitamin 37 77.09 17.28 78.78 15.13 2.56 .115 Placebo 36 83.04 14.49 83.51 16.32 Content (post battery) Multivitamin 37 64.97 17.33 66.01 16.10 Placebo 36 72.49 16.39 69.20 15.84

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Table 6-6 Cont. Means and Standard deviations for the acute mood assessments

Calm (pre battery) Multivitamin 37 66.49 21.69 74.27 17.40 5.37 .023* Placebo 36 75.90 17.48 75.57 23.26 Calm (post battery) Multivitamin 37 55.62 19.15 59.68 19.15 Placebo 36 63.50 20.86 63.17 18.24 Stress (pre battery) Multivitamin 37 23.95 24.41 15.43 17.94 7.44 .008* Placebo 36 14.28 17.73 15.08 20.31 Stress (post battery) Multivitamin 37 43.68 23.67 35.89 17.93 Placebo 36 34.22 23.84 36.11 23.56 Anxiety (pre battery) Multivitamin 37 18.16 22.05 14.11 14.48 4.38 .040* Placebo 36 13.94 19.11 15.92 22.27 Anxiety (post battery) Multivitamin 37 31.46 22.13 29.41 15.95 Placebo 36 29.44 20.93 33.22 23.26 Concentration (pre battery) Multivitamin 37 65.68 29.05 59.76 26.05 .045 .833 Placebo 36 63.89 26.75 60.81 27.09 Concentration (post battery) Multivitamin 37 54.70 25.56 53.62 21.15 Placebo 36 56.89 20.89 54.89 19.93 Mental fatigue (pre battery) Multivitamin 37 23.08 23.97 30.32 24.32 .002 .966 Placebo 36 22.42 22.00 27.08 23.63 Mental fatigue (post battery) Multivitamin 37 43.35 23.69 48.32 20.43 Placebo 36 41.89 21.02 49.11 20.45 Physical fatigue (pre battery) Multivitamin 37 21.27 23.27 27.00 23.36 .899 .346 Placebo 36 16.72 18.92 22.56 20.22 Physical fatigue (post battery) Multivitamin 37 36.43 22.74 35.46 20.75

Placebo 36 27.67 16.76 32.00 19.29

State Trait Anxiety Inventory – State Version

STAI (pre battery) Multivitamin 39 33.23 10.81 30.28 8.03 1.39 .242

Placebo 36 30.47 8.96 28.67 9.52

STAI (post battery) Multivitamin 39 35.51 11.40 32.64 9.37

Placebo 36 32.56 11.98 31.39 10.56

N= represents participants included in the pre to post treatment analysis * = significant time x treatment interaction (p<.05) Interaction values represent the time x treatment analysis.

Significant time effects were observed on a number of the measures. The DASS total

(F(1,72)=13.68, p<.000, partial η2=.16) reduced over time. Scores on the DASS

depression subscale (F(1,72)=10.19, p=.002, partial η2=.12), DASS anxiety

(F(1,72)=5.55, p=.021, partial η2=.07), and DASS stress subscales (F(1,72)=14.20,

p>.000, partial η2=.17) all reduced over time.

Reductions were observed on the STAI-S (F(1,73)=13.27, p=.001, partial η2=.15)

regardless of treatment group. Ratings of VAS mental fatigue (F(1,71)=9.80, p=.003,

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partial η2=.12) were reduced over time, and an almost significant reduction on the

physical fatigue scale (F(1,71)=6.84, p=.011, partial η2=.09) were observed.

Additional analysis revealed that the cognitive battery significantly influenced mood

ratings. Significant task effects were observed on a number of the VAS measures,

indicating that irrespective of treatment, completing the cognitive battery resulted in a

significant reduction in alertness (F(1,71)=104.01, p<.000, partial η2=.59), calmness

(F(1,71)=80.03, p<.000, partial η2=.53), contentedness (F(1,71)=117.90, p<.000,

partial η2=.62), and concentration (F(1,71)=9.85, p=.002, partial η2=.12). Significantly

higher reports of stress (F(1,71)=111.90, p<.000, partial η2=.61), anxiety

(F(1,71)=7.44, p=.008, partial η2=.10), increased mental fatigue (F(1,71)=81.56,

p<.000, partial η2=.54) and physical fatigue (F(1,71)=35.59, p<.000, partial η2=.33)

after completing the battery.

6.10 Discussion

The current study investigated the acute (single dose) and chronic (4-weeks) effects of

multivitamin and mineral supplementation on mood and cardiovascular function in a

group of healthy older women. The findings from this study did not reveal any chronic

benefits of MVM supplementation on mood or cardiovascular function. The results

from the current study are consistent with the findings of the previous trial reported in

the current thesis (See Chapter 5), which did not find any benefits to mood after chronic

MVM supplementation. The current findings are at odds with previous reports in the

literature that have demonstrated that 4 weeks of MVM supplementation is effective in

improving mood in healthy younger adults (Carroll, Ring et al., 2000; Kennedy, Veasey

et al., 2010).

Despite the lack of chronic benefits of the MVM preparation, a number of acute benefits

to mood were observed in the current study. Specifically, when assessed 1-2 hours

post-dose, a single MVM dose was effective in improving overall mood, as measured

by the DASS, as well as decreasing rating of stress and increasing calmness as

measured by visual analogue scales.

6.10.1 Chronic effects In the current study, the primary outcome, that MVM supplementation would improve

mood as measured by the GHQ, was not supported. The current results are inconsistent

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with previous research that has found improvements in mood after four weeks of MVM

supplementation in younger adults (Carroll, Ring et al., 2000; Kennedy, Veasey et al.,

2010). The results are also inconsistent with previous research from our lab that found

that a MVM, similar to the formulation used in the current study, demonstrated mood

improvements after 8 weeks of supplementation in older men (Harris, Kirk et al., 2011).

The mood measures used in the current study were the same as those used in our

previous work, and the improvements observed on these scales suggest that the

measures were suitable to identify changes due to supplementation. On the other hand,

the results of the current study are consistent with the findings from the previous

clinical trial reported in this thesis (Chapter 5). The trial reported in Chapter 5 did not

find any benefit of chronic MVM supplementation on mood, using similar mood

ratings.

Past investigations that have found beneficial effects of MVM supplementation in the

elderly have found these benefits in groups that can be defined as ‘at risk’. For

example, Gariballa and Forster (2007b) demonstrated improvements in depressive

symptoms after supplementing with a liquid MVM drink in hospitalised, acutely ill,

elderly patients. In a subsequent paper published by the same authors, they found that

the MVM also improved quality of life, measured on the SF-36 in the same cohort of

participants (Gariballa and Forster, 2007a). Gosney et al. (2008) assessed the effects of

MVMs in frail nursing home residents, and observed benefits of MVM supplementation

on mood in a subgroup of participants who had higher levels of depression at baseline.

Additionally, our previous report that demonstrated reductions in negative mood was

conducted in a group of men with a sedentary lifestyle, and at risk of cognitive decline

(Harris, Kirk et al., 2011).

Consistent with the previous trial reported in Chapter 5, participants in the current study

were asked not to take their daily supplement the morning of their follow-up visit at 4-

weeks. This is also consistent with the design of our previous work (Pipingas, Camfield

et al., 2013), and was implemented in order to account for any potential acute effects of

the MVM. In the majority of previous multivitamin and mineral RCTs reported in the

literature, participants were not asked to abstain from their supplements on the day of

their follow-up session, or this was not specifically reported. The results of the current

study that required participants to abstain from taking their daily MVM on the morning

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of return 4-week testing suggests that past researchers may have inadvertently observed

a combination of the acute actions, and chronic benefits of the MVM treatments. The

lack of chronic benefits of the MVM treatment in the current study could also be

attributed to a ‘withdrawal’ effect. The participants in the MVM group may have

adapted to consuming the MVM formulation on a daily basis, and receiving the

nutritional benefits. A sudden discontinuation of the treatment may have been

detrimental to mood both in general, and in the buffering demands of laboratory testing.

The following section will provide evidence to partially support this claim.

6.10.2 Acute effects The secondary outcome, that multivitamin and mineral supplementation would acutely

influence mood was supported in the current study. Benefits to mood were observed 1-

2 hours post dose, suggesting that MVMs have the potential to exert effects on aspects

of mood in a very short period of time. Specifically, after taking a single MVM, overall

ratings on a modified version of the DASS were significantly improved. This appeared

to be largely due to significant improvements in the rating of stress levels on the DASS.

These results are further strengthened by decreased ratings of stress and increases in

calmness ratings on the visual analogue scales. No effects on other aspects of mood

were observed, including depression and fatigue ratings. To our knowledge, this is the

first study to investigate the acute effects of MVMs in an older group of individuals.

In the current study, ratings of stress appeared to benefit most from MVM

supplementation. Specifically, two stress measures, and a measure of anxiety and

calmness all showed improvement 1 to 2 hours post MVM dose. A recent meta-

analysis demonstrated that stress is the mood facet that has recently been shown to

demonstrate the greatest improvements after chronic MVM supplementation (Long and

Benton, 2013). Furthermore, MVMs containing high-dose B vitamins have been

shown to improve ratings of stress in a number of investigations of young adults

(Carroll, Ring et al., 2000; Schlebusch, Bosch et al., 2000; Kennedy, Veasey et al.,

2010; Stough, Scholey et al., 2011).

As previously described, folate, B12 and B6 have an important role in the synthesis of

the neurotransmitters serotonin, noradrenaline and dopamine (Huskisson, Maggini et al.,

2007a), and in the remethylation of homocysteine to SAMe (Bottiglieri, 2005). Due to

this, the beneficial effects of MVMs on mood are often associated with the B vitamin

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content of the preparations. As previously discussed, B12 and folate deficiency is often

associated with increased depression (Alpert, Mischoulon et al., 2000; Baldewicz,

Goodkin et al., 2000; Tolmunen, Voutilainen et al., 2003), and folate has been shown to

aid in the reduction of clinical depression (Bottiglieri, 2005) and reduce depressive

symptoms in non-clinical samples (Malouf, Grimley Evans et al., 2003).

The mechanism by which MVMs exert acute effects on mood is previously unexplored.

Kennedy et al. (2008) propose improvements in mitochondrial function and vascular

endothelial function as an underlying mechanism by which MVMs may exert acute

cognitive benefits. These mechanisms may also serve to improve mood through

increased availability of metabolites in the brain through improved blood flow and

vasodilation (Scholey, Harper et al., 2001). Given that blood biomarkers were not

collected in the current study, potential mechanisms through which acute benefits were

observed cannot be determined.

The acute benefits observed in the current study provide some support for the

‘withdrawal’ effect that may have been observed in previous investigations. In the

current study, acute benefits on mood were observed 1-2 hours post dose. However, at

the follow-up session, where participants were instructed not to take their daily MVM

dose, mood benefits were not observed. It could be that participants, who had adapted

to receiving the daily benefits of the MVM, suddenly stopped taking the supplement for

the return visit, which may have adversely impacted mood, both in general and in the

buffering of the demands of task performance. Future research would benefit from

adding an additional acute session at follow-up to further test this hypothesis. An

alternative explanation is, that in healthy older participants, there may not be a chronic

effect of MVM supplementation after 4-weeks. Rather the benefits of MVMs are seen

as a result of the acute actions of the supplements in the hours following ingestion.

6.10.3 Cardiovascular function There were no significant effects of MVM treatment on cardiovascular parameters

observed in the current investigation. These findings are consistent with those of the

first study reported in this thesis that also found no effect of MVM supplementation on

cardiovascular parameters, after 16 weeks.

Very little research has investigated the effects of MVM combinations on

cardiovascular health. The parameters studied in the current investigation have

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previously been shown to benefit from chronic supplementation with Vitamin C and

Vitamin E, although not all have found benefits.

Wilkinson et al. (1999) studied the effect of acute administration of 2g of vitamin C on

arterial stiffness in healthy males. They found that vitamin C significantly reduced

augmentation index after acute administration. However, Kelly et al. (2008) failed to

find improvements on augmentation index after acute, high-dose (2g) vitamin C

administration in their sample of healthy volunteers. However, in the current study,

arterial stiffness was not assessed after acute administration of the supplement.

Augmentation index has been modified by chronic vitamin C supplementation in

previous investigations. Briefly, 4 weeks of daily vitamin C (500mg) successfully

reduced augmentation index in patients with type 2 diabetes (Mullan, Young et al.,

2002). Furthermore, combined vitamin C and E supplementation in patients with

essential hypertension was marginally reduced after 8 weeks (Plantinga, Ghiadoni et al.,

2007). Lastly, vitamin E, supplemented for 2 months resulted in improvements in

augmentation index in healthy male participants (Rasool, Rahman et al., 2008).

There is limited evidence for the effects of B vitamins on arterial stiffness. Koyama

(2010) found that augmentation index was more effectively reduced when combining

folate and meythlcobalamin than when folate was given in isolation to patients on

haemodialysis. The Atherosclerosis and Folic Acid Supplementation Trial (ASFAST)

did not find any significant effect of folic acid supplementation on indices of arterial

stiffness in chronic renal failure patients (Zoungas, McGrath et al., 2006), suggesting

that folate alone is not able to improve arterial stiffness.

Compared to other studies, differences in group demographics and health could

potentially explain the lack of positive results in the current study. Like the study

describe in the previous chapter, the study sample investigated in the current trial were

healthy older individuals rather than a patient group. Reports of beneficial effects of

vitamin C and folate previously described in the literature were all found in patient

groups. Additionally, the vitamin E benefits reported by Rasool et al (2008) were found

by using a highly bioavailable form of vitamin E that was different from the vitamin E

contained in the supplement in the current study. Moreover, the supplements used in

the current study only contained a small amount of vitamins C and E (200mg and 20-

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25mg respectively), which may have not been great enough to see any beneficial effects

on arterial stiffness indices. Additionally, like in the previous study in chapter 5, the

arterial stiffness observed in the current study is likely age-related, rather than due to

functional changes, and therefore less amenable to improvement with supplementation

(Pase, Grima et al., 2011). Another issue worthy of consideration was the significant

differences in blood pressure between the treatment groups at baseline. The MVM

group had significantly lower systolic blood pressure (9mmHg) than the placebo group.

Importantly, even though the MVM group was healthier, on the basis of the

cardiovascular parameters, they still showed acute mood effects after supplementation.

6.10.4 Limitations and Future directions A limitation of the current study was that the chronic effects of the MVM were assessed

after only 4 weeks. While there has been a small amount of studies that have

investigated MVMs in younger groups on a similar time scale (Carroll, Ring et al.,

2000; Schlebusch, Bosch et al., 2000; Kennedy, Veasey et al., 2010; Kennedy, Veasey

et al., 2011), studies conducted in older groups have investigated chronic effects with

greater supplementation periods ranging from 6 weeks to 24 weeks. The only other

study conducted in a healthy older sample used a 24 week chronic intervention period,

and resulted in null mood effects (Cockle, Haller et al., 2000), suggesting that longer

intervention periods may be required in order to observe any chronic effects to mood in

healthy older groups. These results suggest that the mechanism of action for chronic

mood improvements due to MVM supplementation is different to the mechanism

influencing acute mood. Slow changes in nutritional status over time will result in

increased neurotransmitter production, reductions in homocysteine and improved

cardiovascular function (see Chapter 3), and in turn lead to improvements in mood.

Whereas it seems that the acute mood effects may due to a pharmacological effect of the

MVM supplements on the brain.

The absence of blood biochemical markers in the current study is another limitation.

These markers of vitamin status and other biochemical markers of health would have

been able to provide more of an insight into the potential mechanisms through which

the MVM exerted acute benefits to mood, and could help elucidate which components

of the MVM contributed to mood improvements. Furthermore, given the associations

between B vitamins and mild psychiatric symptoms (Long and Benton, 2013), it would

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have been interesting to ascertain how effective the MVM was in increasing B vitamin

status over the 4-week supplementation period.

Another limitation of the current study was that acute assessments were not conducted

at the return visit. The addition of this extra session would have provided information

regarding a potential ‘withdrawal’ effect of the MVM. If acute benefits were seen after

providing participants with their daily MVM, it could be assumed that the absence of

chronic effects was due to abstaining from the daily dose on the morning of the session.

Additionally, it could be that the majority of benefits previously attributed to MVMs on

mood are due to the acute action of these supplements rather than a cumulative effect in

a healthier sample.

Finally, limiting the sample to female only participant’s means the results may not be

relevant to a male population. However, our previous study in an all-male sample

identified mood benefits after 8 weeks of MVM supplementation using a comparable

supplement, and similar measures of mood (DASS, GHQ and PSS) (Harris, Kirk et al.,

2011). Although, it should be noted, that the sample in our previous study comprised

males at risk of cognitive decline, whereas the current sample were healthy.

Furthermore, our previous investigation did not have an acute assessment; therefore

replication of the current investigation is warranted in order to determine if the same

acute benefits of MVMs would be present in a male population.

6.10.5 Summary and Conclusion In summary, the current study investigated the acute and chronic benefits of 4-weeks

MVM supplementation in a group of healthy older women. The results showed that

while chronic 1-month supplementation did not reveal any effects on mood, a single

MVM dose resulted in mood improvements 1-2 hours post ingestion.

Specifically, acute administration of a single MVM dose effectively enhanced general

mood, largely through reductions in stress ratings, suggesting acute actions of MVMs.

While the mechanisms through which MVMs exert these benefits could not be

elucidated in the current trial, the findings of this study present a novel avenue of

research. No other RCT has investigated the acute effects of MVM preparations in an

elderly sample.

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209

Chapter 7 General Discussion This thesis presents the results from two separate, double-blind, randomised, placebo-

controlled trials. The primary aim of the thesis was to examine the effects of a

multivitamin and mineral formulation on mood in a group of healthy, older individuals.

Currently, there is a paucity of literature that has investigated the effects of MVM

supplementation in the elderly. Not including the trials reported in the current thesis,

only one other RCT has investigated MVM supplementation on mood in a healthy

sample of participants. Furthermore, to date, no other study has investigated the acute

actions of MVMs on mood in an elderly group. The studies contained in Chapters 5 and

6 aimed to address these gaps in the available literature.

The first trial (Chapter 5) investigated the chronic effects of a multivitamin, mineral and

herbal supplement on mood and cardiovascular function in healthy older individuals.

The second trial (Chapter 6) examined both the acute and chronic effects of MVM

supplementation on mood and cardiovascular function in healthy older women.

This chapter will begin with a summary of the key findings from each of the studies

presented in the current thesis. The section following (7.2) will compare and contrast

the main findings of the two trials in order to explain the overall effects of MVM

supplementation in an older group. Section 7.3 discusses the difficulties associated with

MVM research, and considers the topic of dosage and duration of MVM

supplementation. The physiological benefits of MVM supplementation are discussed in

section 7.4, while the following section (7.5) describes the benefit verses risk of

supplements. The limitations of the current thesis as well as recommendations for

future research are contained in section 7.6. The chapter concludes with a brief

summary and conclusion in section 7.7.

7.1 Summary of Key findings

7.1.1 Chronic multivitamin supplementation: effects on mood in older individuals The overall aim of the study presented in Chapter 5 was to examine the chronic effects

of 16-weeks MVM supplementation in healthy older adults. The primary outcome of

this investigation was improvements in overall mood, measured by the Depression,

Anxiety and Stress Scale (DASS). The secondary outcome was to examine the

potential mechanisms by which MVMs exert their benefits on mood. This was assessed

by measures of cardiovascular function, including augmentation index, augmentation

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pressure and brachial blood pressure, as well as blood biochemical markers of vitamins,

inflammation and general health parameters. The study also explored the possible

effect that MVMs have on individuals’ reaction to stress, by subjectively recording

stress levels before and after an effortful multitasking computerised task.

The results of the trial did not reveal any benefits of chronic MVM supplementation on

mood. A significant improvement on both subscales of the Hospital Depression and

Anxiety Scale (HADS) was observed in the placebo group. Despite the lack of mood

findings in the current investigation, a number of positive benefits to blood biomarkers

were observed. For example, MVM supplementation resulted in significant increases in

vitamin B12, B6 and folate, and a significant reduction in homocysteine. An exploratory

correlational analysis indicated that increases in folate levels were associated with a

reduction in mental fatigue. Furthermore, MVM supplementation did not improve

measures of cardiovascular health, such as arterial stiffness or blood pressure.

Similarly, the MVM did not influence responses to a laboratory stressor.

7.1.2 Acute and Chronic Multivitamin Supplementation: Effects on Mood in Older Women

The trial in Chapter 6 aimed to investigate the acute and chronic effects of 4-weeks

supplementation with a multivitamin, mineral and herbal supplement in a group of older

women. The primary outcome for this experiment was the chronic effect of the MVM

supplement on mood as measured by the General Health Questionnaire (GHQ). The

secondary outcome was the acute (single-dose) benefits of MVM supplementation on

mood. The main outcome for acute mood was measured using a modified version of

the DASS. Cardiovascular function (augmentation index, augmentation pressure and

brachial blood pressure) was also assessed in order to provide information about

potential mechanisms of action through which MVMs may exert benefits on mood.

The results of this study did not reveal any significant effects on mood following

chronic 4-weeks MVM supplementation. Furthermore, no chronic-related

cardiovascular benefits were observed. With regards to the acute effects of the MVM, a

significant reduction on the DASS was observed for the MVM group. This result

appeared to be primarily driven by a significant reduction on the stress subscale of the

DASS in the MVM group. Additionally, reductions on the stress visual analogue scale

(VAS), and improvements on the anxiety and calmness VAS were observed.

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7.2 Acute verses Chronic Multivitamin Supplementation

This discussion will compare and contrast the findings from the two experimental

chapters contained in this thesis in order to provide an explanation about the overall

effects of MVM supplementation on mood in older adults. The supplements used in the

two trials were similar. The Women’s formulas were identical; however, the Men’s

formula differed slightly in the dosage of some nutrients and herbal constituents.

Furthermore, the age ranges in both experimental groups were similar; both studies

included individuals in good general health, with no mood disturbances or cognitive

impairments. Finally, the study protocols were similar, and a number of mood scales

were used in both experiments to allow comparison across the studies.

Epidemiological research has provided evidence for the role of vitamins and minerals in

the regulation of mood. As discussed in Chapter 3, associations between the B vitamin

(B12, B6 and folate) and mood are often reported in the literature (Bottiglieri, Laundy et

al., 2000; Sachdev, Parslow et al., 2005). Additionally, various minerals have also been

linked to mood modulation, such as zinc (Nowak, Szewczyk et al., 2005). However,

despite these known associations, the evidence from randomised controlled trials

(RCTs) does not consistently report benefits to mood following vitamin and/or mineral

supplementation. The conflicting evidence from MVM trials may be explained by

methodological differences across the trials, differences in supplement formulations and

participant characteristics. The present studies aimed to address the lack of information

regarding the benefits of MVM in healthy, elderly individuals. Additionally, the current

trials utilised measures that have previously been demonstrated as sensitive to

nutritional interventions, as well as using supplements that contained a range of

vitamins, nutrients, minerals and herbs. It should be noted that the addition of the

herbal constituents to the MVM preparations might have contributed to the effects

observed, however this was not directly measured in these studies.

In both studies, the primary outcomes, that mood would be improved by chronic MVM

supplementation, were not supported. The lack of benefit of MVM supplementation on

mood is in contrast to previous reports by our group which found that a daily MVM for

8-weeks improved mood outcomes (Harris, Kirk et al., 2011). The supplements used in

the current investigations were similar to the supplement used in our past research,

whereas the participant group was not. The participants in our previous investigation

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were older males, at risk of cognitive decline. They were slightly older than the

participants in the current investigations, and lived a sedentary lifestyle. Therefore, it

may be that the effects of MVMs are pronounced in more vulnerable groups such as

this.

This premise is supported by evidence from other RCTs in elderly groups. As discussed

in the review in Chapter 4, the majority of the positive benefits of MVMs on mood in

elderly samples have all been reported in ‘at-risk’ groups (Gariballa and Forster, 2007b;

Gosney, Hammond et al., 2008; Harris, Kirk et al., 2011). Specifically, of the four

studies identified in the literature, the three that found benefits on mood were conducted

in vulnerable groups. Gariballa and Forster (2007b), found mood improvements in

acutely ill, hospitalised patients aged over 65 years; Gosney et al. (2008) found

reductions in depressive symptoms in those with higher depressive levels at baseline, in

frail nursing home residents, and as mentioned above, our previous investigation found

mood improvements in sedentary older men, at risk of cognitive decline (Harris, Kirk et

al., 2011). Whereas Cockle et al. (2000) did not report any benefits to mood after

MVM supplementation in a healthy group of older individuals. The evidence from past

research, combined with the results of the current investigations suggests that it is more

difficult to measure changes in mood with nutritional interventions in healthy elderly

group. It could also be that MVMs may not have an effect in healthy older individuals,

although more research is required in order to confirm or negate this notion.

Another potential confounding issue could be the differences in the sensitivity of the

mood measures that were utilised in the past research. While many of the measures that

have been implemented in past research have been validated for use in the general

population (ie. DASS, POMS, HADS), they still measure mood disturbances or

symptoms within these groups. It could be that they are not sensitive enough to detect

subtle changes in mood in a healthy group. In both of the current studies, many

participants scored 0 or 1 on the DASS at the baseline session, leaving very little, or no

room for improvements due to the MVM. In order to measure the more subtle

fluctuations in mood in a healthier sample, a better approach may be to modify visual

analogue scales to record mood over the last few weeks. The traditional visual analogue

scales ask respondents to rate their mood as they are currently experiencing it in that

moment in time.

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A parallel area of investigation is the cognitive effects of MVM supplements. Research

has shown that computerised cognitive batteries such as the Cognitive Demand Battery

(Scholey, French et al., 2009), or the Cognitive Drug Research (CDR) battery (Bracket

Global, UK), may be sensitive enough to detect more subtle changes in cognition due to

supplementation. Furthermore, fluctuations in mood, as measured primarily by visual

analogue scales are often included in these study designs. Similar to the study protocol

reported in Chapter 5, recording mood before and after a cognitively demanding task

may help to determine any protective effects of supplementation on mood. No

protective effects of MVMs were observed in the current studies, however, as

previously mentioned, this may have been confounded by a potential withdrawal from

the study treatment on the morning of laboratory testing.

Multivitamin and mineral supplements are purported to exert benefits on mood via a

number of mechanisms. The reduction of associated risk factors through functional

improvements in a number of health outcomes such as reductions in inflammation,

oxidative stress and improved cardiovascular function may all contribute to mood

modification. The results of the study in Chapter 5 do not support this premise, and

again, it may be that a longer duration of supplementation in a healthy, elderly group is

needed before benefits on oxidative stress and inflammatory markers are observed.

A methodological concern, which may explain the discrepancy between the lack of

chronic effects in the current studies and benefits previously reported in the literature, is

the issue of acute on chronic supplementation. In the majority of previous studies

(expect for Haskell et al. (2010)), participants continued to take their daily MVM on the

morning of repeat testing, meaning that both the acute actions, and chronic benefits of

MVMs were recorded. In contrast, the participants in both studies in the current thesis

were instructed not to take their supplement on the morning of their final testing

session, in order to eliminate potential acute actions of the MVM on mood. This

requirement is consistent across a number of our previous study protocols (Macpherson,

Ellis et al., 2012; Pipingas, Camfield et al., 2013), with the exception of one of our

earlier studies; an 8-week investigation of older, at-risk males (Harris, Kirk et al., 2011).

The acute actions of MVMs on mood, demonstrated in Chapter 6, support the

suggestion that past studies may have in fact been confounded by the acute action of

MVM supplementation due to participants consuming their daily dose on the morning

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of repeat testing. Levels of B vitamins have been shown to peak in the blood within 3

hours after orally consuming a supplement (Bor, Refsum et al., 2003; Dainty, Bullock et

al., 2007; Mönch, Netzel et al., 2010). Therefore, the lack of distinction between the

acute and chronic effects of MVM supplementation in the past literature suggests that

the effects reported may be a combination of acute and chronic benefits.

The lack of positive chronic effects on mood in the current investigations is in direct

contrast to the acute benefits on mood that were observed in the study reported in

chapter 6. The absence of sustained benefits of the MVM on mood in the current trials

could be attributed to a ‘withdrawal’ from the MVM on the morning of their final

testing session. Our group has previously suggested that since the participants in the

MVM group had adapted to consuming a daily MVM, the sudden absence of their daily

supplement may have been detrimental to mood at the follow-up session (Pipingas,

Camfield et al., 2013). The measurements of mood were all taken during the laboratory

testing session requiring participants to concentrate for extended periods of time.

Although the mood measures ask participants to rate their average mood over the course

of a week, it is likely that their current mood, on the morning of repeat testing will have

influenced their reporting. The withdrawal hypothesis is one that has been investigated

with other psychoactive agents, in particular caffeine (Juliano and Griffiths, 2004), but

it is not clear if withdrawal from long-term MVM supplementation would impact

negatively on mood or cognitive performance. This hypothesis has yet to be tested with

regards to multivitamin and mineral supplementation.

Interestingly, stress seemed to be the mood facet that benefited most from the acute

MVM dose. Specifically, the results from Chapter 6 suggest that a single MVM dose

was effective in combating stress and anxiety associated with performance of a

cognitively demanding task. This finding is consistent with a recent meta-analysis that

found that stress was the aspect of mood that was most often modified by chronic MVM

interventions (Long and Benton, 2013). The results of these investigations suggest that

the mood benefits of MVMs often reported in the literature may be a reflection of the

acute actions of the vitamin constituents rather than a more long-term, chronic benefit to

mood.

Taken together, the results of the two RCTs reported in this thesis suggest that chronic

MVM supplementation, up to 16-weeks, does not benefit mood in healthy elderly

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individuals. The results indicate that the findings that have previously been reported in

the literature; both in vulnerable older adults and healthy younger adults, may have been

confounded by the acute influence of MVMs. The acute mood benefits reported in

Chapter 6, in combination with the absence of chronic effects support this hypothesis.

More speculatively is that the current ‘chronic’ approach adopted in the research

designs of the two trials, may be confounded by a withdrawal effect, in that abstaining

from a regular MVM dose on the morning of repeat testing may have negatively

impacted on mood. Future researchers should aim to address these concerns with an

acute on chronic testing session at follow-up. Another approach adopted by our group

(Pipingas, Camfield et al., 2013), and a laboratory in the UK (Kennedy, Veasey et al.,

2011) is the use of mobile phone devices in the home to measure mood and energy over

the course of the day. This allows for the assessment of the cumulative effects of MVM

supplements as a way to get around withdrawal effects as well as the influence of the

laboratory testing session.

7.3 Multivitamin formulations, dosage and duration.

One of the difficulties encountered in MVM research is that there is no established

standard for ingredients or dosages of MVM formulations. The term ‘multivitamin’ and

other similar names, can refer to combinations with widely varied ingredients and

product characteristics (Yetley, 2007). The lack of information regarding formulation

characteristics makes it difficult to compare the results across studies and generalise

results to all marketed products, and important product-related details are often not

adequately described in the scientific literature (Yetley, 2007). While most of the

MVM formulations available in the market are relatively complete in terms of the

vitamin and minerals included, not all forms of vitamins and minerals are equally

bioavailable.

Multivitamin supplements may contain ingredients derived from natural, synthetic or

partially synthetic analogues. There is some evidence to suggest that vitamins,

particularly vitamin E, are absorbed, processed and retained more effectively by the

body if in natural form compared to synthetic forms (Burton, Traber et al., 1998; Zingg

and Azzi, 2004). Therefore, differences in absorption of MVMs will vary depending on

the vitamin compounds included in the formulations. Despite this, increases in blood

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levels of the B vitamins in particular were significant in the current sample and

clinically meaningful.

A number of questions have arisen from the results of the current thesis, as well as past

findings. For example: what is the ideal dose of vitamins? And what is the optimal

duration of supplementation? Long and Benton (2013), in their meta-analysis, recently

reported that supplements with doses higher than the Recommended Dietary Intake

(RDI), resulted in greater mood results. This questions the relevance of RDIs and how

adequately the guidelines meet the requirements for optimal brain health (Benton,

2013). The calculation of RDIs did not include any psychological or behavioural

measures, but were designed to prevent deficiency and for “adequate physiological or

metabolic function” (National Health and Medical Research Council, 2006).

The supplements used in the current studies contained a wide range of vitamins,

minerals and herbal constituents, some at many times greater than the RDI guidelines.

In particular, the levels of B12, B6 and folate, as well as zinc and vitamin E, contained in

the supplements were well over the minimum daily intake outlined by the NHMRC

(2006). Importantly, the supplements utilised in the current studies are comparable,

particularly in relation to the B vitamins, to other supplements used in past research in

older groups. Supplementation with B vitamins generally benefits homocysteine

reduction within weeks of commencing supplementation, however, effects of mood and

cardiovascular function are often not observed in clinical trials, if participants are

considered healthy. Morris and Tangney (2011) suggest that a potential weakness of

RCTs is the inclusion of individuals with optimal nutrient levels. They speculate that

vitamin supplements will be less effective in these individuals, than in those that have

suboptimal levels. In the current group, blood nutrient levels of the B vitamins, zinc and

vitamin E were classified within the “optimal” range for most participants at the

baseline session. This could explain the lack of chronic benefits observed in the group,

despite the increase in the blood nutrient levels after supplementation. In order to get

around this issue, a correlational analysis of the relative change in blood nutrient levels

compared to the change in mood variables was assessed in Chapter 5. It was revealed

that as folate levels increase in the blood, mental fatigue decreases, indicating that

although the overall mood of the sample was not changed, there seems to be an

underlying mechanism of change occurring that does not come through in a traditional

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ANOVA approach. Therefore, the lack of effect of chronic supplementation on the

main mood outcomes does not mean that the supplements were ineffective. The

examination of the physiological effects of MVMs, on mechanisms that are known to

influence mood and cardiovascular function, in the case of healthy older individuals, is

important in order to determine if the MVM is providing any benefits. In the long-term,

the protective benefits of MVMs may be a result of a reduction in risk markers

associated with cardiovascular disease processes and mood dysfunction.

Inadequate quantities of nutrients or impaired absorption into the body of the required

nutrients may have influenced the null findings for the mood outcomes. However, the

results from the study in Chapter 5 do not support this premise. The levels of B12, folate

and B6 dramatically increased after 16 weeks of MVM supplementation, suggesting that

the group had no issues with absorption. Furthermore, homocysteine levels were

significantly reduced, indicating that the levels of the B vitamins contained within the

supplements were adequate enough to enhance homocysteine methylation. Past

research has identified associations between increases in circulating B vitamins and

improvements in mood, however, as mentioned in the previous section (7.2), a design

flaw of these studies assumes that a combination of acute and chronic effects of

supplementation were observed. The fact that we found acute mood effects, but no

chronic effects with an identical MVM formulation suggests that mood may be

improved via an acute mechanism, rather than a longer term reduction in risk factors

such as homocysteine status. While the acute mechanism through which MVMs exert

benefits to mood is yet to be studied, past research has indicated that blood plasma

levels, particularly for B2, B6 and folic acid, peak in the blood within 3 hours of

ingestion (Bor, Refsum et al., 2003; Dainty, Bullock et al., 2007; Mönch, Netzel et al.,

2010). Furthermore, it has been suggested that improvements in mitochondrial

function, and vascular endothelial function may be a pathway through which acute

actions of MVMs may work (Kennedy, Haskell et al., 2008). For instance,

improvements in endothelium-dependent vasodilation following a single dose of B

vitamins (Chambers, Ueland et al., 2000; Doshi, McDowell et al., 2001; Doshi,

McDowell et al., 2002), and vitamins C and E (Title, Cummings et al., 2000; Katz,

Nawaz et al., 2001) in both clinical and healthy groups have been identified, suggesting

a role for these vitamins in improving endothelial function. However, the precise

mechanism of action is still yet to be determined. Scholey et al. (2001) suggest that an

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increase in the delivery of active metabolites to neural tissue may be the mechanism

through which mood is influenced. Due to increased brain metabolite availability and

improvements in blood flow and vasodilation in the brain.

It could be that in order to discern subtle changes in mood in healthy older individuals,

without the interference of acute effects; a longer duration of supplementation is

required. The study in Chapter 5 was a 16-week intervention, while the trial in Chapter

6 was only 4 weeks. Other studies conducted in older samples have found mood

benefits with short supplementation durations; however, these participants have been

more vulnerable than the participants studied in the two RCTs contained in this thesis.

A similar study conducted in a healthy group of older individuals also failed to find any

mood benefits after 24-weeks of chronic MVM supplementation (Cockle, Haller et al.,

2000), suggesting that longer dosage durations are required in healthy older individuals

in order to observe any benefits to mood. Studies that have been conducted for much

longer period of time than the studies reported in this thesis have observed benefits of B

vitamin supplementation. For example, results from the VITACOG study suggest that 2

years of B vitamin supplementation was effective in reducing homocysteine, improving

cognitive function, as well as reducing the rate of brain atrophy in patients with mild

cognitive impairment (MCI) (Smith, Smith et al., 2010). These results suggest that

benefits to the brain are possible after a longer supplementation period.

7.4 Physiological effects of multivitamin supplementation

A number of beneficial effects on physiological outcomes were observed, despite the

lack of effect of chronic MVM supplementation on mood. Even though long-term

mood was not influenced in the current studies, it is still important to discuss the

potential mechanisms through which the MVM may provide benefits. A change in

blood biomarkers after 4 months of supplementation is an important finding, given the

popularity of MVM supplements in the community (Millen, Dodd et al., 2004;

Sebastian, Cleveland et al., 2007).

That the MVM was able to provide health benefits, in a group of people with overall

good health, is encouraging. Participants in the study reported in Chapter 5, began with

vitamin B levels within the reference range for their age, and moderate homocysteine

levels. Despite these baseline levels, the MVM was still effective in increasing B

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vitamin levels in the blood. Furthermore, homocysteine was significantly reduced by

the MVM. As described in Chapter 3, higher levels of homocysteine have been linked

to mood disturbances (Bottiglieri, 2005), and are an independent risk factor for

cardiovascular disease (Graham, Daly et al., 1997). Additionally, high levels of

homocysteine have been shown to be neurotoxic. These findings suggest that although

mood was not modified by MVM supplementation, the measureable change in blood

biomarkers may be a way to address modifiable risk factors and effect change over a

longer period of supplementation.

In order to address the inter-individual differences associated with the uptake of the

MVM constituents, a correlational analysis of change scores revealed an important

finding. Individuals with the largest increases in folate showed a significant reduction

in mental fatigue. The variability in the uptake of vitamins in older populations needs

to be accounted for, and an ANOVA approach where group means are compared,

particularly in small sample may restrict the results. We suggest that this approach has

merit, and should be considered in future research. Having blood biomarkers of vitamin

levels presents a useful reference for the observation of mood effects.

Cardiovascular function was also not modified by the multivitamin in either study. The

null findings with regards to cardiovascular function may also explain the lack of

observable changes to mood. The cardiovascular system is a pathway through which

mood may be modulated, and improvements to cardiovascular health may result in

improvements to mood. A number of cardiovascular measurements were assessed in the

current trials. Blood biomarkers of cardiovascular health were collected in the first trial,

and blood pressure and indices of arterial stiffness were recorded in both studies.

Measures of inflammation, hsCRP and fibrinogen, were not changed by 16 weeks of

MVM treatment. The participants in the first study had relatively low levels of the

inflammatory markers at baseline, leaving only a small window for improvement due to

supplementation. Both fibrinogen and hsCRP have been identified as independent risk

factors for cardiovascular disease (Ridker, Cushman et al., 1998; Ridker, Hennekens et

al., 2000; Mora, Rifai et al., 2006), and elevated levels of both markers have been

associated with increased depression (Panagiotakos, Pitsavos et al., 2004; Howren,

Lamkin et al., 2009). However, there is little evidence for the role of vitamins in

reducing levels of fibrinogen and hsCRP. The results of one study suggested a

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protective role of vitamin C after cardiac surgery in patients with atrial fibrillation.

Specifically, 7 days of vitamin C supplementation reduced levels of fibrinogen and

CRP, and also reduced the risk of reoccurrence of atrial fibrillation (Korantzopoulos,

Kolettis et al., 2005). hsCRP levels in cardiac patients has been lowered by combined

vitamin C, E and omegea-3 fish oil when supplemented for 7 days prior to cardiac

surgery (Castillo, Rodrigo et al., 2011). Conversely, Bae et al (2009) found no effects

of four weeks of antioxidant treatment (Vitamin C and quercetin) on CRP in patients

with rheumatoid arthritis. Only one MVM trial was reported in the literature with

regards to lowering CRP. Church et al. (2003) reported the reduction of CRP, in

healthy participants after 6 months of MVM supplementation. The participants were

slightly younger (30-70 years, mean age = 53 years) than the participants in the current

studies. Additionally, the supplements contained higher levels of B12 and folate than

those used in the current studies, and the supplementation duration was slightly longer.

It could be that a longer duration and higher levels of B12 and folate are required in

order to exert any benefits on hsCRP levels.

Multivitamin and mineral supplementation did not improve the measures of arterial

stiffness, augmentation index or augmentation pressure in either of the studies. The

majority of past research has been conducted primarily in patient groups. Of the studies

conducted in healthy groups, only one found benefits of supplementation on

augmentation index. This study found that 2 months supplementation of a highly bio-

available form of vitamin E was effective in reducing augmentation index in young

healthy male participants (Rasool, Rahman et al., 2008). The same group, using a

different form of vitamin E failed to find the same benefits of vitamin E on

augmentation index (Rasool, Yuen et al., 2006).

Compared to the data from healthy samples, there seems to be more evidence for the

benefit of supplementation on augmentation index in patient groups. For example,

Mullan et al (2002) found that 4-weeks of 500mg/day of vitamin C was effective in

reducing augmentation index in patients with type II diabetes. Another investigation

found that a combination of vitamin C and E, in patients with untreated essential

hypertension was effective in reducing augmentation, but failed to reach statistical

significance (Plantinga, Ghiadoni et al., 2007). Furthermore, a combination of folate

and methylcobalamin was found to be more effective in reducing augmentation index in

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patients on haemodialysis than folate administered in isolation (Koyama, Ito et al.,

2010). Interestingly, results from the Atherosclerosis and Folic Acid Supplementation

Trial (ASFAST) failed to find any effect of folate supplementation on a range of arterial

stiffness measure in chronic renal failure patients (Zoungas, McGrath et al., 2006).

Given these findings, the fact that the participants in the current studies were in good

health may explain the lack of positive findings for augmentation index and

augmentation pressure. Additionally, as the supplements in the current studies

contained much smaller amounts of vitamins C and E (200mg and 20-25mg

respectively), than the supplements used in previous trials, indicating that the daily

dosage may not have been great enough to see any beneficial effects of supplementation

on measures of arterial stiffness. Another explanation could be that the arterial stiffness

often observed in patients groups is often functional, a result of disease processes

(Wilkinson, Hall et al., 2002; Wilkinson, Qasem et al., 2002), and therefore more

amenable to improvement with treatment interventions (Pase, Grima et al., 2011).

However, the arterial stiffness observed in healthy, older individuals is more likely to be

age-related, and often not reversible (O'Rourke, 1995). It is possible that improvements

due to supplementation were not observed in the current group, as they would likely be

categorised with age-related arterial stiffness.

The lack of significant reductions in augmentation index can also explain the lack of

mood improvements in the current trials. Depression, and to an extent anxiety, have

been associated with increased arterial stiffness measured by pulse wave velocity

(Tiemeier, 2003), as well as augmentation index (Seldenrijk, van Hout et al., 2011).

Recently, Oulis et al (2010) demonstrated that successful treatment of depression

through traditional antidepressant treatment also resulted in significant reductions in

arterial stiffness. These results suggest that the successful reduction of depressive

symptoms also leads to a significant improvement in arterial stiffness, providing support

for the relationship between cardiovascular function and mood.

7.5 The Benefit versus Risk of Multivitamin Supplementation.

A number of general health measures were recorded over the course of both

experiments reported in the current thesis. These measures enabled an assessment of

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the suitability of the supplements under investigation for the improvement of health-

related outcomes for an older adult group.

In terms of tolerability, only two participants, across both investigations reported side

effects. One of these participants, as reported in Chapter 5, was allocated to the placebo

supplement, so the side effects experienced by this participant could not be attributed to

the MVM. The other participant, reported in Chapter 6, experienced possible side

effects related to the MVM treatment. This was reported as an adverse event, and the

participant was instructed to discontinue use and subsequently withdrawn from the

study.

Importantly, the safety profile of the MVM assessed using renal and liver measures

showed no significant changes following 16 weeks’ supplementation (Chapter 5). It was

assumed that these safety parameters could be extended to the study reported in Chapter

6 as a shorter duration of supplementation, and an identical MVM formulation as the

women’s supplement given in the Chapter 5 trial was employed for this study. To our

knowledge, no other research group has investigated the safety of MVM supplements

on general health in this way. A search of the literature yielded only one other study,

which was conducted by our group. This study, conducted in elderly women with

subjective memory complaints, used the same MVM supplement as the current studies,

and also found no detrimental effects of the MVM on kidney or liver function

(Macpherson, Ellis et al., 2012). These results, when combined with those from the

current study, suggest that MVM formulations are safe for daily use in older groups of

individuals.

Despite the many documented benefits of MVMs, some reports of possible health risks

have been published in the literature. A paper published by Larsson et al (2010)

reported that MVM use was associated with an increased risk of breast cancer. In this

study of over 35,000 Swedish women, MVM use was associated with a 19% increased

risk of developing breast cancer within the 10-year follow-up period. The authors

attributed the folate content of the MVM supplements to the increase in cancer risk.

However, other studies have failed to find the same associations between MVM use and

cancer risk. For example, in a study of women who drank moderate amounts of alcohol

daily, the folic acid content of MVMs was found to be associated with a decreased risk

of breast cancer (Zhang, Hunter et al., 1999). Furthermore, the risk of colorectal cancer

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in moderate to heavy drinkers has been found to be reduced by the folate content of

MVMs (Jacobs, Connell et al., 2001). Fuchs et al. (2002) found that higher folate

intake, either through diet or using a MVMs, and reducing alcohol intake, reduced the

risk of colon cancer in those with a family history of the disease.

Others have also found, MVM use lowers the risk of colon cancer, regardless of alcohol

intake (Giovannucci, Stampfer et al., 1998; Zhang, Moore et al., 2006). Furthermore,

others have found no associations between MVM use and cancer (Neuhouser,

Wassertheil-Smoller et al., 2009). Interestingly, Lawson et al (2007) found that, while

regular MVM use was not associated with the risk of prostate cancer, men that reported

excessive use of MVM supplements (greater than 7 times per week) were at greater risk

of advanced and fatal prostate cancers, suggesting that over use of MVMs may be

harmful. Finally, a recent systematic review of RCTs failed to find any benefit or harm

of MVMs in the prevention of cancer (Huang, Caballero et al., 2006). Collectively,

there is little evidence to suggest that MVM use increases the risk of cancer.

Another potential risk of MVM supplements was brought to attention after the

publication of the results from the Iowa Women’s Health Study. In 2011, JAMA

Internal Medicine published findings suggesting that MVM use was associated with

increased total mortality risk in elderly women (Mursu, Robien et al., 2011). However,

these results are potentially confounded by the observation design, as well as factors

such as indication of use (Bjelakovic and Gluud, 2011) and that those with a history of

disease are more likely to use supplements (Rock, 2007). Little consensus regarding the

safety of MVMs has been provided by other large epidemiological studies. Park et al

(Park, Murphy et al., 2011) found no associations between MVM use and all-cause

mortality in data drawn from the Multiethnic Cohort Study of 182,099 individuals

across 2 US states. A larger study in the US, the Cancer Prevention Study II, of over 1

million US citizens indicated that in MVM use increased the risk of mortality in male

smokers only (Watkins, Erickson et al., 2000). A recent meta-analysis of randomised

controlled trials that have investigated the effects of MVMs on mortality reported no

effect of MVM treatment on all-cause mortality (Macpherson, Pipingas et al., 2013).

Data from observational studies are only able to provide limited information about

causality, while results from RCTs provide the highest level of evidence (Macpherson,

Pipingas et al., 2013). Therefore, the result of the meta-analysis suggests that there is

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no evidence of MVMs increasing the risk of mortality. Taken collectively, the risk of

MVM supplements on health is not clear. The potential risk of using a MVM

supplement should be considered with reference to the known benefits. The results of

the current studies lend support to the potential benefit of MVMs, particularly in the

reduction of homocysteine, and acute mood benefits.

One of the most important health-related findings in the current studies was the

significant reduction of homocysteine reported in the study in Chapter 5. Homocysteine

in the MVM group was reduced by almost 14% after supplementation. This is a finding

that has been consistently observed in our previous studies (Harris, Macpherson et al.,

2012; Macpherson, Ellis et al., 2012; Pipingas, Camfield et al., 2014), indicating that

this is a replicable finding. Other groups have reported similar reductions in

homocysteine after MVM treatment. Earnest (2002) observed reductions of 1.2 μmol/L

(15%) after 12 weeks of MVM supplementation. A 16-week MVM trial also reported

significant reductions in homocysteine (1.57 μmol/L) after treatment (Summers, Martin

et al., 2010). Furthermore, lowering homocysteine concentrations for patients with

vascular disease can slow the progression of the disease, even in those that have lower

levels of homocysteine (Hackam, Peterson et al., 2000). Elevated homocysteine has

also been associated with increased depression in a number of epidemiological studies

(Almeida, Flicker et al., 2004; Tolmunen, Hintikka et al., 2004b; Almeida, McCaul et

al., 2008; Wang, Wang et al., 2008). Reductions in plasma homocysteine

concentrations have been linked to recovery from depression after antidepressant

treatment augmented with folate (Coppen and Bailey, 2000). In the current study, while

homocysteine levels were reduced, mood was not improved. It could be that a longer

duration of supplementation is required before the benefits of reduced homocysteine are

reflected in changes in mood and cardiovascular function. Additionally, the inclusion

of participants with already optimal nutrient levels may have limited the actions of the

supplements on mood (Morris and Tangney, 2011)

Although not a focus of the current investigations, the actions of MVMs for improving

cognitive function has been investigated in a number of studies. Chronic MVM

supplementation has been shown to improve memory and other cognitive domains after

supplementation in younger (Haskell, Robertson et al., 2010; Kennedy, Veasey et al.,

2010) and also older samples (Harris, Macpherson et al., 2012; Macpherson, Ellis et al.,

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2012). Low levels of B vitamins and elevated homocysteine have been associated with

impaired cognitive function (Selhub, Bagley et al., 2000; Duthie, Whalley et al., 2002;

Selhub, Troen et al., 2010). The pathways through which MVMs exert their influence

on cognition are similar to the pathways for mood. Researchers have suggested that

alterations to neurotransmitter function (Calvaresi and Bryan, 2001), cardiovascular

disease prevention (Waldstein and Wendell, 2010) and homocysteine reduction (Smith,

Smith et al., 2010) may all help to improve cognitive outcomes.

7.6 Limitations and Future Directions

A number of limitations of the current investigations were discussed separately in the

experimental chapters (Chapters 5 and 6). The most important caveats were related to

the sample sizes and characteristics of the participants. Of particular importance was the

inclusion of participants with good baseline health, whose response to the MVM

treatment may have been smaller than those with poorer health.

With regards to the size of the samples in the current investigations, the inclusion of

additional participants in both experiments would have allowed for additional sub-group

analyses. In particular, a separate analysis of male and female participants in Chapter 5

would have been possible. Males and females have different daily requirements of

nutrients, and may respond to supplementation differently. The supplements used in the

experiment in Chapter 5 were designed in order to account for the differences in daily

nutrient requirements of males and females. The resulting formulations ensured that

male and female participants received similar, if not the same, daily dosage of vitamins

and minerals over the course of the study.

Additionally, a larger sample of participants would have allowed for an analysis of the

effect of baseline health. Specifically, a comparison between those with poorer health

at baseline and the effect of health on mood after supplementation would have been

possible with a larger sample. We would predict that those deficient or “sub-optimal”

would have poor mood, and be most amenable to supplementation.

Another potential limitation of the current investigations is the issue of multiplicity. A

high number of tests examining mood, cardiovascular and biochemical measures were

conducted across the two experimental chapters. A large number of tests increases the

possibility of type I error or false positive (Tabachnick and Fidell, 2013). While this

226

does not affect the primary outcome measures in the current studies, the secondary

outcome measures should be interpreted with caution. However, it should be noted that

in order to correct for multiplicity statistical corrections were applied to the current

investigations. Despite this, the corrections applied did not account for the large

number of hypotheses within the current thesis. Therefore, results with borderline

significance should be considered with this in mind. The most convincing findings are

the increase in blood B vitamin levels and reduction in homocysteine in Chapter 5,

along with the significant acute mood improvements (as measured by the DASS)

reported in Chapter 6. More speculatively are the reductions in anxiety, measured at the

acute session, as well as the improvements in calmness.


In summary, the aim of the current thesis was to investigate the effects of MVMs on

mood and cardiovascular function in the healthy elderly. Specifically, both the acute

and chronic effects of MVM supplementation on measures of mood were examined. A

further goal of these investigations was to examine the potential mechanisms through

which MVMs exert their benefits. Therefore, measures of cardiovascular function and

blood biomarkers (in Chapter 5 only) were assessed.

Previous investigations that examined the effects of MVMs on mood in the elderly have

yielded mixed results. The selection of participant groups, and the measures of mood

employed in these studies may have contributed to the disparity of the results. In the

current study, the results do not support the hypothesis that chronic MVM

supplementation improves mood in a healthy, older participant group. However, the

current investigation supports an acute role of MVMs in improving mood, particularly

in improving self-reported stress. This is the first study to examine the acute effects of

MVMs in an older group.

While the supplement had no effect on chronic mood in the current investigations,

beneficial effects on blood biomarkers were observed in the 16-week trial (Chapter 5).

Specifically, MVM supplementation increased levels of B vitamins and reduced

homocysteine. These improvements may have benefited health, mainly through an

improvement in B vitamin status, which is important for neurotransmitter production

and overall health of the brain. The increase in B vitamins resulted in a decrease in

227

homocysteine, which is very important for cardiovascular health and health in general.

Additionally, those with a greater change in folate levels demonstrated a greater

reduction in mental fatigue. Including blood biomarkers as a part of the research design

presents another option for the observation of the effects of MVMs on mood.

Although the findings with regard to chronic mood improvements after MVM

supplementation are limited in the present investigation, further research is necessary to

elucidate the role that nutritional interventions have on mood. In particular, the

mechanisms through which vitamins exert benefits on mood require further study. The

results of the present investigation revealed acute benefits of MVM supplementation on

mood. Future research should aim to address the potential mechanisms through which

MVMs exert acute benefits.

In conclusion, the current studies set out to determine if mood could be improved by

MVM supplementation in an older group of healthy individuals. While the results do

not support a role of chronic MVM supplementation, a novel finding revealed by the

current studies was that a single MVM dose was effective in improving mood 1-2 hours

after ingestion. This suggests that MVMs may act to improve mood through more

immediate physiological effects in the hours following ingestion.

228


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Appendix A Explanatory statement and

Informed consent (Chapter 5)

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Appendix B Ethics Documentation (Chapter 5)

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Appendix C Explanatory statement and

Informed consent (Chapter 6)

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Appendix D Ethics Documentation (Chapter 6)

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Appendix E Publications relevant to this thesis Preliminary results of the Purple multitasking research framework in chapter 5 were

presented in poster form at 2 conferences.

The acute mood data presented in Chapter 6 has been published in the following paper:

Macpherson H, Rowsell R, Cox K, Scholey A, Pipingas A. (2015). Acute mood but not

cognitive improvements following administration of a single multivitamin and

mineral supplement in healthy women aged 50 and above: a randomised

controlled trial. Age 37, 38.

The chronic mood data from chapter 6 has been accepted for publication for publication.

Other abstracts/publications from author:

Bauer I, Crewther DP, Pipingas A, Rowsell R, Cockerell R, & Crewther SG. (2011) Omega-3 fatty acids modifies human cortical visual processing – A double-blind crossover study. PlosOne, 6(12); e28214.

Harris E, Kirk J, Rowsell R, Vitetta L, Sali A, Scholey AB, & Pipingas A. (2011) The effect of multivitamin supplementation on mood and stress in healthy older men. Human Psychopharmacology Clinical and Experimental, 26(8), 560-567.

Bauer I, Hughes M, Rowsell R, Cockerell R, Pipingas A, Crewther SG, & Crewther DP. (2014) Omega-3 supplementation improves cognition and modifies brain activation in young adults. Human Psychopharmacology Clinical and Experimental, 29(2), 133-144.

Harris E, Rowsell R, Pipingas A, Macpherson H. (2016) No effect of multivitamin supplementation on central blood pressure in healthy older people: A randomised controlled trial. Atherosclerosis, 246, 236-242.

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Multivitamin supplementation in an older population: the impact … · 2017. 2. 6. · Swisse...

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