Iodine intakes and food sources of
iodine in Victorian Schoolchildren
by
Kelsey Beckford
Bachelor of Food Science and Nutrition (Hons)
Submitted in fulfilment of the requirements for the degree of
Doctor of Philosophy
Deakin University
June 2018
Acknowledgements
There are many people who I wish to thank and acknowledge for helping
and supporting me throughout the past four years. First and foremost, I wish to
thank my beautiful family who have had to put up with my unpredictable mood
swings and continued ranting. Mum, Dad, Meghan and Truffels, I could not have
gotten through the past four years without you and I am eternally grateful for all
of your help, comfort and support.
Considerable mention must go out to each and every single person who has
been a friend and support in my immediate work environment, as at times I know
I have been a right pain to deal with on a daily basis. Particular shout outs go to
Sim, Jules, Penny, Andrew, Inga, Ajam, Kathryn, Peggy, Linda, Jen, Megs, Simi, Karen
and Rivkeh, I could not have done it without you.
I wish to extend my most heartfelt thanks to my team of supervisors. You
have all contributed uniquely to my PhD experience, and I definitely could not have
gotten through my PhD without the combined efforts of all 5 of you. Caryl, your
knowledge and expertise have added to my own immensely, and I have learnt so
much from working with you. Thank you for being a dedicated and steadfast
supervisor, always pushing me to do better. Lynn, thank you for your support,
guidance and advice throughout my PhD I definitely do not think I would have had
the belief in myself to conquer a PhD if it had not been for your encouragement
and support at the end of honours. Claire, thank you for letting my hide under your
desk when I was feeling stressed and overwhelmed, for being a rational confidant
and providing advice and support in my more stressed out moments. Carley, thank
you for taking the time out of your busy schedule to answer my questions and give
me direction and support, particularly when it came to the data analysis and the
re-entry of the food recalls. I have learnt so much from you and I hope we are able
to work together in the future. Finally, Sheila, although you were involved from
afar, thank you for your support and knowledge. I am so grateful for your warm
hospitality, kindness, patience and understanding when I called Otago home for 6
weeks. You, Murray and the team at Otago made me feel so welcome and made
living away from home a breeze (even though you tried to kill me at sandfly bay).
This brings me to the rest of the Otago uni crew. Anna, Zheng, Andrew,
Devonia, thank you for welcoming me into your circle and involving me in your
social activities. Your warmth and generosity was immensely appreciated. I also
wish to thank Michelle Harper and Ashley Duncan for their support in the lab as I
was learning the urine analysis method and to Claire who opened her home for me
to stay in.
Additional thanks goes out to Rachel West and the Deakin University
Librarians, who helped me during my systematic review. Karen Lamb for her
statistical knowledge and for spending hours with me trying to figure out the
analyses for all of my studies. I also wish to acknowledge Dorothy Mackerras whose
question at a Nutrition Society of Australia conference got the ball rolling for the
systematic review. Finally I wish to acknowledge all of the tech team and admin
team at Deakin, Joan, Sharon, Linda and Amanda, as well as the HDR co-ordinators
and Brad Aisbett, all of whom have provided support and who have contributed to
my PhD experience in some way.
I also wish to acknowledge the project manager of the SONIC study,
Manuela Rigo, as well as all of the research assistants, participants, parents and
schools involved in the SONIC study, without whom my PhD would not exist. I
would also like to acknowledge the National Heart Foundation of Australia Grant-
in-Aid, Helen MacPherson Smith Trust Fund Project Grant and Deakin University
Faculty Research Development grant, which funded the SONIC study, as well as the
Australian Postgraduate Award which supported me throughout my study.
The past four years of my life have been incredibly challenging, but I have
learnt so much and I am so grateful to everyone for helping me get through it all.
I would like to dedicate this thesis to my best friend and confidante, Toffy,
whom I had to say goodbye to towards the end of my PhD after 16 long years of
unconditional love and friendship. I will never forget your scraggly face and the
look of love in your eyes as I complained to you about things you would never
understand. I hope you are living a better life wherever you are.
List of Publications and Presentations
Manuscripts published:
Beckford K, Grimes C, Margerison C, Riddell L, Skeaff S, Nowson C. Iodine
Intakes of Victorian Schoolchildren Measured Using 24-h Urinary Iodine Excretion.
Nutrients. 2017;9(9):961.
Conference abstracts published:
International Conference on Diet and Activity Methods, Brisbane, Australia, 2015
Beckford K, Grimes CA, Riddell LJ, Margerison C, Skeaff S, Nowson C. 24-
hour Urinary Iodine Concentration and 24hr Urinary Iodine Excretion in a sample
of Australian primary school children. 2015. Poster Presentation.
Joint Annual Scientific Meeting of the Nutrition Society Australia and Nutrition
Society New Zealand, Wellington, New Zealand, 2015
Beckford K, Grimes CA, Riddell LJ, Margerison C, Skeaff S, Nowson C. 24-
hour Urinary Iodine Concentration and 24hr Urinary Iodine Excretion in a sample
of Australian primary school children. 2015. Poster Presentation.
Beckford K, Grimes CA, Riddell LJ, Margerison C, Skeaff S, Nowson C. The
association between 24-hour urinary sodium and iodine excretion in a sample of
Victorian school-aged children. 2015. Oral Presentation.
The Nutrition Society of Australia Annual Scientific Meeting, Melbourne, Australia,
2016
Beckford K, Grimes C, Margerison C, Riddell L, Skeaff S, Nowson C.
Relationship between urinary iodine excretion, milk and bread intake in Victorian
schoolchildren. Poster Presentation
Asia Pacific Conference on Clinical Nutrition, Adelaide, Australia, 2017
Beckford K, Grimes C, Margerison C, Riddell L, Skeaff S, Nowson C. Twenty-
four hour urinary volume of children: a systematic review of the literature. 2017.
Oral Presentation.
Contribution to Associated Publications
Grimes CA, Riddell LJ, Campbell KJ, Beckford K, Baxter JR, He FJ, et al. Dietary
intake and sources of sodium and potassium among Australian schoolchildren:
results from the cross-sectional Salt and Other Nutrients in Children (SONIC) study.
BMJ Open. 2017;7(10).
Specific contributions and tasks performed by
the Author
1. Conducted a systematic review and meta-analysis of studies reporting the 24-hour
urine volume of children and adolescents. This process involved:
Locating relevant articles
Screening for inclusion in data synthesis
Data extraction and collation
Meta-analysis of study findings
2. Utilising data from a larger study, the Salt and Other Nutrient Intake in Children
(SONIC) study the following tasks were undertaken by the author:
Locating previously frozen 10mL aliquots of 24-hour urine samples, collected
from the 750 participants of the SONIC study. Following this the Author
defrosted, re-aliquoted and immediately refroze the samples for iodine analysis.
These samples were then transported from Deakin University, Melbourne,
Australia to the University of Otago in Dunedin, New Zealand.
The author then learnt the method for determining the iodine concentration in
urine samples, a modification of the method established by Pino et. al, under
the supervision of Associate Professor Sheila Skeaff at the University of Otago.
Following this, the author analysed the 750 available urine samples for iodine
concentration, under the supervision of Associate Professor Skeaff.
The author was originally involved in the co-ordination and entry of over 650
24-hour food recalls collected as part of the SONIC study, under the supervision
of Dr. Carley Grimes. However, as these recalls were originally entered into a
version of FoodWorks which was linked to an outdated nutrient database, the
recalls for use in the present thesis (i.e. children aged >8 years of age, ~600
recalls) needed to be re-entered into the newer software, released in early
2017, as this was linked to a database which had been updated to reflect
changes to the iodine content of foods as a result of the introduction of
mandatory fortification of bread with iodised salt from October 2009. The
process of re-entry was undertaken solely by the Author, under the supervision
of Professor Caryl Nowson and Dr. Carley Grimes.
~ i ~
Table of Contents
ABSTRACT 1
CHAPTER ONE: INTRODUCTION 7
CHAPTER TWO: REVIEW OF THE LITERATURE 13
2.1 BACKGROUND ............................................................................................................. 13
2.2 IODINE IN THE BODY ..................................................................................................... 13
2.3 IODINE INTAKES AND HEALTH ......................................................................................... 15
2.3.1 Severe consequences of iodine deficiency................................................................ 15
2.3.2 Mild iodine deficiency ................................................................................................ 17
2.3.3 Excessive iodine intakes ............................................................................................. 19
2.3.4 Recommended Dietary Intakes for iodine: Australia and New Zealand and
determination of individual iodine requirements ..................................................... 20
2.4 ASSESSMENT OF IODINE NUTRITION ................................................................................ 21
2.4.1 Assessment of Thyroid size ........................................................................................ 21
2.4.2 Urinary iodine ............................................................................................................ 22
2.4.3 WHO recommendations for assessing the iodine status of populations .................. 28
2.5 IODINE NUTRITION IN AUSTRALIA ................................................................................... 33
2.5.1 History of Iodine deficiency in Australia .................................................................... 33
2.5.2 Mandatory fortification of bread with iodised salt ................................................... 35
2.5.3 Population Iodine nutrition in Australia post‐fortification of bread with iodised salt
36
2.5.4 Dietary assessment .................................................................................................... 37
2.6 FOOD SOURCES OF IODINE IN AUSTRALIA ......................................................................... 38
2.6.1 Bread .......................................................................................................................... 38
2.6.2 Milk as a dietary source of iodine .............................................................................. 39
2.6.3 The use of iodised salt ............................................................................................... 40
2.7 SODIUM REDUCTION TARGETS AND IODINE ....................................................................... 43
2.7.1 Sodium intakes and health of children and adolescents .......................................... 43
2.7.2 Global action to reduce sodium intake ..................................................................... 43
2.7.3 Australian sodium reduction strategies .................................................................... 44
2.8 SUMMARY .................................................................................................................. 46
CHAPTER THREE: STUDY 1: META‐ANALYSIS OF AVERAGE 24‐HOUR
URINARY VOLUME OF CHILDREN AND ADOLESCENTS 49
3.1 INTRODUCTION ........................................................................................................... 49
3.2 AIM .......................................................................................................................... 50
3.3 METHODS .................................................................................................................. 50
3.3.1 Information Sources and Search ............................................................................... 50
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3.3.2 Inclusion/Exclusion criteria ....................................................................................... 52
3.3.3 Data extraction and synthesis ................................................................................... 54
3.3.4 Quality Assessment ................................................................................................... 55
3.3.5 Statistical Analysis ..................................................................................................... 56
3.4 RESULTS .....................................................................................................................69
3.4.1 Summary of studies considered for primary analysis ............................................... 69
3.4.2 Quality of studies considered for primary analysis ................................................... 69
3.4.3 Initial analysis ............................................................................................................ 70
3.4.4 Primary analysis limited to studies with > 1 urine assessment criteria .................... 70
3.5 DISCUSSION ................................................................................................................75
3.6 CONCLUSION ...............................................................................................................78
CHAPTER FOUR: THE SALT AND OTHER NUTRIENT INTAKE IN
CHILDREN (SONIC) STUDY METHODOLOGY 81
4.1 PARTICIPANT RECRUITMENT ...........................................................................................81
4.1.1 Phase One: Victorian non‐government privately funded schools ............................ 82
4.1.2 Phase Two: Victorian government schools ............................................................... 82
4.2 TESTING PROCEDURES ..................................................................................................84
4.2.1 Demographic characteristics ..................................................................................... 84
4.2.2 Discretionary salt use characteristics ........................................................................ 85
4.2.3 Anthropometric measurements ............................................................................... 85
4.3 24‐HOUR URINE COLLECTION .........................................................................................86
4.3.1 Procedure .................................................................................................................. 86
4.3.2 Validity of urine samples ........................................................................................... 87
4.3.3 Biochemical Analysis ................................................................................................. 88
4.4 24‐HOUR FOOD RECALL .................................................................................................90
CHAPTER FIVE: STUDY 2: IODINE INTAKES OF VICTORIAN SCHOOL‐
AGED CHILDREN MEASURED USING 24‐HOUR URINARY IODINE
EXCRETION 93
5.1 INTRODUCTION ............................................................................................................93
5.2 AIM ...........................................................................................................................94
5.3 METHODS ...................................................................................................................94
5.3.1 Participants and recruitment .................................................................................... 94
5.3.2 24‐hour urine collection ............................................................................................ 94
5.3.3 Urinalysis ................................................................................................................... 94
5.3.4 Statistical analysis ...................................................................................................... 95
5.4 RESULTS .....................................................................................................................96
5.4.1 Demographic characteristics ..................................................................................... 96
5.4.2 Urinary parameters, by gender ................................................................................. 96
5.4.3 Urinary parameters, by age ....................................................................................... 98
5.4.4 Urinary parameters, by socioeconomic status ......................................................... 99
5.5 DISCUSSION ............................................................................................................. 100
5.6 CONCLUSIONS .......................................................................................................... 103
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CHAPTER SIX: STUDY 3: FOOD SOURCES OF IODINE AND
ASSOCIATION WITH URINARY IODINE EXCRETION 105
6.1 INTRODUCTION ......................................................................................................... 105
6.2 AIMS ....................................................................................................................... 106
6.3 METHODS ................................................................................................................ 106
6.3.1 Participants and recruitment ................................................................................... 106
6.3.2 Measures ................................................................................................................. 106
6.3.3 24‐hour food recall .................................................................................................. 106
6.3.4 24‐hour urine collection .......................................................................................... 107
6.3.5 Urinalysis .................................................................................................................. 107
6.3.6 Statistical analysis .................................................................................................... 107
6.4 RESULTS .................................................................................................................. 109
6.4.1 Demographic characteristics ................................................................................... 109
6.4.2 Iodine intakes ........................................................................................................... 109
6.4.3 Food sources of iodine ............................................................................................ 111
6.4.4 Relationship between food sources of iodine and UIE ........................................... 113
6.4.5 Differences in dietary iodine intake and UIE between consumers and non‐
consumers of bread and milk. ................................................................................. 117
6.5 DISCUSSION .............................................................................................................. 118
6.6 CONCLUSION ............................................................................................................ 121
CHAPTER SEVEN: STUDY 4: ASSOCIATION BETWEEN URINARY
EXCRETION OF SODIUM AND IODINE IN 24‐HOUR URINE SAMPLES
AND ASSOCIATION WITH DISCRETIONARY SALT USE 123
7.1 INTRODUCTION ......................................................................................................... 123
7.2 AIMS ....................................................................................................................... 124
7.3 METHODS ................................................................................................................ 124
7.3.1 Participants and recruitment ................................................................................... 124
7.3.2 Measures ................................................................................................................. 124
7.3.3 Discretionary salt use characteristics ...................................................................... 125
7.3.4 24‐hour urine collection .......................................................................................... 125
7.3.5 Urinalysis .................................................................................................................. 125
7.3.6 Statistical analysis .................................................................................................... 125
7.4 RESULTS .................................................................................................................. 126
7.4.1 Demographic characteristics ................................................................................... 126
7.4.2 Relationship between urinary sodium and urinary iodine excretion ...................... 127
7.4.3 Differences in urinary iodine excretion across discretionary salt use categories ... 128
7.5 DISCUSSION .............................................................................................................. 130
7.6 CONCLUSION ............................................................................................................ 132
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CHAPTER EIGHT: DISCUSSION 133
8.1 VICTORIAN CHILDREN HAVE SUFFICIENT IODINE INTAKES – A RESULT OF THE SUCCESSFUL
IMPLEMENTATION OF MANDATORY FORTIFICATION? ........................................................ 133
8.2 CURRENT METHODS FOR ASSESSING THE IODINE NUTRITION OF POPULATIONS – IS IT TIME FOR A
CHANGE?................................................................................................................. 137
8.3 CURRENT LACK OF POPULATION IODINE MONITORING IN AUSTRALIA .................................. 141
8.4 CONCLUDING REMARKS .............................................................................................. 143
REFERENCES 145
APPENDICES 165
~ v ~
List of Tables
Table 2.1: Daily iodine intake recommendations for children and
adolescents - Australia and New Zealand (µg/day) .................. 20
Table 2.3: World Health Organization epidemiological criteria for
assessing iodine nutrition based on median urinary iodine
concentrations from spot urines in different target groups ..... 32
Table 2.4: Studies documenting iodine deficiency in the Australian
population pre-fortification of bread with iodised salt .............. 34
Table. 2.5: Comparison of median UIC from spot urine samples of
schoolchildren in 2003-2004 and 2011-2013 ................................ 36
Table 3.1: Search criteria specifications for each database .......................... 51
Table 3.2: Data extracted from included studies ............................................ 54
Table 3.3: Characteristics of studies considered for primary analysis
where 24-hour urine volume was presented as mean (SD/SEM),
n=36 studies ...................................................................................... 59
Table 3.4: Characteristics of studies considered for the primary analysis
where 24-hour urine volume was presented as median (IQR),
n=7 studies ........................................................................................ 67
Table 5.1: Descriptive characteristics and urinary parameters of SONIC
participants ....................................................................................... 97
Table 5.2: Urinary parameters of SONIC participants, by age group
(n=650). .............................................................................................. 98
Table 5.3: Urinary parameters of SONIC participants by school postcode
socioeconomic status mean (SD) (n=650) ..................................... 99
Table 5.4: Urinary parameters of SONIC participants, by parental
education socioeconomic status mean (SD) (n=554) ................... 99
Table 6.2: Food sources of iodine in SONIC participants >8y/o with both a
valid food recall and urine sample (n=454) ............................... 111
Table 6.3: Urinary Iodine Excretion and dietary iodine intake by
consumption of bread and milk (n=454) .................................... 116
Table 7.1: Demographic characteristics of SONIC participants included in
sodium analysis (n=649) ............................................................... 127
~ vi ~
Table 7.2: Urinary excretion of iodine and sodium across discretionary salt
use categories (n=638), mean (SEM) or n (%) ............................ 129
Table 7.3: Relationship between urinary iodine excretion (μg/24-hour) and
discretionary salt use (n=638) ...................................................... 129
Table 8.1: Iodine Nutrient Reference Values for children and adults ...... 139
~ vii ~
List of Figures
Figure 2.1: Absorption and metabolism of dietary iodine ........................... 15
Figure 3.1: PRISMA flow chart of study selection ......................................... 53
Figure 3.2: Flow chart of studies included in analyses ................................. 58
Figure 3.3: Forest plot of studies assessing 24-hour urine volumes of 2-6
year olds with >1 urine assessment criteria (n=1084) ................. 72
Figure 3.4: Forest plot of studies assessing 24-hour urine volumes of 7-11
year olds with >1 urine assessment criteria (n=3628 ) ................ 73
Figure 3.5: Forest plot of studies assessing 24-hour urine volumes of 12-19
year olds with >1 urine assessment criteria (n=1438) ................. 74
Figure 4.1: Outline of recruitment and participation in the SONIC study 84
Figure 4.2: Flow chart of urines included in iodine analysis ....................... 88
Figure 6.1: Relationship between grams of bread consumed and 24-hour
urinary iodine excretion among SONIC participants with both
a valid food recall and urine sample (n=454) ............................ 114
Figure 6.2: Relationship between grams of milk consumed and 24-hour
urinary iodine excretion among SONIC participants with both
a valid food recall and urine sample (n=454) ............................ 114
Figure 6.3: Relationship between grams of bread and milk consumed and
24-hour urinary iodine excretion among SONIC participants
with both a valid food recall and urine sample (n=454) .......... 115
Figure 7.1: Relationship between urinary excretion of iodine and sodium
in the SONIC paticipants included in sodium analyses
(n=649) ............................................................................................. 128
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List of Appendices
Appendix A: Summary of Food and Health Dialogue food reformulation
targets (323) ........................................................................................ 165
Appendix B: Characteristics of studies which utilised the Dortmund
Nutritional and Anthropometric Longitudinally Designed
(DONALD) Study ......................................................................... 167
Appendix C: Modified Newcastle – Ottawa Quality Assessment Scale .. 176
Appendix D: Forest plot of studies assessing 24-hour urine volumes of 2-6
year olds ......................................................................................... 177
Appendix E: Forest plot of studies assessing 24-hour urine volumes of 7-
11 year olds .................................................................................... 178
Appendix F: Forest plot of studies assessing 24-hour urine volumes of 12-
19 year olds .................................................................................... 179
Appendix G: Subgroup analysis of relationship between food sources of
iodine and UIE ............................................................................... 180
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List of Abbreviations
2 – Chi-squared test
µg – microgram
ACT – Australian Capital Territory
AHS – Australian Health Survey
AWASH – Australian Division of the World Action on Salt and Health
BP – Blood Pressure
BMI – Body Mass Index1
CASH – Consensus Action on Salt and Health
CNPAS – Children’s Nutrition and Physical Activity Survey
CNS – Central Nervous System
CVD – Cardiovascular Disease
CV – Coefficient of Variation
EAR – Estimated Average Requirement
estBMR – estimated Basal Metabolic Rate
FHD – Food and Health Dialogue
FFQ – Food Frequency Questionnaire
FSANZ – Food Standards Australia New Zealand
GIT – Gastro-intestinal Tract
ICCIDD – International Council for the Control of Iodine Deficiency Disorders
I/CR – Iodine : Creatinine Ratio
IDD – Iodine Deficiency Disorders
IOM – Institute of Medicine
IQ – Intelligence Quotient
IQR – inter-quartile range
kg – kilogram
L – Liter
mg – milligram
mL – milliliter
mmol – millimole
Na – sodium2
NHMRC – National Health and Medical Research Council
~ x ~
NINS – National Iodine Nutrition Survey
NRV – Nutrient Reference Value
PAHO – Pan American Health Organization
PRISMA – Preferred Reporting Items for Systematic Reviews and Meta-Analyses
r – Correlation co-efficient
R2 – co-efficient of determination
RCT – Randomised Control Trial
RDI – Recommended Dietary Intake
SD – Standard Deviation
SE – Standard Error
SEIFA – Socioeconomic Indexes for Areas
SES – Socioeconomic Status
SONIC – Salt and Other Nutrient Intake in Children study
T3 – 3,5,3’-Tri-iodothyronine
T4 – Thyroxine
Tg - Thyroglobulin
TSH – Thyroid Stimulating Hormone
UIC – Urinary Iodine Concentration
UIE – Urinary Iodine Excretion
UL – Upper Level of intake
UNICEF – United Nations Children’s Emergency Fund
USI – Universal Salt Iodisation
WHO – World Health Organization
Notes:
1 BMI was converted to age and gender adjusted z-scores using the least mean squares method
and the 2000 Centers for Disease Control and Prevention growth reference charts (1)
2 Ninety-five percent of sodium consumed is in the form of sodium chloride, commonly referred
to as salt. Throughout this thesis the term ‘salt’ has been used to refer to the presence of
sodium in foodstuffs. Where possible results for both sodium and salt excretion and/or intake
have been presented. The conversion factors for sodium to salt used throughout this thesis
are:
1 mmol sodium = 23 mg sodium
1 gram of salt (sodium chloride) = 390 mg of sodium (2)
~ 1 ~
Abstract
Iodine is an essential trace element that plays an important role in the
production of thyroid hormones, important in the growth and development of the
brain and central nervous system. As such, iodine deficiency during childhood has
been linked to impaired growth and cognition. Prior to the 1990s Australia was
believed to be iodine sufficient, however iodine deficiency was reported in children
and pregnant women in the late 1990s. In 2009 mandatory fortification of all
commercially produced yeast-leavened bread, excluding organic varieties, with
iodised salt was implemented. Studies conducted post-fortification using spot urine
samples have reported an improvement in iodine status among children and adults,
when compared to pre-fortification. More recently however, the successful
application of sodium reduction targets to bread, implemented as a part of a larger
sodium reduction strategy, has raised the concern that sodium reduction strategies
may have a negative impact on the iodine intakes of Australian schoolchildren.
As approximately 90% of ingested iodine is excreted within 24-48 hours the
measurement of urinary iodine excretion (UIE) in 24-hour urine samples can
provide an accurate estimate of total daily iodine intake, however their use in large
population based studies is limited. Historically however iodine nutrition has been
assessed through the measurement of median urinary iodine concentration (UIC)
measured in µg/L from spot urine samples, with the use of 24-hour urine samples
for measuring iodine intakes only becoming more common in larger population
groups in the late 20th century. Current recommendations for evaluating the
severity of iodine deficiency within a population provide criteria for defining iodine
status, whereby the median UIC estimated in spot urine samples from school-aged
children is used as a marker of iodine status. These recommendations define iodine
deficiency as a population median UIC <100 µg/L and are based on the assumption
that UIC is able to provide a surrogate estimate of the iodine intakes of the
population. Whilst this method may be appropriate for use in populations where
the daily urine volume is approximately 1L, its use as a surrogate index of iodine
intake in populations where the urine volume is less than 1L, such as younger
Abstract
~ 2 ~
children, could result in the overestimation of iodine intakes. To date however, no
studies have systematically evaluated the daily urine volume of school-aged
children, the population group recommended for use in iodine monitoring
programs.
Whilst spot urine samples are the easiest and most commonly used method
for assessing iodine nutrition in Australia, this method is not able to provide an
accurate estimate of actual iodine intake. To date there have been no studies
utilising 24-hour urine samples to estimate the iodine intakes of Australian school-
aged children post-fortification of bread with iodised salt. Furthermore, whilst the
recent Australian Health Survey was able to identify the main food sources of iodine
using 24-hour food recalls, to date there have been no studies examining the
association between the main food sources of iodine and an objective measure of
iodine intake, i.e. 24-hour urinary excretion of iodine. Such studies will help to
determine the success of iodine fortification strategies, as well as the potential
impact which sodium reduction strategies may have on the iodine intakes of
Australian schoolchildren.
The overall aims of this thesis were to: i) assess the average urine volume
of school-aged children to inform population estimates of iodine intake, through a
systematic review of the literature; ii) determine the iodine intakes of a sample of
Australian schoolchildren using an objective measure of total daily iodine intake,
post-fortification of bread with iodised salt, and identify socio-demographic
characteristics associated with iodine intake, and iii) to determine the association
between the major food sources of iodine, including bread, milk, and iodised salt,
and total iodine intake as measured using 24-hour urine samples.
The aim of Study 1 (Chapter 3) was to produce an estimate of the average
24-hour urine volume of children and adolescents, through a systematic review of
studies conducted in healthy children and adolescents (>1y and <19y). Of the 53
studies initially located a meta-analysis was conducted on 26 studies, which
included at least one criteria for assessing the completeness of urine collections.
Of these, 12 reported results for 2-6 year olds, 11 for 7-11 year olds and 7 for 12-
19 year olds. The overall mean (95% CI) 24-hour urine volume of 2-19 year olds was
774 (656, 893) mL/24-hours. When broken down by age group, mean (95% CI) 24-
Abstract
~ 3 ~
hour urine volume was 539 (468, 611), 786 (749, 824) and 1067 (855, 1279) mL/24-
hours for 2-6, 7-11 and 12-19 year olds, respectively (P<0.001). There was no
difference in average daily urine volume between genders. This study provides
evidence that the average urine volume of school-aged children is less than 1L,
which could result in the misclassification of iodine intakes when spot urine
samples are used as a surrogate index of iodine intakes in populations of school-
aged children.
The remaining three studies in this thesis utilised data from the Salt and
Other Nutrient Intakes in Children (SONIC) study, a cross-sectional study conducted
in a convenience sample of Victorian schoolchildren between June 2010 and May
2013. A single twenty-four hour urine sample was obtained from 650
schoolchildren aged 4-12 years (55% male) from 43 government and non-
government schools across Victoria, Australia. Completeness of collections was
assessed using collection time, total volume, and urinary creatinine. These samples
were analysed for urinary iodine using a modification of the ammonium persulfate
method. In a subset of participants aged >8 years of age (n=520), a single 24-hour
food recall was also collected.
The aim of Study 2 (Chapter 5) was to determine total daily iodine intake of
a sample of Victorian schoolchildren on one day utilising 24-hour UIE and to assess
differences across age, gender, and socioeconomic status. Valid 24-h urine samples
were provided by 650 children, mean (SD) age 9.3 (1.8) years (55% male). The mean
UIE of 4–8 and 9–13 year olds was 94 (48) and 111 (57) µg/24-hours, respectively,
with 29% and 26% of participants having a UIE below the age-specific Estimated
Average Requirement (EAR), respectively. The median (IQR) UIC was 124 (83,172)
µg/L, with 36% of participants having a UIC <100 µg/L. There was no difference in
UIE between the genders or by socioeconomic status. This convenience sample of
Victorian schoolchildren were found to be iodine replete, based on UIC and
estimated iodine intakes derived from 24-h urine collections, confirming the
findings of the 2011-13 Australian Health Survey.
The aims of Study 3 (Chapter 6) were to: i) determine the dietary intake and
food sources of iodine in a sample of Victorian schoolchildren, and ii) assess the
association between the major food sources of iodine, including bread and milk,
Abstract
~ 4 ~
and urinary excretion of iodine over a 24-hour period. A total of 454 participants
aged 8-12 years (mean (SD) 10 (1.3) years, 55% male) had both a valid 24-hour food
recall and a 24-hour urine sample analysed for iodine. Mean UIE and dietary iodine
were 108 (54) g/24-hour and 172 (74) µg/day, respectively. Major food sources
of dietary iodine were “regular breads, and bread rolls” (27%), “dairy milk” (25%)
and “mixed dishes where cereal is the major ingredient” (7%). The total amount of
bread consumed (g/d) was not associated with UIE, however there was a
significant, weak correlation between the amount of milk consumed (g/d) and UIE
(r=0.15, P=0.001). Furthermore, a 100 g/day increase in milk intake was associated
with a 4 µg/24-hour higher UIE and accounted for 2% of the variance in UIE
(R2=0.02, β=4.03 (0.90)(SE), P<0.001). This study demonstrated that both bread
and milk are important food sources of iodine, however only milk was significantly
associated with UIE.
As bread was a major source of iodine in this population most likely as a
result of the iodised salt added during processing, the aim of Study 4 (Chapter 7)
was to examine the relationship between urinary excretion of iodine (UIE) and
sodium (UrNa), as a measure of the intakes of these two nutrients. An additional
aim of this study was to assess whether there was an association between
discretionary salt use, i.e. salt added at the table or during cooking, and UIE. The
mean (SD) UIE and UrNa for all participants (n=649) were 104 (54) μg/24-hour and
104 (45) mmol/24-hour, respectively. There was a moderate, positive correlation
between UrNa and UIE (r=0.37, P<0.001). Regression analysis revealed that a 1
mg/24-hour increase in UrNa (0.003g salt) was associated with a 7.1 µg/24-hour
higher UIE and accounted for 14% of the variance in UIE (R2=0.14, β(SE)=7.12(0.80),
P<0.001). In the subsample of participants with both a complete 24-hour urine
sample and discretionary salt use data (n=638), 77% (n=493) of participants were
classified as a discretionary salt user, defined as using salt either at the table or
during cooking, with 28% (n=177) of participants adding salt both at the table and
during cooking. There was, however, no significant difference in UIE between those
who added salt either at the table or during cooking and those who did not. This
study did not detect a relationship between discretionary salt use and UIE,
suggesting that the positive association between UIE and UrNa is due to iodised
Abstract
~ 5 ~
salt present in the food supply. Regular monitoring of population iodine status is
essential as reductions in the amount of iodised salt added to key food sources of
iodine, i.e. bread, may adversely impact iodine intakes.
The results from these four studies provide a novel contribution to the
current evidence base surrounding assessment of iodine nutrition in Australia post-
fortification of bread with iodised salt. The findings of the systematic review
indicate that the urinary volume of children may need to be considered in studies
assessing the iodine nutrition of populations. In addition, the findings from the
remaining three studies which used an objective measure of total iodine intake, 24-
hour urinary excretion of iodine, confirmed the results of the recent 2011-2013
Australian Health Survey. Furthermore, the results from this thesis provide
evidence that the mandatory fortification of bread with iodised salt may be
contributing to the total iodine intakes of Australian schoolchildren. It is therefore
imperative that population sodium and iodine intakes continue to be monitored
using an objective measure of intake, i.e. 24-hour urinary excretion, in order to
ensure that a reduction in sodium intakes to decrease dietary related disease risk
does not put Australian schoolchildren at risk of iodine deficiency
~ 6 ~
~ 7 ~
Chapter One: Introduction
Iodine is an essential trace element found in low concentrations in the soil,
air and sea (3-5). Due to the important role which iodine plays in the production of
thyroid hormones, which are vital in the growth and development of the brain and
central nervous system (3-5), iodine deficiency has been linked to impaired growth
and cognition in schoolchildren (6, 7). In less economically developed regions of the
world, severe iodine deficiency during pregnancy and childhood has been linked
with the development of goiter and cretinism (8, 9).
The iodine content of foods varies depending on the iodine content of the
soil where it is grown (10). The concentration of iodine in the soil can further vary
depending on regional variations in soil solubility, as well as exposure to rain, snow
and glaciation (10). In Australia specifically, the iodine content of plant foods is
particularly low (<20-280 μg /kg fresh weight (11)). due to the impact of glaciation
on the iodine content of the soil during the last ice age (12). This, in combination
with the low iodine content of the drinking water (13), has contributed to the history
of iodine deficiency in Australia, particularly in the island state of Tasmania where
iodine deficiency was documented in the early 1960s (13, 14).
Historically, population monitoring of iodine nutrition was limited to the
assessment of thyroid size and goiter prevalence in school-aged children (15).
However, in the early 1990s it was established that the assessment of median
urinary iodine concentration (UIC) measured in spot urine samples provided an
accurate reflection of population iodine status. Whilst spot urine samples are the
easiest and most commonly used method for assessing iodine nutrition, they are
not able to provide an accurate estimate of the actual iodine intake of a population
as they do not capture variations in iodine excretion over the course of the day (16-
19) (20, 21). Comparatively however, the use of a 24-hour urine sample to determine
urinary iodine excretion (UIE) in μg/24-hour allows for a good estimate of recent
iodine intake as approximately 90% of ingested iodine is excreted within 24-48
hours (22-26). In order to measure daily iodine intake, a complete 24-hour urine
sample is recommended as it is able to capture variations in iodine excretion over
Introduction
~ 8 ~
the course of the day (25, 27, 28), however their use in large population based studies
is limited due to the high subject burden associated with collecting 24-hour urine
samples. Spot urine samples are the easiest and most commonly used method for
assessing iodine nutrition (29-35), with a small number of more recent studies using
24-hour urine samples to measure the iodine intakes of larger groups (36)
Current recommendations for assessing the severity of iodine deficiency of
populations define iodine sufficiency based on a population median UIC (µg/L),
measured in spot urine samples from school-aged children, >100µg/L (37). These
recommendations are based on the assumption that the median UIC can be used
as a surrogate index of the daily iodine intake of individuals within the population
(38). However a review by Zimmerman and Andersson (2012) highlighted that this
assumption would only be true if total daily urine volume was equivalent to 1L (15).
In populations where the urine volume is substantially less than 1L, for example
young children, the use of UIC as a surrogate index of daily iodine intake may result
in the overestimation of intakes. As such, it is currently not clear whether it is
appropriate for UIC to be used as a surrogate index of daily iodine intake in
populations such as young children or adults where the average urine volume may
be less than or in excess of 1L (15). Furthermore, the average urine volume of school-
aged children, the population group recommended for use in iodine monitoring
programs, has yet to be systematically evaluated. Such information could help in
determining appropriateness of spot urine samples for estimating the iodine
intakes of populations where the daily urine output is not 1L.
Prior to the 21st century, monitoring of iodine deficiency in Australia was
scarce and was limited to studies in small sample sizes (<100 participants) (12, 13, 39).
As endemic goiter was largely limited to Tasmania, monitoring of iodine nutrition
was focused on the island state until the early 1990s (12-14, 40). However, following
the detection of iodine deficiency in a small sample of pregnant women in Sydney
in the late 1990s (33) a number of studies began to document iodine deficiency in
other regions of Australia, using spot urine samples in school-aged children (34, 41-
43). In response to this, Food Standards Australia New Zealand (FSANZ) legislated
that all salt added during commercial bread production be replaced by iodised salt
from October 2009 (44). Whilst this fortification strategy was limited to bread
Introduction
~ 9 ~
products, excluding organic and homemade varieties, it was also recommended
that iodised salt replace non-iodised salt in other foods, where possible, at the
manufacturer’s discretion.
Studies conducted post-fortification have determined that the iodine status
of the Australian population has returned to sufficiency (29, 45-47). Specifically, the
2011-13 Australian Health Survey (AHS) observed a median population UIC of 2-18
year olds 16% higher than the population median UIC determined as part of the
National Iodine Nutrition study in 2003/4 (124 µg/L vs. 104 µg/L) (34, 48). It is
important to note, however, that these studies have focused only on estimating
median UIC from spot urine samples, with no studies using 24-hour urine samples
to determine the iodine intakes of a sample of Australian schoolchildren post-
fortification. The 2011-13 AHS collected 24-hour food recalls and spot urine
samples from a representative sample of the population (45). Whilst these methods
are able to provide valuable insight into the food sources of iodine and the iodine
status of the population, they may not provide an accurate estimate of daily iodine
intake. Due to the wide variation in iodine excretion both within and between
individuals throughout the day (16, 18, 19), spot urine samples are unable to provide
an accurate reflection of daily iodine intake. In addition, limitations associated with
the use of food databases for estimating the iodine content of foods impact the
ability of food recalls for estimating total iodine intake (15, 49, 50). Food recalls, can
however, provide an indication of the main food sources of iodine in a population.
Prior to the introduction of mandatory fortification of bread with iodised
salt in 2009, milk was the main food source of iodine (~30-60%) amongst Australian
school-aged children (51), as iodine containing sanitisers used during milk processing
leached into the milk increasing its iodine content (52). However, after the detection
of thyrotoxicosis in two groups of Tasmanian adults in the 1970s (40, 53), the use of
these sanitisers declined over the next two decades (13). This was believed to be the
primary factor influencing the emergence of iodine deficiency in the Australian
population in the late 1990s (52). However, the 2011-13 AHS observed that milk was
still the highest contributor to total daily iodine intake amongst school-aged
children, as measured using 24-hour food recalls, with 27% and 25% of dietary
iodine coming from dairy milk amongst 4-8 and 9-13 year olds, respectively (45). The
Introduction
~ 10 ~
contribution of milk to total dietary iodine was similar to that observed for bread,
which accounted for 27% and 23% of daily iodine intake, among 4-8 and 9-13 year
olds, respectively (45).
The iodine content of bread in Australia is primarily influenced by the
iodised salt added during processing (54). Whist there is no recommended amount
of salt which should be added, the salt content of commercially available breads in
Australia ranges from 0.5-2mg/100g (55). In addition, the iodine concentration of
this salt varies between 25-65 mg/kg of salt (15-40 ppm iodine) (56), indicating that
the iodine content of commercially produced bread can vary up to tenfold (0.013 -
0.13 µg I/100g bread). Due to the well-established links between high salt intakes
and adverse health outcomes, including cardiovascular disease (57), it has become
increasingly important to implement strategies to reduce population salt intake.
The World Health Organization (WHO) recommends a reduction in salt intake to
<5g (2 g sodium)/day among adults by 2025 worldwide with a further reduction to
<2g (0.8g sodium)/day recommended for children (58). In Australia, the
establishment of salt reduction targets for nine food categories, including bread,
by the Federal Government’s former Food and Health Dialogue (FHD) in 2009
resulted in a 10% reduction in the sodium content of commercially available breads
over four years (59). As such strategies may have an adverse impact on iodine
intakes, it is important to understand the association between the major food
sources of iodine, including iodised salt added both during processing and as
discretionary salt (i.e. added at the table or during cooking), and iodine intakes of
Australian school-aged children.
It is important to understand the relationship between the major food
sources of iodine, particularly bread, milk and iodised salt added either during
processing or as discretionary salt (i.e. at the table and/or during cooking), and
iodine intakes. To date, there have been no studies examining the relationship
between these food sources and an objective measure of total iodine intake, i.e.
24-hour urinary excretion of iodine. Such studies will help to determine the success
of iodine fortification strategies, as well as the potential impact which sodium
reduction strategies may have on the iodine intakes of Australian schoolchildren.
Furthermore, it is important to establish the relationship between foods which are
Introduction
~ 11 ~
not reliant on iodised salt, such as milk, and total iodine intake, as an increase in
the consumption of these foods could help alleviate the impact which a reduction
in the iodised salt content of bread may have on iodine intakes.
The overall aims of this thesis were to i) assess the average urine volume of
school-aged children to inform population estimates of iodine intake; ii) determine
the iodine intakes of a sample of Australian schoolchildren using an objective
measure of total daily iodine intake, post-fortification of bread with iodised salt,
and identify socio-demographic characteristics associated with iodine intake, and
iii) determine the association between the major food sources of iodine and total
iodine intake as measured using 24-hour urine samples. More specifically, Study 1
(Chapter 3) estimated the average 24-hour urine volume of children and
adolescents, through a meta-analysis of studies conducted in healthy children and
adolescents (>1y and <19y). The remaining studies in this thesis utilised data from
the Salt and Other Nutrient Intake in Children (SONIC) study, described in Chapter
4. The first study using this data, Study 2 (Chapter 5) determined the total daily
iodine intake of a sample of Victorian schoolchildren on one day utilising 24-hour
UIE and to assess differences across age, gender, and socioeconomic status. Study
3 (Chapter 6) built on the findings of Study 2, by: i) determining the dietary intake
and food sources of iodine in a sample of Victorian schoolchildren, and ii) assessing
the association between the major food sources of iodine, including bread and
milk, and urinary excretion of iodine over a 24-hour period. Finally, Study 4 (Chapter
7) combined the findings of studies 3 and 4 to examine the relationship between
urinary excretion of iodine (UIE) and sodium (UrNa), as a measure of the intakes of
these two nutrients. An additional aim of this study was to assess whether there
was an association between discretionary salt use, i.e. salt added at the table or
during cooking, and UIE.
~ 12 ~
~ 13 ~
Chapter Two:
Review of the Literature
2.1 Background
Iodine is an essential trace element found in low concentrations in soil, air
and the sea (3-5). Iodine is most abundant in oceans, however movement of iodine
from the ocean through glaciation, rain or snow and subsequent transportation by
rivers, floods or wind has led to the accumulation of iodine in surface soil (3-5). The
most abundant source of iodine is seawater, and foods of marine origin have
greater amounts of iodine than plant foods due to the ability of marine animals to
concentrate iodine from seawater (60). Therefore the iodine content of fish varies
based on the seawater which they inhabit (<1 – 400 µg/kg fresh weight (61). In
Australia, the iodine content of plant foods is relatively low and reflects the
concentration of iodine in the soil in which they are grown (<20-280 µg/kg fresh
weight (11)). The iodine concentration of soil is dependent on regional variations in
soil solubility and can be affected by exposure to rain, snow, and glaciation (10).
Areas which experience frequent flooding or soil erosion, such as mountainous
regions or river deltas generally produce foods with poor iodine content, and these
areas are generally associated with iodine deficient populations (62). As such, the
major food sources of iodine can vary considerably both within and between
countries.
2.2 Iodine in the body
Whilst iodine in foods is present mainly in the inorganic form as iodide,
organically bound iodine is most abundant within tissues, with inorganic iodide
present in very low concentrations (3, 5). Therefore, inorganically bound iodide is
easily absorbed in the stomach and upper small intestine and converted to
organically bound iodine (3-5). Organically bound iodine is an essential component
in thyroid hormones, which are synthesised in the body by the thyroid gland (3, 5).
The adult human body contains between 15 and 20 mg of iodine (63). Approximately
Review of the Literature
~ 14 ~
70% of iodine in the body is found in the thyroid gland, nearly 40 times that found
in the plasma under normal circumstances (63). Iodine is an essential component of
the thyroid hormones Thyroxine (T4) (5) and 3,5,3’-Tri-iodothyronine (T3) (5). These
hormones are iodinated derivatives of the amino acid tyrosine, and are essential
for normal growth, metabolism and maturation of the whole body (3, 5).
Specific functions of these hormones include the growth and development
of tissues in the central nervous system (CNS), maintenance of basal metabolic rate
and macronutrient metabolism (3-5). Iodine also plays an important role in a variety
of enzymatic processes in the body, including lipolysis, glycogen synthesis and the
uptake of glucose and galactose from the gastro-intestinal tract (GIT) (4). Iodine is
an essential element, meaning that humans cannot synthesise it and need to obtain
iodine from their diet (3). Once absorbed by the stomach and converted to
organically bound iodine in the upper small intestine, iodine is transported in the
blood to several tissues in the body, including the thyroid gland. In the thyroid gland
iodine is oxidised and added to the thyroxine residues on thyroglobulin to form
iodinated thyroglobulin. This iodinated thyroglobulin then participates in a complex
series of reactions to produce the thyroid hormones T3 and T4 (5). These hormones
are stored in the thyroid gland, with production and secretion controlled by the
level of thyroid-stimulating hormone (TSH) in circulation (5). The absorption and
metabolism of iodine is outlined in Figure 2.1.
When the circulating levels of thyroid hormones are adequate, feedback on
the pituitary gland regulates the production of TSH within normal levels. During
periods of mild iodine deficiency, a decrease in circulating levels of T4 will result in
an increase in the production of TSH by the pituitary gland. This leads to an increase
in iodine uptake by the thyroid gland in order to promote T4 production (5). When
deficiency is severe, circulating levels of both T4 and T3 decline resulting in a
prolonged increase in secretion of TSH by the pituitary. If stimulation of the thyroid
becomes chronic, as in the case of continued severe iodine deficiency, the thyroid
can become enlarged and produce a goiter (9). De-iodination of T4 to T3 is an
irreversible step and results in a release of free iodide back into the plasma iodine
Review of the Literature
~ 15 ~
pool. Here iodide is either taken up by the thyroid gland to produce more thyroid
hormones or it is transported to the kidneys and excreted in the urine (64).
2.3 Iodine intakes and health
2.3.1 Severe consequences of iodine deficiency
In populations where the food supply is not secure or where multiple
nutritional inadequacies are observed, iodine deficicency is often prevalent in its
severest form (8). When iodine intakes are extremely low, severe iodine deficiency
can impact health in a number of different ways. The disorders associated with
severe iodine deficiency are termed “Iodine Deficiency Disorders” (IDD), which can
impact people from all life stages (9). The most severe consequences of iodine
deficiency are endemic goiter and cretinism (9). Severe deficiency during childhood
Figure 2.1: Absorption and metabolism of dietary iodine Adapted from (3-5)
Review of the Literature
~ 16 ~
and adolescence generally presents as endemic goiter (9, 65). The most severe
consequence of iodine deficiency is endemic cretinism, which can manifest as a
result of severe deficiency during pregnancy. Endemic cretinism usually manifests
as severe and irreversible mental retardation, and a combination of one or more
neurological impairments, including deaf mutism, squint, spastic diplegia, motor
rigidity or dwarfism (66).
Whilst endemic goiter remains the most visible consequence of severe
iodine deficiency, of more concern is the impact of iodine deficiency on the brain,
which can occur even in the absence of goiter (65). As thyroid hormones are
essential in the growth and development of tissues in the CNS, a deficiency in
iodine during critical periods of brain development can lead to neurological
impairment, intellectual disability, retarded growth, delayed onset of puberty and
sexual immaturity (65, 67). The severity of endemic cretinism in the newborn can be
impacted by maternal iodine status, as well as the severity and duration of
postnatal iodine deficiency (68). Whilst thyroid goiter may be reversible with long-
term treatment of iodine (69), endemic cretinism is irreversible (70), and is better
treated by prevention and intervention prior to pregnancy, through iodine
supplementation (71, 72).
A recent systematic review of randomised control trials (RCTs) conducted
by Zhou et. al (2013) highlighted the current lack of quality evidence regarding the
effect of iodine supplementation during pregnancy on growth and cognitive
functions in children (72). In this review, 8 of the 14 included studies were high
quality RCTs, of which only two were conducted in areas of severe iodine
deficiency. In these studies it was demonstrated that iodine supplementation
during pregnancy or the peri-conception period reduced risk of cretinism, however
there were no improvements in childhood intelligence, gross development,
growth, or pregnancy outcomes (72). The remaining 6 studies were conducted in
areas of mild to moderate iodine deficiency, 5 in Europe and 1 in rural Chile (72)
however none of these studies reported childhood development or growth
outcomes as a result of iodine supplementation. Instead these studies focused on
the impact of iodine supplementation on the thyroid function of children and their
Review of the Literature
~ 17 ~
mothers. The findings of this review were inconsistent, with no obvious dose-
response relationship demonstrated by any of the 6 studies (72). Whilst this review
demonstrates that there is currently a lack of evidence linking iodine
supplementation to improvements in child growth and development in areas of
mild to moderate iodine deficiency, the results from studies in areas of severe
deficiency highlight the importance of monitoring iodine intakes during pregnancy,
in order to prevent the development of cretinism in the newborn (72).
2.3.2 Mild iodine deficiency
In economically developed countries such as Australia and New Zealand
where the food supply is secure and malnutrition is rare, mild iodine deficiency and
long-term exposure to low level mild iodine deficiencyis of greater concern than
the consequences associated with severe deficiency, as this is seldom observed (8,
15). Deficiency observed in these countries is typically associated with a low
concentration of iodine in the soil, which results in a low concentration of iodine in
food (4, 11). A recent systematic review and meta-analysis of nine RCTs and 8
observational studies investigated the impact of iodine supplementation on
maternal and newborn thyroid function, infant neurodevelopment, and cognitive
performance in school-aged children in populations with mild-moderate iodine
deficiency (73). In this review it was concluded that iodine supplementation was
associated with beneficial effects on cognitive function, even in marginally iodine
deficient areas (73). It is important to note that this review only included 2 RCTs
examining the impact of iodine supplementation on cognitive function in school-
aged children from areas of mild to moderate iodine deficiency and that current
research into the effects of mild iodine deficiency during childhood and
adolescence is fairly limited (6, 7, 73-76). Furthermore, the potential impact of long-
term exposure to mild iodine deficiency in school-aged children using prospective
studies has yet to be investigated.
Most of the literature available investigating the consequences of mild
iodine deficiency in school-aged children consists of cross-sectional and
observational studies (62, 73, 77). One cross-sectional study carried out in a
Review of the Literature
~ 18 ~
representative sample of school-aged children (n=1221, 6-16 years old) in an
economically developed province of southern Spain, found that Intelligence
quotient (IQ) was significantly higher in children with urinary iodine levels above
100 µg/liter (P=0.01) (78). Similar observational studies in areas of mild to moderate
iodine deficiency have also made links between lower iodine intakes and impaired
intellectual function and fine motor skills (79, 80). A study conducted in an iodine
deficient region of Sicily (n=719, 6-12 years old) found that the proportion of
children with learning defects was significantly higher when compared to an iodine
sufficient, goiter free control area in the same region (13.8% vs 3.5%, P<0.0001)(79).
High quality RCTs have attempted to examine the impact of mild iodine
deficiency during childhood (6, 7, 74). One of these studies, a double-blind
intervention trial in 10-12 year old children (n=310) in a mildly iodine deficient
region of rural Albania, found that treatment of iodine deficiency with
supplementation resulted in an improvement in information processing, fine motor
skills and visual problem solving (7). After 24 weeks of supplementation with a single
dose of oral iodised oil (400 mg iodine) it was found that the supplemented group
had significantly improved in 4 out of the 7 cognitive tests, when compared to the
placebo group. Iodine treatment was associated with highly significant
improvements in test scores (P<0.0001) in measures of ability to reason and solve
problems, namely rapid target marking, symbol search, rapid object naming and
Raven’s Coloured Progressive Matrices (mean (95%CI) adjusted treatment effects:
2.8 (1.6, 4.0), 2.8 (1.9, 3.6), 4.5 (2.3, 6.6) & 4.7 (3.8, 5.8), respectively) (7). Although
significant differences in the baseline measurements for the cognitive tests existed
between the two groups (7), with the control group scoring higher in four of the
seven tests of cognitive and motor skills, this study provides strong evidence for
the relationship between iodine intake and cognition.
No RCTs have been conducted investigating the impact of mild iodine
deficiency in Australian children, however one study has been conducted in a
sample of mildly deficient school-aged children from New Zealand (6). This study, a
randomised placebo-controlled double-blind trial, was conducted in 184 10-13
year old children. Cognitive performance was measured using four subtests from
Review of the Literature
~ 19 ~
the Wechsler Intelligence Scale for Children, at baseline and after a 28 week
treatment period. The treatment consisted of a daily supplement of either 150 μg
iodine (equivalent to the recommended daily intake (RDI) for children aged 9-13 (2))
or a placebo. The study found that children in the supplemented group had
significantly improved scores for two of the four cognitive tests, when compared
to the placebo group. Iodine supplementation was found to significantly improve
perceptual reasoning (P<0.05), and the supplemented group had a higher overall
cognitive score when compared to the placebo group after supplementation
(+0.19SDs, P=0.011) (6). Although the study may have been underpowered due to
difficulties recruiting participants and time restraints relating to the introduction of
mandatory fortification, this study does provide evidence that supplementation
with iodine in areas of mild iodine deficiency has a beneficial effect on cognition in
school-aged children. Furthermore, it highlights the impact which iodine deficiency
may have on the growth and development of school-aged children.
Methodological differences and limitations of these studies make it difficult
to compare the results and make an accurate conclusion regarding the potential
impact of mild iodine deficiency on cognitive development in childhood. Both
studies described above were relatively short in duration, and longer treatment
periods may be necessary in order to adequately examine the impact which mild
iodine deficiency may have on cognition in children.
2.3.3 Excessive iodine intakes
Although iodine is an important nutrient component of multiple processes
and functions in the body, excessive intakes have also been linked with increased
prevalence of goiter (81, 82) and impaired thyroid function (83, 84). Such intakes (>300
µg/day) are generally observed in populations where consumption of iodine-rich
seaweeds is high, such as China (81, 82), and are not usually observed in countries
such as Australia and New Zealand. Recently however, the impact of mandatory
fortification of foods with iodised salt has been linked with an increase in the
prevalence of excessive iodine intakes in America (85), Brazil (86), and Australia (47).
Long-term increased thyroid hormone levels could lead to the development of
Review of the Literature
~ 20 ~
hyperthyroidism and other autoimmune disorders, which may have a life-long
impact on health and well-being (87).
2.3.4 Recommended Dietary Intakes for iodine: Australia and New
Zealand and determination of individual iodine requirements
The Australian National Health and Medical Research Council (NHMRC)
have provided a set of iodine intake requirements (Table 2.1) (2). These individual
based recommendations vary based on age group and gender, as iodine
requirements differ across the lifespan (2). The iodine Estimated Average
Requirement (EAR) for adults was determined from accumulation and turnover
studies which related urinary iodide to thyroid volume and indicated that iodine
balance is achieved at intakes between 85-100µg/day (63, 88). As such, the EAR was
set at 100µg/day. The RDI was set assuming a CV of 20% for the EAR, and rounded
up to reflect the possible influence of natural goitrogens (2, 89). The Upper Level of
intake for adults was set based on studies which observed extremely low serum
TSH levels (associated with impaired thyroid function) in adults after administration
of supplemental iodine at 1,800 µg/day and 1,700 µg/day (90, 91).
Recommendations for children were based on iodine balance studies for
the age groups 1–3 years, 4–8 years and 14–18 years (92, 93) and by extrapolation
from adults on the basis of metabolic weight [(bodyweight)0.75] for 9–13 year olds
(92, 93). The RDI was set assuming a CV of 20% for the EAR from studies in adults and
rounded (2). Finally, the UL for children and adolescents was determined through
extrapolation of the adult recommendation on a metabolic weight basis (2).
Table 2.1: Daily iodine intake recommendations for children and adolescents - Australia and New Zealand (µg/day) (2)
EAR RDI UL
1-3 y/ols 65 90 200
4-8 y/old 65 90 300
9-13 y/old 75 120 600
14-18 y/old 95 150 900
EAR: estimated average requirement; RDI: recommended dietary intake,
UL: upper level of intake
Review of the Literature
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2.4 Assessment of iodine nutrition
Since the 1960s school-aged children, usually defined as children 6-12 years
of age, have been the most commonly used target group for iodine monitoring
surveys as they are readily accessible, a representative sample can be obtained as
most children attend school even in low-income countries, they are particularly
vulnerable to goiter, and goiter is more responsive to treatment in children when
compared to adults (15). Historically, the iodine nutrition of populations was
primarily assessed using assessment of thyroid size to determine goiter rate and
urinary excretion of iodine (as approximately 90% of ingested iodine is excreted in
the urine within 24-48 hours (64, 94, 95)). Whilst urinary iodine concentration
measured in random spot urine samples continues to be the preferred method for
assessing the iodine nutrition of populations, the assessment of thyroid size is more
commonly used at a clinical level to assess the iodine nutrition of individuals, as it
is more reflective of long-term iodine nutrition (months to years)(96, 97). At the
individual level, assessment of serum thyroid hormone levels (TSH and
Thyroglobulin (Tg)) are used to provide an indicator of intermediate iodine
nutrition (weeks to months)(98). The following sections will focus on the methods of
assessing the iodine nutrition of population: measurement of thyroid size and
urinary iodine excretion.
2.4.1 Assessment of Thyroid size
Prior to the 1980s assessment of thyroid size by palpation or ultrasound to
determine goiter rate was the primary method used to assess the iodine nutrition
of populations (15). The use of goiter rate in iodine nutrition monitoring can be
traced back to the early 1500s (99, 100), however it was not until a joint Pan American
Health Organization (PAHO) and World Health Organization (WHO) meeting in
1983 that the first official system of classification of goiter rate by thyroid palpation
was proposed (101). Following this the WHO, along with the United Nations
Children’s Fund (UNICEF) and the International Council for the Control of Iodine
Deficiency Disorders (ICCIDD), published a simplified grading system in 1993, which
formed the basis of the current day goiter classification criteria (102, 103). In addition,
Review of the Literature
~ 22 ~
it was recommended that the goiter rate within populations also be used to define
iodine deficiency as follows: <5%, iodine sufficiency; 5–19%, mild deficiency; 20–
29%, moderate deficiency; and >30%, severe deficiency (103).
Following recommendations by the WHO in 1993 (102), a number of
countries introduced universal salt iodisation (USI) as a strategy to address the
growing concern of iodine deficiency (8). The implementation of these strategies
lead to the observation that although thyroid size decreased as iodine intakes
increased, it could take months or even years for a thyroid to return to normal after
correction of iodine deficiency (104-106). In addition, there is considerable
intraindividual variation in the ability of the thyroid to adapt to iodine prophylaxis
(107). Furthermore, measurement of thyroid size requires substantial training and
differences in technique can result in large intraobserver errors (108). As such, the
use of goiter rate to assess the iodine nutrition of populations where salt iodisation
strategies have been introduced could result in an overestimation of the
prevalence of iodine deficiency (104-106).
2.4.2 Urinary iodine
It is estimated that approximately 90% of ingested iodine is excreted in the
urine within 24-48 hours, with only minimal losses in sweat and faeces (64, 95, 109). As
such, 24-hour urine samples are able to provide a good estimate of recent iodine
intake. This method allows for the determination of 24-hour urinary iodine
concentration (24-hour UIC, µg/L) and 24-hour urinary iodine excretion (24-hour
UIE), expressed as µg/24-hour. The determination of 24-hour UIE is widely
regarded as the most appropriate method for measuring the daily iodine intake of
a population (23, 25, 26, 110, 111).
Although it is recognised that to measure the iodine intake of an individual
a minimum of 10 days of 24-hour urine collections are required (23), for the
assessment of mean intake within a population a single 24-hour urine can be used
for group level assessment (28). Early recommendations by the WHO suggested the
use of 40-50 subjects to determine the mean concentration of iodine in a given
Review of the Literature
~ 23 ~
region (112), however more recent recommendations by the WHO do not specify
the recommended number of participants for use in population studies (37, 38).
Due to the practical difficulties associated with collecting 24-hour urine
samples, such as high participant burden and financial costs, the WHO recommend
the use of casual, spot urine samples as an appropriate indicator of iodine status in
populations (37). Iodine excretion from spot urine samples is most often expressed
as a concentration (spot UIC, µg/L) (37), or as a ratio to creatinine excretion (I/Cr, µg
iodine/ g creatinine) (113-115). Estimation of daily iodine intake from spot urine
samples through extrapolation based on daily creatinine excretion was a commonly
used method for determining the iodine status of populations prior to the 1990s
(101, 116-118). This method involves the calculation of estimated daily UIE from spot
urine samples on an individual basis, based on standard creatinine excretion values
(119, 120) using the following formula (111):
The use of I/Cr to estimate daily iodine intake was believed to provide an
accurate estimate of daily iodine excretion from spot urine samples as creatinine,
an endogenous indicator of lean body mass, is relatively constant from day to day
in healthy adult populations (121, 122). Whilst this is true in adults, estimating
expected creatinine excretion values for children can be difficult as creatinine
excretion can be affected by muscle mass, age, gender, ethnicity and onset of
puberty (123). Some equations for estimating daily creatinine excretion are able to
account for these factors, whilst others provide a more crude estimate of daily
creatinine excretion (111).
Whilst some studies have determined that 24-hour urine samples are more
likely to capture the full range of iodine excretion throughout the day when
compared to UIE estimated from spot urine samples (18, 23, 113), there are
inconsistencies in the methods used between studies. Table 2.2. provides a
comprehensive summary of studies which have compared UIE estimated from spot
Estimated 24-hour urinary iodine excretion (estUIE)
measured in spot urine samples
Creatinine (g/L)
Iodine (µg/L) X
Predicted 24-hour Cr excretion (g/day)
from established reference values
(119 ,120)
=
Review of the Literature
~ 24 ~
urine samples to daily iodine intake measured in 24-hour urine samples (18, 23, 111,
113-115, 124-127). These studies have estimated daily iodine intake from spot urine
samples (estUIE) through extrapolation based on creatinine excretion. Whilst most
studies utilised spot and 24-hour urine samples collected on the same day (18, 23, 111,
113, 115, 124, 125), some studies collected the spot and 24-hour samples on different
days (114, 126-128). Furthermore, there are discrepancies in the use of fasting and non-
fasting spot urine samples between studies. Finally, these studies were also limited
to relatively small sample sizes and the inclusion of wide age ranges. Aside from
these limitations, the studies described in Table 2.2. demonstrate that when daily
iodine intake is estimated from spot urine samples, through extrapolation based
on creatinine excretion, there is considerably more within person variation than
iodine intake measured in 24-hour urine samples (18, 23, 111, 113-115, 124-126). Studies
utilising both morning fasting (18, 23) and random non-fasting (113) spot urine samples
have found that, on average, iodine intake determined from spot urine samples is
significantly lower than iodine intake determined from 24-hour urine samples by
up to 20% (range 10-20%, P<0.001), and is largely dependant on the time of day
when the urine sample is collected(18, 23, 113).
A 2014 study by Perrine et.al. demonstrated that the I/Cr should not be
used interchangeably with observed UIE when estimating the iodine intakes of a
population (111). In this study of 18-39 year olds (n=400), UIE and UIC were both
determined from 24-hour urine samples and compared to daily iodine intake
estimated from morning spot urine samples and spot UIC. It was determined that
the the estimated daily iodine intake was consistently and substantially lower than
daily iodine intake determined in the 24-hour urine samples and varied significantly
by age, sex, ethnicity and anthropometric measures (111). Furthermore it has been
demonstrated in children that as age increases, so too does the I/Cr as a result of
the decrease in creatinine excretion associated with an age related decline in lean
body mass(114). As this increase is related more to a change in creatinine excretion
and less to an increase in iodine excretion, the use of the I/Cr could result in the
misclassification of the iodine intakes of populations of children (129).
Review of the Literature
~ 25 ~
Whilst the variation in individual iodine excretion between days is largely
dependant on the iodine content of the diet, iodine excretion has also been found
to vary over the course of the day in individuals (18, 23, 111, 113-115, 124-126). One study
conducted in 42 adults and children (aged 4-60 years) found that urinary iodine
excretion varied significantly by timing of collection (P<0.001), with lowest levels
occurring in the morning and peaks observed following meals (16). Whilst both inter
and intra individual variations in iodine excretion have been examined in adult
populations (18, 23, 111, 113-115, 124-126), to date there have been no studies examining
the inter and intra individual variation in iodine excretion in children.
A recent systematic review of studies comparing spot and 24-hour urine
samples for estimating the iodine intakes of a population concluded that there is
currently not enough evidence to determine whether iodine intake determined
from spot urine samples provides an accurate reflection of daily iodine intake, as
measured using 24-hour urine samples (27). As such, the measurement of observed
24-hour urinary iodine excretion (24-hour UIE) is currently the most appropriate
method for determining the iodine intakes of children (15). Spot urines continue to
be the most widely used method of measuring the iodine status of school-aged
children in Australia (6, 29, 32, 34, 35, 42, 130-132) and New Zealand (35, 133-136), due to their
low cost and minimal respondent burden. To date there have been no studies
utilising 24-hour urine samples to measure the iodine intakes of school-aged
children in Australia. Such studies will help identify populations at risk of iodine
deficiency and/or excess and allow for the implementation of appropriate
strategies. In addition such studies can help evaluate the impact of various public
health strategies, such as iodine fortification or the application of sodium reduction
targets to major food sources of iodine, on the iodine intakes of the population.
Stu
dy
Co
un
try
Sam
ple
M
eth
od
olo
gy
Mai
n f
ind
ing
Vo
ugh
t et
. al.
(19
63)
(124
) U
.S.
n=6
(4
mal
e, 2
fem
ale)
yo
un
g ad
ult
s
(age
no
t d
escr
ibed
)
Twen
ty-f
ou
r h
ou
r u
rin
es
colle
cted
dai
ly f
or
24
day
s.
Co
ncu
rren
t d
aily
sp
ot
uri
ne
sam
ple
s id
enti
fie
d a
s fa
stin
g,
mid
day
or
nig
ht
ob
tain
ed
.
estU
IE f
rom
all
spo
t u
rin
e sa
mp
les
no
t si
gnif
ican
tly
dif
fere
nt
fro
m o
bse
rved
24
-ho
ur
UIE
.
Frey
et.
al.
(19
73)
(125
) N
orw
ay
n=6
2
(33
mal
e, 2
9 f
emal
e)
20
-64
y/o
ld
Sin
gle
24
-ho
ur
uri
ne
spec
imen
co
llect
ed.
5m
L o
f u
rin
e fr
om
a s
ingl
e vo
id b
etw
een
no
on
an
d 6
p. m
. o
n t
he
sam
e d
ay t
ake
n a
s n
on
-fas
tin
g af
tern
oo
n s
po
t u
rin
e sa
mp
le
Stro
ng,
sig
nif
ican
t co
rrel
atio
n b
etw
een
ob
serv
ed 2
4-h
ou
r U
IE e
stU
IE f
rom
no
n-f
asti
ng
afte
rno
on
sp
ot
sam
ple
(m
ales
: r=0
.69
, P=0
.00
1; f
emal
es: r
=0.6
8, P
=0.0
05
).
Kon
no
et.
al.
(19
93)
(114
) Ja
pan
n=2
2
(9 m
ale,
13
fem
ale)
m
ean
(SD
) ag
e 5
2 (
19
) ye
ars
Mo
rnin
g fa
stin
g sp
ot
uri
ne
colle
cted
pri
or
to 2
4-h
ou
r u
rin
e co
llect
ion
. All
uri
ne
void
ed o
ver
follo
win
g 2
4-h
ou
rs
colle
cted
Stro
ng,
sig
nif
ican
t co
rrel
atio
n b
etw
een
ob
serv
ed 2
4-h
ou
r U
IE a
nd
est
UIE
fro
m m
orn
ing
fast
ing
spo
t sa
mp
le (
r=0
.83
, P
<0.0
01
). N
o s
ign
ific
ant
corr
elat
ion
bet
wee
n e
stU
IE f
rom
n
on
-fas
tin
g sp
ot
sam
ple
s an
d o
bse
rved
24
-ho
ur
UIE
Tho
mso
n e
t.
al. (
1996
) (1
23)
New
Ze
alan
d
n=6
1
(30
mal
e, 3
1 f
emal
e)
18
-58
y/o
ld
Mo
rnin
g fa
stin
g sp
ot
uri
ne
colle
cted
pri
or
to 2
4-h
ou
r u
rin
e co
llect
ion
. All
uri
ne
void
ed o
ver
follo
win
g 2
4-h
ou
rs
colle
cted
into
sep
arat
e co
nta
iner
s. T
he
last
of
the
se
sam
ple
s w
as a
mo
rnin
g fa
stin
g u
rin
e. E
ach
vo
id
con
sid
ere
d a
sin
gle
spo
t u
rin
e sa
mp
le. O
ne
-fif
th o
f ea
ch
void
was
po
ole
d t
o g
ive
a re
pre
sen
tati
ve 2
4-h
ou
r sa
mp
le.
Stro
ng,
sig
nif
ican
t co
rrel
atio
n b
etw
een
est
UIE
fro
m
mo
rnin
g fa
stin
g sp
ot
sam
ple
an
d o
bse
rved
24
-ho
ur
UIE
(r
=0.7
4, P
<0
.00
1).
N
o s
ign
ific
ant
corr
elat
ion
be
twee
n o
bse
rved
24
-ho
ur
UIE
an
d e
stU
IE f
rom
no
n-f
asti
ng
spo
t sa
mp
les.
Ras
mu
ssen
et.
al
. (19
99)
(18)
Den
mar
k n
=22
(9
mal
e, 1
3 f
emal
e)
30
-55
y/o
ld
All
uri
ne
void
ed
ove
r 2
4 h
ou
rs c
olle
cted
into
sep
arat
e co
nta
iner
s. E
ach
vo
id c
on
sid
ered
a s
ingl
e sp
ot
sam
ple
. Io
din
e ex
cre
tio
n in
eac
h v
oid
fro
m e
ach
su
bje
ct
sum
mar
ised
to
de
term
ine
ob
serv
ed 2
4-h
ou
r U
IE.
Ob
serv
ed 2
4-h
ou
r U
IE c
om
par
ed w
ith
est
UIE
det
erm
ined
fr
om
sp
ot
uri
ne
sam
ple
s at
dif
fere
nt
tim
es
of
the
day
.
estU
IE f
rom
mo
rnin
g fa
stin
g sp
ot
uri
ne
sam
ple
si
gnif
ican
tly
low
er t
han
ob
serv
ed 2
4-h
ou
r U
IE (
mea
n±S
D
11
1±5
8 v
s. 1
39
±59
µg/
day
, P=
0.0
06
).
No
sig
nif
ican
t d
iffe
ren
ce b
etw
een
ob
serv
ed 2
4-h
ou
r U
IE
and
est
UIE
fro
m n
on
-fas
tin
g u
rin
e sa
mp
les.
St
ron
g, s
ign
ific
ant
corr
elat
ion
bet
wee
n e
stU
IE f
rom
m
orn
ing
fast
ing
sam
ple
, fir
st s
amp
le a
fter
mo
rnin
g an
d
even
ing
sam
ple
s an
d o
bse
rve
d 2
4-h
ou
r U
IE. (
r=0
.70
, P
<0.0
01
, r=0
.74
, P<0
.00
1, r
=0.6
7, P
=0.0
01
, res
pec
tive
ly).
~ 26 ~
Review of the Literature
Tabl
e 2.
2: S
tud
ies
com
pari
ng
spo
t vs
. 24
-ho
ur
uri
nes
as
a m
easu
re o
f u
rina
ry io
din
e ex
cret
ion
(U
IE)
Stu
dy
Co
un
try
Sam
ple
M
eth
od
olo
gy
Mai
n f
ind
ing
Knu
dse
n e
t. a
l. (2
000
) (1
13)
Den
mar
k
n=3
1
(24
mal
e, 7
fem
ale)
2
7-7
1 y
/old
All
uri
ne
void
ed
ove
r 2
4-h
ou
rs c
olle
cted
be
twee
n 2
-6
tim
es p
er p
arti
cip
ant.
Si
ngl
e co
ncu
rren
t ra
nd
om
no
n-f
asti
ng
spo
t u
rin
e sa
mp
le
colle
cted
on
th
e sa
me
day
as
each
24
-ho
ur
uri
ne
sam
ple
.
est
UIE
fro
m s
po
t sa
mp
les
sign
ific
antl
y lo
wer
th
an
ob
serv
ed 2
4-h
ou
r U
IE (
med
ian
(P
5 –
P9
5)
12
6 (
58
-31
9)
vs.
14
3 (
75
-29
7)
µg/
day
, P=0
.03
) St
ron
g si
gnif
ican
t co
rrel
atio
n b
etw
een
est
UIE
fro
m n
on
-fa
stin
g sp
ot
uri
ne
sam
ple
s an
d o
bse
rved
24
-ho
ur
UIE
(r
=0.6
2, P
<0
.05
).
Kön
ig e
t. a
l. (2
011
)(23)
Swit
zerl
and
n
=22
fem
ales
5
2-7
7 y
/old
All
uri
ne
void
ed
ove
r 2
4-h
ou
rs c
olle
cted
bi-
we
ekly
fo
r 1
5
mo
nth
s
Smal
l am
ou
nt
of
corr
esp
on
din
g fa
stin
g, s
eco
nd
-vo
id,
mo
rnin
g sp
ot
uri
ne
sam
ple
s co
llect
ed
on
th
e sa
me
day
as
the
24
-ho
ur
uri
ne
sam
ple
use
d a
s th
e fa
stin
g sp
ot
sam
ple
fo
r es
tUIE
de
term
inat
ion
.
estU
IE f
rom
fas
tin
g sp
ot
sam
ple
s w
as 1
6%
low
er t
han
th
e o
bse
rved
24
-ho
ur
UIE
(m
ean
±SD
86
±33
vs.
10
3±2
8
µg/
day
, P<0
.00
1).
Bla
nd
-Alt
man
an
alys
is r
evea
led
th
at
estU
IE f
rom
fas
tin
g sp
ot
sam
ple
was
16
mg/
24
-ho
ur
low
er
than
ob
serv
ed 2
4-h
ou
r U
IE. T
he
95
% li
mit
s o
f ag
reem
ent
(±1
.96
SD
) w
ere
-57
an
d 2
4 µ
g/2
4-h
ou
r o
f th
e in
div
idu
al
mea
ns
and
-1
25
an
d 9
3 µ
g/2
4 h
of
the
ove
rall
mea
ns.
Per
rin
e et
. al.
(20
14)(1
11)
U.S
.
n=3
97
(1
85
mal
e, 2
12
fe
mal
e)
18
-39
y/o
ld
All
uri
ne
void
ed
ove
r 2
4-h
ou
rs c
olle
cted
into
sep
arat
e co
nta
iner
s. A
pro
po
rtio
nal
aliq
uo
t fr
om
eac
h v
oid
was
ta
ken
to
cre
ate
a co
mp
osi
te 2
4-h
ou
r u
rin
e sa
mp
le.
Fou
r n
on
-fas
tin
g ti
me
d s
po
t u
rin
e sa
mp
les
wer
e al
iqu
ote
d f
or
anal
ysis
.
estU
IE f
rom
sp
ot
sam
ple
s n
ot
sign
ific
antl
y d
iffe
ren
t fr
om
ob
serv
ed 2
4-h
ou
r U
IE a
t an
y o
f th
e ti
me
po
ints
(m
ean
(95
% C
I) c
ross
ed 0
fo
r al
l tim
e p
oin
ts).
Mo
nte
neg
ro-
Bet
han
cou
rt
et. a
l. (2
015
) (1
15)
Ger
man
y n
=18
0
(90
mal
e, 9
0 f
emal
e)
6-1
8 y
/old
All
uri
ne
void
ed
ove
r 2
4-h
ou
rs c
olle
cted
. C
on
curr
ent,
ran
do
m n
on
-fas
tin
g sp
ot
uri
ne
sam
ple
s w
ere
colle
cted
on
th
e sa
me
day
as
the
24
-ho
ur
colle
ctio
n.
Mo
der
ate,
sig
nif
ican
t co
rrel
atio
n b
etw
een
ob
serv
ed 2
4-
ho
ur
UIE
an
d e
stU
IE f
rom
no
n-f
asti
ng
spo
t u
rin
e sa
mp
le
(6-1
2 y
/old
s: r
=0
.41
, P<
0.0
01
; 1
3-1
8 y
/old
s: r
=0.4
7,
P<0
.00
1).
~ 27 ~
Review of the Literature
Tabl
e 2.
2: S
tud
ies
com
pari
ng
spo
t vs
. 24
-ho
ur
uri
nes
as
a m
easu
re o
f u
rina
ry io
din
e ex
cret
ion
(U
IE)
Review of the Literature
~ 28 ~
2.4.3 WHO recommendations for assessing the iodine status of
populations
The development of the current recommendations for assessing the iodine
nutrition of populations using spot urine samples evolved over a number of years,
however the use of UI as an indicator of the iodine status of populations was first
introduced in 1983 by the PAHO and WHO working group on iodine deficiency (101).
Recognising the issues associated with focusing on goiter assessment alone, these
recommendations proposed that iodine nutrition be described by a combination
of goiter rate and measurement of UI in spot urine samples. As spot samples are
unable to provide an estimate of total iodine intake, initial recommendations were
based on excretion of iodine per gram of creatinine, as this was believed to provide
a proxy estimate of daily iodine excretion and thus intake (101).
A key study informing the recommendations issued by the PAHO/WHO
working group in 1983 was conducted in 1970 in a study that included both children
and adults (n=21,000) from 186 regions of Central America (117). This study
examined the relationship between estUIE from spot urine samples, and goiter rate
estimated by thyroid palpation. The study found that goiter rate was >10% in i) all
areas in which the mean estUIE was <25 µg/day; ii) most areas in which the mean
estUIE was 25-49 µg/day; iii) approximately a third of areas where the mean estUIE
was 50-99 µg/day and; iv) virtually none of the areas in which the mean estUIE was
>100 µg/day (117). It is important to note, however that the exact creatinine
excretion values used to determine the estUIE in this study are not clear, nor
whether intakes determined were adjusted for the age of the participants.
Furthermore, the intakes of 25, 50, and 100 µg/day associated with varying levels
of goiter rate in the population were determined for the population as a whole,
with the results for both children and adults pooled together in one overall
estimate. Whilst the study did report a negative correlation between age and goiter
rate, the relationship between estUIE and goiter rate was not broken down by age
(117). Therefore, as iodine requirements vary with age (2), the mean estUIE of 100
µg/day associated with reduced goiter prevalence in this population of children and
Review of the Literature
~ 29 ~
adults may not be reflective of the true estUIE associated with reduced goiter
prevalence in either children or adults independently.
Regardless of these potential inaccuracies, the PAHO/WHO recommended
in 1986 that the degree of iodine deficiency in a population be defined using spot
urine samples collected from school-aged children, and were based on the cutoffs
of 25, 50, and 100µg/day determined by the study in Central America (101). The
recommendations were as follows: “Grade 1: goiter endemias with an estimated
mean UIE of greater than 50 mg/g creatinine - at this level of iodine intake, no
thyroidal or developmental abnormalities are anticipated; Grade 2: goiter
endemias with an estimated mean UIE in the range of 25–50 mg/g creatinine - this
group is at risk for hypothyroidism but not for overt cretinism; and grade 3: goiter
endemias with an estimated mean UIE of <25 mg/g creatinine - there is a high risk
for endemic cretinism in such a population.”(101)
Following the publication of these recommendations in 1986, a study by
Pierre Bourdoux in 1988, demonstrated the inaccuracies associated with the use of
estUIE from spot urine samples for classifying daily iodine intakes of populations
(118). Furthermore, Bourdoux demonstrated that UIC did not follow a normal
distribution in populations, and that the use of mean UIC to describe the severity
of iodine deficiency in a population was inappropriate. As such, Bourdoux
suggested that UI determined from casual urine samples in children be expressed
solely as the median concentration, in µg iodine/L urine. In addition, he
recommended that the severity of iodine deficiency be described based on the
proportion of individuals, either children or adults, within a population with a UIC
below 20, 50 and 100 µg/L, as this would provide researchers with a more complete
picture of the true extent of iodine deficiency within the population (118). Based
primarily on these two studies and the finding that goiter rate was <10% in
populations where mean estimated UIE was >100 µg/day, in 1993 the WHO
endorsed the use of a median UIC of 100 µg/L as an indicator of iodine sufficiency
within a population (102). Furthermore, it was recommended that the prevalence of
median UIC <50 µg/L (based on a minimum daily iodine requirement of 50 µg (112,
137)) should not exceed 20% within a population (102).
Review of the Literature
~ 30 ~
One of the key studies which supported the new WHO cut-offs as being
appropriate was a multi-center study conducted in 5,709 schoolchildren (7-15
years) from The Netherlands, Belgium, Luxembourg, France, Germany, Austria,
Italy, Poland, the Czech and Slovak Republics (1997) (107). This study collected spot
urine samples and measured thyroid volume using thyroid ultrasound to determine
iodine status and assess the relationship between UIC and goiter rate. Iodine
deficiency was defined on the basis of the 1993 WHO recommendations as i)
prevalence of >5% of clinically detectable goiter or of thyroid volume determined
by ultrasonography above the 97th percentile for a population of children with
normal iodine intake and; ii) a median UIC below 100 µg/L. Median UIC ranged from
20µg/L in Poland to 160µg/L in the Netherlands, however goiter rate was above 5%
in all sites, including iodine sufficient areas (as determined using UIC). In addition,
goiter rate was systematically below 5% in areas where the median UIC was above
100 µg/L, indicating an association between UIC and thyroid size and supporting
the recommendations proposed by the WHO (107).
Whilst this study provided strong evidence in support of the WHO
recommendations and formed the basis of thyroid volume recommendations
published by the WHO in 1997 (138), subsequent reports suggested that the study
had overestimated the goiter rate (139-141). Studies in American (141), Swiss (140) and
Malaysian (139) school-aged children observed significantly lower goiter rates, less
than 1%, when compared to the European study where a goiter prevalence rate of
>5% was observed in all sites, even in areas with normal iodine intakes (107). It was
first suggested that this may have been a result of the long standing history of
iodine deficiency in Europe, resulting in a slower response by the thyroid gland to
iodine prophylaxis as a result of long-term exposure to iodine deficiency (141).
However in 2000 a WHO/ICCIDD workshop on thyroid ultrasound uncovered
several sources of inter-observer and inter-equipment error, even in experienced
examiners (108). It was suggested that this systematic error in the thyroid ultrasound
methodology used in the 1997 study was the reason for the observed discrepancies
in goiter prevalence estimates (108). Whilst this led to the re-development of
Review of the Literature
~ 31 ~
recommended reference values for thyroid volume by ultrasound (97), the UIC cut-
off of 100 µg/L remained unchanged (37, 38, 142).
Whilst the 1993 recommendations supported the use of median UIC from
spot urine samples, it was still recommended for use in combination with goiter
rate (102). As previously discussed, however, goiter can take months, if not years to
respond to iodine prophylaxis, and studies conducted in school-aged children in
the late 1990s observed that spot UIC responded to iodine supplementation much
faster than thyroid size (69, 143). One such study conducted in 671 6, 12, and 15 year
old children in South Africa 1 year after the introduction of USI, observed that
goiter rate ranged from 5%-29%, even though median UIC from spot urine samples
was >100 µg/L (143). Similarly, a 5 year prospective study in 5-14 year old children
from West Africa, measured median UIC in spot urine samples alongside goiter
prevalence determined using thyroid palpation 6 months before the introduction
of USI and annually for 4 years after (7). In this study it was observed that although
median UIC had increased to within normal levels, goiter rate remained elevated
four years after the introduction of USI. As such, it was recognised that the use of
goiter rate could result in the misclassification of iodine status, and population
monitoring surveys began to focus more on using median UIC, estimated from spot
urine samples in school-aged children, with a subsequent shift away from the use
of goiter rate (144). This led to the WHO endorsing the use of median UIC determined
from spot urine samples in school-aged children as the primary indicator for
assessing the iodine status of populations in 2001 (142). Since the publication of
these recommendations in 2001, they have remained largely unchanged (Table 2.3)
(38).
Review of the Literature
~ 32 ~
Whilst the use of UIC from spot urine samples has been valiadated for use
as a tool for identifying iodine deficiency, its use as a measure of intake is based on
a number of assumptions (15). Specifically, only in populations where daily urine
volume is equal to 1L can spot UIC be extrapolated to equal daily iodine intake (15).
For example, in a population of adolescents with a daily urine volume of 1L, a UIC
of 100 µg/L would be equivalent to a daily iodine intake of 100 µg/24-hours.
However in a population of children with a daily urine volume closer to 0.5L, the
same UIC would be indicative of a daily intake of approximately 50 µg/24-hours. As
such, this population would be classified as being iodine sufficient, based on a UIC
of <100 µg/L, when their daily intake may in fact be lower than the 100 µg/day
originally associated with reduced goiter prevalence (117). Such misclassification
might prevent the implementation of appropriate strategies to improve iodine
intakes in this population and result in the subsequent development of iodine
deficiency disorders.
The assumption of a daily urinary output of 1L in children was first identified
by a 1995 study in 206 children aged 7 to 15 years. In this study the median 24-
hour urine volume for aged 7 -15 years was estimated to be approximately 0.9
mL/hr/kg (145). However daily urinary excretion varied between 0.3-3.2 mL/kg/hour,
indicating a wide range. Based on the findings of this study, however, a number of
studies have assumed a daily urine output of 1L amongst children and have utilised
Table 2.3: World Health Organization epidemiological criteria for assessing iodine nutrition based on median urinary iodine concentrations from spot urines in different target groups (38) Median Urinary Iodine Concentration (µg/L)
Iodine intake Iodine status
School-age children (6 years or older) a
<20 Insufficient Severe iodine deficiency
20-49 Insufficient Moderate iodine deficiency
50-99 Insufficient Mild iodine deficiency
100-199 Adequate Adequate iodine nutrition
200-299 Above requirements May pose a slight risk of more than adequate iodine intake in these populations
≥300 Excessive b
Risk of adverse health consequences (Iodine induced hyperthyroidism, autoimmune thyroid disease)
a Applies to adults but not to pregnant and lactating women b The term “excessive” means in excess of the amount required to prevent and control iodine deficiency
Review of the Literature
~ 33 ~
UIC as a surrogate index of daily iodine intakes amongst populations of
schoolchildren (8, 144, 146-149) . To date, however, there has been no systematic
evaluation of the average 24-hour urine volumes of children and adolescents from
around the world. This information would assist in determining the
appropriateness of the assumption that UIC can be used as a surrogate marker of
daily iodine intake in children and adolescents, and whether such assumptions
might result in the misclassification of populations with inadequate iodine intakes
as iodine sufficient.
2.5 Iodine Nutrition in Australia
2.5.1 History of Iodine deficiency in Australia
Monitoring of iodine nutrition in Australia prior to the 21st century was
scarce, and was limited to very small sample sizes (13, 39, 40, 53, 130). Prior to the 1990s
Australia was believed to be iodine-sufficient, with the exception of the Australian
Capital Territory (ACT) and the island of Tasmania where endemic goiter was
prevalent (12, 13). In order to address this, public health experts in Australia
recommended the substitution of potassium bromate for potassium iodate as the
‘improver’ added to flour before bread was baked, following the successful
implementation of a similar program in the Netherlands (13). This fortification
program was subsequently introduced in the ACT in 1963 and Tasmania in 1966
and was estimated to result in an average intake of approximately 100 µg of iodine
per day in school-aged children. This, in conjunction with the serendipitous
contamination of milk by newly-introduced iodine containing sanitisers in the dairy
industry, saw a dramatic increase in iodine intakes (12, 13, 40, 53). The detection of mild
thyrotoxicosis in a sample of Tasmanian adults in the 1970s (40, 53) led to a reduction
in the use of these sanitisers by the dairy industry over the next two decades (13, 52,
150). This was believed to be the reason for the re-emergence of iodine deficiency
in the Australian population, first observed in a small sample of pregnant women
from Sydney in the late 1990s (33). Following this, a number of studies documented
iodine deficiency in Australian children (14, 34, 42, 43, 130) (Table 2.4) .
Tabl
e 2.
4: S
tud
ies
do
cum
enti
ng
iod
ine
defi
cien
cy in
th
e A
ust
ralia
n p
op
ulat
ion
pre
-fo
rtif
icat
ion
of
bre
ad w
ith
iod
ised
sal
t
Au
tho
r St
udy
Yea
r Lo
cati
on
Part
icip
ants
M
eth
ods
Res
ult
s
Gu
ttik
ond
a (1
4)
200
0
Tasm
ania
n
=2
25
4
-17
y/o
ld
99
gir
ls, 1
26
bo
ys
spo
t U
IC d
eter
min
ed
fro
m m
orn
ing
no
n-
fast
ing
spo
t sa
mp
les
med
ian
(IQ
R)
UIC
= 8
4 (
57
-11
0)
µg/
L
[gir
ls: 8
1 (
54
-11
1)
µg/
L;
bo
ys: 8
7 (
59
-11
1)
µg/
L (P
>0.0
5)]
Gu
ttik
ond
a (4
2)
200
0
Cen
tral
Co
ast,
N
ew S
ou
th W
ales
n=
30
1
5-1
3 y
/old
1
38
gir
ls, 1
60
bo
ys
spo
t U
IC d
eter
min
ed
fro
m m
orn
ing
no
n-
fast
ing
spo
t sa
mp
les
m
edia
n (
IQR
) U
IC =
82
(6
1-1
09
) µ
g/L
McD
onn
ell (4
3)
200
1
Mel
bo
urn
e, V
icto
ria
n=
57
7
11
-18
y/o
ld
41
0 g
irls
, 16
7 b
oys
spo
t U
IC d
eter
min
ed
fro
m m
orn
ing
no
n-
fast
ing
spo
t sa
mp
les
med
ian
UIC
= 7
0 µ
g/L
[g
irls
: 64
µg/
L; b
oys
: 82
µg/
L (P
<0.0
02
)]
Hyn
es (1
30)
bas
elin
e:
199
8/1
999
Ta
sman
ia
n=
24
1 4
-12
y/o
ld
13
3 g
irls
, 12
8 b
oys
sp
ot
UIC
det
erm
ined
fr
om
fas
tin
g, f
irst
vo
id
spo
t sa
mp
les
med
ian
(ra
nge
) U
IC =
75
(1
5-2
40
) µ
g/L
follo
w-u
p:
200
0-2
001
n
=17
0 5
-14
y/o
ld
75
gir
ls, 9
5 b
oys
m
edia
n (
ran
ge)
UIC
= 7
6 (
18
-48
0)
µg/
L
Li (3
4)
200
3-2
004
New
So
uth
Wal
es,
Vic
tori
a,
Sou
th A
ust
ralia
, Wes
tern
A
ust
ralia
an
d Q
uee
nsl
and
n=
17
09
8
-10
y/o
ld
82
8 g
irls
, 88
1 b
oys
spo
t U
IC d
eter
min
ed
fro
m n
on
-fas
tin
g ra
nd
om
sp
ot
uri
ne
sam
ple
s
ove
rall
med
ian
(IQ
R)
UIC
= 1
04
(7
1-1
47
) µ
g/L
NSW
: 89
(6
5-1
24
) µ
g/L
VIC
: 74
(5
3-1
04
) µ
g/L
SA: 1
01
(7
4-1
30
) µ
g/L
WA
: 14
3 (
10
4-2
14
) µ
g/L
QLD
: 13
7 (
10
4-1
84
) µ
g/L
UIC
–U
rin
ary
Iod
ine
Co
nce
ntr
atio
n
~ 34 ~
Review of the Literature
Review of the Literature
~ 35 ~
2.5.2 Mandatory fortification of bread with iodised salt
In response to the increased concern over the re-emergence of iodine
deficiency in Australia and New Zealand (33, 35, 41, 150, 151), Food Standards Australia
and New Zealand (FSANZ) introduced mandatory fortification of bread with iodised
salt in October 2009 (44). The primary strategy for preventing and controlling iodine
deficiency disorders promoted by the WHO since 1993 is the implementation of
USI (152). This involves the “fortification of all food-grade salt, used in household and
food processing” with iodine at a level of 15-40 ppm iodine (153). FSANZ chose not
to implement the USI policy recommended by the WHO (152) due to a concern over
the risks associated with a rapid increase in iodine consumption (154). Additionally,
FSANZ was concerned that the implementation of a USI policy may restrict the
ability of Australia to export and trade with countries where a USI policy had not
been established (154). As a result, FSANZ chose to limit salt iodisation to salt used
in bread manufacture, and since October 2009 all bread products, excluding
organic varieties and bread mixes for making bread at home (44), should have
iodised salt added where non-iodised salt would otherwise be used (155). It is also
recommended that iodised salt be added to other foods, however this is at the
manufacturers discretion (44). There is no recommended amount of salt which
should be added however salt the current level of iodine in salt added to bread in
Australia varies more than two fold: between 25-65 mg iodine per kilogram of salt
(56). Furthermore the sodium content of bread ranges between 200-800 mg/100g
(55), resulting in substantial variations in the iodine content of bread products both
within and between varieties (56). Bread was specifically chosen it was believed to
be a commonly consumed food product amongst children and pregnant women,
the two main target groups for iodine intervention (132). Studies conducted in
school-aged children since the introduction of mandatory fortification of bread in
2009 (44) have reported an improvement in iodine status, measured using spot
urine samples (29, 45-47).
Review of the Literature
~ 36 ~
2.5.3 Population Iodine nutrition in Australia post-fortification of
bread with iodised salt
The recent Australian Health Survey (AHS) reported that the Australian
population was iodine replete, based on a population median spot UIC of 124 µg/L
(45). Median UIC determined from ‘random’ spot samples in the AHS was found to
be significantly higher than UIC estimates from the 2003-2004 Australian National
Iodine Nutrition Study (NINS), conducted prior to the introduction of mandatory
fortification (34) and was found to vary by state (Table 2.5). Specifically, the median
population UIC of 2-18 year olds was 16% higher than the population median UIC
determined as part of the NINS in 2003/4 (124 µg/L vs. 104 µg/L) (34, 48). Median
UIC was highest in Western Australia and lowest in South Australia and Victoria (156),
indicating possible regional differences in iodine intakes (34). Of increasing concern
was the finding that the median spot UIC observed in Western Australia, was
nearing the WHO’s upper level recommendation of 300 µg/L. In another study in a
sample of Queensland preschoolers (n=51, 2-4 years old) (47), 18% of the population
had a spot UIC exceeding 300 µg/L, which puts children at risk of developing iodine-
induced hyperthyroidism and other autoimmune disorders(87).
The findings from the AHS are supported by a study in Tasmanian
schoolchildren 8-13 years of age (n=320) which observed that median spot UIC was
significantly higher in 2011 when compared to the period prior to fortification (129
µg/L vs. 108 µg/L, P<0.001)(29). Whilst this study compared data from different
cohorts, it does provide evidence that population iodine nutrition has improved
Table. 2.5: Comparison of median UIC from spot urine samples of schoolchildren in 2003-2004 and 2011-2013 (34)
State Median UIC (µg/L)
2003-2004 2011-2012
New South Wales 89 177
Victoria 74 163
Queensland 137 166
South Australia 101 150
Western Australia 143 261
UIC – urinary iodine concentration
Review of the Literature
~ 37 ~
following the introduction of mandatory fortification. It is important to note that
both the AHS and the studies in Tasmania and Queensland utilised spot urine
samples to assess iodine status as opposed to iodine intake. To date there have
been no studies examining the iodine intakes of Australian schoolchildren utilising
24-hour urine samples, post-fortification of bread with iodised salt.
2.5.4 Dietary assessment
Whilst dietary assessment methodologies may be more cost-effective than
24-hour urines, enabling their use in large population based studies, they are not
considered as accurate as urine samples for estimating iodine intakes (15). In
addition to the recall and subject biases associated with dietary assessment
methodologies (157) food composition databases often lack specificity regarding the
use of iodised salt during food production (49, 50). For example in Australia the
iodised salt added to bread during production contributes a significant proportion
of total iodine intake, as bread is one of the main sources of iodine (44, 54). The
concentration of iodine bound to the salt added to bread can vary more than two
fold, depending primarily on the amount of potassium iodate added during
production (56). Furthermore, the sodium content of bread can range between 200-
800 mg/100g (55), however most food databases used to estimate iodine intakes
from food recalls and food records utilise the mean sodium and iodine content of
each bread product and do not account for the variation in either sodium or iodine
contents of breads (158). Additional variations in the iodine content of other foods
such as milk, another major food source of iodine in the Australian population (45),
which can vary from 90-300 µg iodine /kg milk (11) are unlikely to be captured by
food composition databases.
This lack of specificity regarding the iodine content of foods can result in
inaccurate estimations of daily iodine intakes when dietary assessment
methodologies are used (15, 159). Therefore dietary assessment methodologies are
more commonly used for identifying the food sources of iodine in populations (46,
159-162). Whilst the recent AHS utilised 24-hour food recalls primarily to identify the
main food sources of iodine, these recalls were also used to estimate the daily
Review of the Literature
~ 38 ~
iodine intakes of the population. A recent analysis of the AHS dietary data
confirmed the improvement in population iodine intake with only a small
proportion of children (8%, n=144/1772) having inadequate iodine intakes,
assessed by dietary recall, below the age-specific EAR (46).
2.6 Food sources of iodine in Australia
2.6.1 Bread
Prior to the introduction of mandatory fortification in 2009, bread was not
considered a major food source of iodine. In the 2007 Australian Children’s
Nutrition and Physical Activity Survey (CNPAS), cereal products and dishes
contributed <10% of total iodine intake (51). Comparatively, the 2011-2013 AHS
found that cereals and cereal products contributed 33% and 30% of total dietary
iodine in 4-8 and 9-13 year olds, respectively (45). Furthermore, the AHS found that
regular bread and bread rolls specifically contributed 27% of 4-8 year olds and 23%
of 9-13 year olds’ total dietary iodine. Additional analyses of the AHS data indicated
that, amongst children and adolescents (2-18 year olds), consumption of 100g of
bread was associated with 12 times greater odds of achieving an adequate dietary
iodine dietary iodine intake (OR 12.34, 95% CI 1.71–89.26; P<0.001) compared to
children who consumed <100g bread per day, using 24-hour food recalls (46).
Similarly, a recent study in 147, 8-10 year old New Zealand schoolchildren,
post-fortification of bread with iodised salt, estimated total dietary iodine intake
and the food sources of iodine using an iodine-specific food frequency
questionnaire (FFQ) (133). In addition, this study collected random spot urine
samples, in order to determine the association between the food sources of iodine
and spot UIC. In this study bread was found to contribute 28% of total dietary iodine
intake (determined using the FFQ), compared to 1% in 2002. Furthermore, the
percentage contribution of iodine from bread was significantly associated with UIC
(P=0.017) (133). The results of this study are limited, however, as spot UIC does not
provide an accurate estimate of daily iodine intake. Studies assessing the
association between bread consumption and iodine intake assessed using an
objective measure of iodine intake, i.e. observed 24-hour UIE, are needed to
Review of the Literature
~ 39 ~
confirm these findings and further elucidate the relationship between bread
consumption and total daily iodine intake. Such a study will help to evaluate the
impact of the current fortification strategy and determined whether it has been
effective in improving the iodine intakes of Australian population. To date, no
studies have examined this association in a sample of Australian schoolchildren,
post-fortification of bread with iodised salt.
2.6.2 Milk as a dietary source of iodine
In Australia and New Zealand between 1975 and 2009 one of the most
abundant food sources of iodine was milk and dairy products (51, 52, 130, 163, 164), as
iodophores, used as sanitisers during dairy processing, leached into the milk
increasing its concentration (165). Whilst concerns have been raised that a change
in the use of sanitisers by the dairy industry may have led to the observed reduction
in iodine intakes of the Australian population (52), a recent study by Tinggi et. al.
(2012) found that the iodine content of Australian milk is comparable with that in
iodine sufficient countries such as Switzerland, where iodine containing sanitisers
are still used (11). Furthermore, the 2011-13 AHS observed that milk was the
greatest contributor to total daily iodine intake in children, as measured using 24-
hour food recalls, with 27% and 25% of dietary iodine coming from dairy milk
amongst 4-8 and 9-13 year olds, respectively (45). Similarly in adults, milk products
and dishes was the second highest food source of iodine, after bread, contributing
26% of total dietary iodine (45).
The iodine content of milk appears to be dependant mainly on
contamination from iodophores (165), although there is some naturally occurring
iodine which is present within milk (166). This naturally occurring iodine is, however,
highly variable and is largely dependent on the iodine intake of the cow itself (165-
167). Factors such as the supplementation of cow feed and salt licks, the cow species
and farm location can impact the level of naturally occurring iodine in milk (165, 166,
168). Currently within Australia iodophores are still permitted for use in the dairy
industry, however their use is not monitored, and the proportion of farmers
currently using them is not known, nor is the concentration at which they are used
Review of the Literature
~ 40 ~
(Kathryn Davis, Dairy Australia, Personal Communication, January 2017). As such,
it is difficult to determine the level of contamination in milk by iodophores, and this
in combination with the variation in the naturally occurring iodine content of milk,
means that the iodine content of Australian milk could vary considerably both
within and between producers.
A recent study in a sample of 168 children aged 8-10 years from three areas
of the United Kingdom (Omagh, Northern Ireland; Glasgow, Scotland, and
Guildford, South-East England) observed a significant positive association between
milk intake and spot UIC (P=0.006) (169). Furthermore, consumption of milk <140mL
per day was associated with a 20% lower median spot UIC compared to those
children who consumed 140-280 mL per day (P=0.03) (169). Similarly, a study in
German school-aged children (n=221, 3-6 y/old) observed that milk intake,
assessed from 3-day weighed food records, was a significant predictor of observed
24-hour UIE (160). In this study a 1g/day increase in milk intake was associated with
a 0.08 µg/24-hour increase in UIE (=0.08, P<0.001) (160). It is important to note,
however, that milk is the main food source of iodine in both the U.K. and Germany
, primarily due to contamination of milk with iodine containing sanitisers, as neither
country currently has a mandatory iodine fortification strategy in place (160, 170).
These two studies (160, 169) indicate that milk is a significant contributor to iodine
intakes among school-aged children in the Germany and U.K., however the
contribution of milk to iodine intake, measured using 24-hour urine samples, has
not been assessed in Australian school-aged children. Establishing the association
between milk consumption and observed 24-hour UIE would help to confirm the
AHS finding that milk remains a significant source of iodine in Australia.
2.6.3 The use of iodised salt
Iodine can be fortified into a variety of food products, including oil, milk,
sugar or animal feed (5). As salt remains one of the few foodstuffs consumed by
people worldwide it provides a unique medium through which to correct and/or
prevent iodine deficiency in multiple regions of the globe (50). Additionally salt
consumption remains fairly stable throughout the year, is not affected by
Review of the Literature
~ 41 ~
seasonality, and salt production/importation is limited to a few sources in most
countries (50). Finally, iodisation technology is relatively easy to implement and
monitor, with low costs and no impact on the overall flavour and colour of the salt
itself (50). Therefore salt provides a good medium for iodine supplementation.
Furthermore, a recent systematic review and meta-analysis of 89 studies found
that exposure to iodised salt was significantly associated with reduced risk or
prevalence of goiter, cretinism, low intelligence and low observed 24-hour UIE (171).
This analysis also did not find an association between exposure to iodised salt and
prevalence/risk of adverse effects, including increased hypothyroidism or
hyperthyroidism, indicating that iodised salt is both effective and safe for use as a
fortification strategy (171).
It has been estimated that approximately 70% of households worldwide
have access to iodised salt, with regions in the Western Pacific and Americas having
the greatest access, and parts of the Eastern Mediterranean having the least access
(148). In Australia specifically, monitoring of iodised salt consumption has been
limited to data from salt sales (172) or questions related to engagement in
discretionary salt use behaviours (including the AHS) (45). Iodised salt has been
available in supermarkets and grocery stores in Australia since the 1960s, however
consumption has remained relatively low, despite the prevalence of iodine
deficiency (172). Previous research has found that the main reason for low iodised
salt sales is that consumers are generally uneducated regarding the benefits of
iodised salt (172). A 2008 study conducted by Li et. al. examined national data on
iodised salt sales, obtained from national point-of-purchase bar code scanning for
all brands of iodised salt from major supermarket stores and independent stores
throughout Australia from January 1, 1997 – April 30, 2006 (172). There was an
overall increase in iodised salt sales between 1997 and 2006, with the most
noticeable increase occurring in the three years following the NINS in 2003-2004.
It was estimated that during this three year period, iodised salt sales increased
approximately 29%, with a 5% increase in sales in the month immediately following
the broadcast of a science program on iodine deficiency disorders in November
2005.
Review of the Literature
~ 42 ~
It has been estimated that discretionary salt use contributes 10-15% of total
dietary salt (173) and it has been found that adults who report adding salt at the
table and in cooking have higher total salt intakes compared to those not using
discretionary salt (174). The 2011-13 AHS reported that 50% of 4-8 year olds and 57%
of 9-13 year olds reported using salt in cooking “rarely/occasionally/very often”
with 17% of 4-8 year olds and 36% of 9-13 year olds adding salt at the table(45). Of
those who reported adding salt during cooking, 24% of 4-8 year olds (parental
report) and 25% of 9-13 year olds (self-report) reported that the salt used was
iodised. In addition, 8% of 4-8 year olds and 13% of 9-13 year olds who reported
adding salt at the table indicated iodised salt was used (45). However, the AHS did
not include a direct estimate of daily salt intake, with data pertaining to
engagement in salt use behaviours collected via self-report by the participant or a
proxy (in the case of young children). As such there may have been some
underreporting or overreporting of engagement in these behaviours (175, 176). This
makes it difficult to ascertain the contribution of discretionary salt to total dietary
iodine intakes among Australian school-aged children.
Some studies have utilised 24-hour urinary sodium excretion as an indicator
of total sodium, and thus salt, intake as a means of assessing the relationship
between total salt intake and iodine intake (160, 177-179). Whilst the results of these
studies are varied, with studies in adults failing to determine an association
between 24-hour excretion of urinary sodium and iodine (178, 179), one study in a
sample of mildly iodine deficient German children (n=378, 3-6 year olds) estimated
that total salt intake, measured using 24-hour urinary sodium excretion,
contributed 42% of total dietary iodine, measured using observed 24-hour UIE (160).
In addition, the study observed a moderate positive correlation between observed
24-hour UIE and 24-hour excretion of sodium (r=0.43, P<0.05) (160). To date no
studies have examined the association between daily intakes of sodium (as a
marker of total salt intake) and iodine measured using 24-hour urinary excretion in
a sample of Australian school-aged children. Such a study could help to establish
the relationship between iodine intake and salt intake, in order to further
understand the role which iodised salt, added either during processing or as
Review of the Literature
~ 43 ~
discretionary salt (i.e. during cooking and at the table), plays in the iodine intakes
of Australian school-aged children.
2.7 Sodium reduction targets and iodine
2.7.1 Sodium intakes and health of children and adolescents
The relationship between sodium intake and blood pressure is well
established in adults (57, 180-182). Similar associations have also been reported in
children, with a 2006 meta-analysis of controlled trials, encompassing 10 trials and
966 children and adolescents aged 8-16 years observed a significant reduction in
both systolic, -1.17 mm Hg (95% CI: -1.78 to -0.56 mm Hg; P<0.001), and diastolic,
-1.29 mm Hg (95% CI: -1.94 to -0.65 mm Hg; P<0.0001), blood pressure (BP) with a
reduction in salt intake (median (IQR) salt reduction 42% (7%-58%) (181). Similarly,
a review of 25 observational and 12 intervention studies conducted by Simons-
Morton & Obarzanek (1997) concluded that a greater sodium intake was
associated with higher BP in children and adolescents (183). More recently, a
possible link between high sodium intakes and sugar sweetened beverage
consumption has been observed in studies in Britain (184), the United States (185) and
Australia (186). The mechanism behind this relationship lies in the homeostatic
trigger of thirst in response to the ingestion of dietary salt (187). It is suggested that
in an environment where soft drinks are readily available, a high salt diet may
encourage greater consumption of sugar sweetened beverages in children (187).
Increased consumption of sugar sweetened beverages has been linked to an
increased risk of obesity amongst Australian children and adolescents (186).
Furthermore, recent cross-sectional studies in Australia have also observed an
association between salt intake and obesity (188). Together these studies highlight
the adverse effects which excessive salt intakes may have on the health of children
and adolescents.
2.7.2 Global action to reduce sodium intake
Due to the adverse health effects known to be associated with high salt
intakes (57, 180, 181, 189) the WHO recommends a reduction in salt intake to <5g/day
Review of the Literature
~ 44 ~
among adults by 2025 worldwide (58) with a further reduction to <2g/day
recommended for children based on the energy requirements of children relative
to those of adults (190). A recent systematic review of 55 peer-reviewed articles and
170 grey literature documents and websites conducted in 2014 found that 75
countries had implemented national salt reduction strategies with a further 9
studies in the planning stages (191). The most prominent strategy implemented to
reduce sodium reductions was food reformulation, with 81% of national salt
reduction strategies focusing on engaging food industry to reduce the sodium
content of processed foods (191).
The most successful example of a population based sodium reduction
strategy comes from the United Kingdom (192). Initially, the strategy aimed to
reduce average population salt intakes to <6 g per day by 2015, through a
combination of engagement with the food industry to reduce the amount of salt
added to processed, restaurant and fast food, as well as a public health campaign
to increase awareness around the harmful effects of high salt intakes (192). Since the
introduction of the strategy in 2003, the U.K. has observed a 15% reduction in the
average salt consumption, with an estimated 9000 fewer cardiovascular deaths per
year (192). The success of the strategy has led to the subsequent revision of the
original target, with the program now aiming to reduce population salt intake to 3g
per day by 2025 (193).
2.7.3 Australian sodium reduction strategies
Currently within Australia, a number of sodium reduction initiatives are
being implemented by different organizations, however there is no national
governmental policy related to reducing sodium intake at the population level (194).
A key stakeholder in the development of sodium reduction strategies in Australia
is the Australian Division of World Action on Salt and Health (AWASH). AWASH was
originally modelled on the United Kingdom’s Consensus Action on Salt and Health
(CASH), and was first established in 2005 (195). AWASH comprises of a growing body
of experts in public health, marketing and communications, and project
management, with wider stakeholder input from research organisations, the food
Review of the Literature
~ 45 ~
industry, health and consumer entities, government bodies and food and health
consultants (195). In 2007 AWASH launched its ‘Drop the Salt!’ campaign, a multi-
pronged initiative modelled on the strategy implemented in the U.K. (194). The
primary aim of this campaign was a reduction in the average salt consumption of
the Australian population to 6 grams per day over 5 years through the
reformulation of processed and catered foods, and advocacy to improve
population knowledge regarding the health benefits of limiting salt intakes.
Furthermore, the campaign aimed to raise the profile of salt reduction on the
agenda of both State and Federal governments across Australia (194).
This was followed in 2009 by the establishment of the Federal
Government’s Food and Health Dialogue (FHD) between government, food
industry, the Heart Foundation and Public Health Association which saw the
establishment of salt reduction targets for nine food categories, including bread
(Appendix A) (194). Since the establishment of the FHD in 2009, Australia has
observed a 10% reduction in the sodium content of commercially available breads
(59). In addition the number of bread products with a sodium content below the
maximum recommended level of 400 mg sodium/100 g tripled from 28% in 2009
to 86% in 2015(59). However, during this same period (2010-2013) FSANZ also
reported a reduction in the iodine contents of white and wholemeal bread
products by 11% and 25%, respectively (196). This reduction in the iodine content of
bread products is most likely a result of the successful implementation of sodium
reduction targets, and raises the concern that a further reduction in the sodium
content of bread products could result in a subsequent reduction in the iodine
content of bread. As bread was found to be a significant contributor to total dietary
iodine intake in the 2011-13 AHS, due to the addition of iodised salt to bread during
processing, there are concerns that further reductions in the salt content of bread
could have a negative impact on the iodine intakes of Australians (197).
It is, however, important that sodium reduction strategies remain a public
health priority in Australia due to the negative health outcomes associated with
high salt intakes intakes (57, 180, 181, 189). Whilst there is currently no co-ordinated
national strategy for sodium reduction in Australia, the ‘Healthy Food Partnership’
Review of the Literature
~ 46 ~
established in November 2015 (198) aims to build on the FHD’s reformulation
targets, with the overarching aim of reducing average population salt intakes by
30% by 2025 as part of a broader international commitment to reducing the
prevalence of non-communicable diseases (199). It is therefore important to
continually monitor the iodine intakes of Australian schoolchildren, to ensure they
are not being placed at risk of iodine deficiency as a result of a reduction in the
amount of iodised salt added to bread during processing. Furthermore, establishing
the relationship between iodine intakes determined using an objective measure of
intake (i.e. 24-hour UIE), food sources of iodine, including iodised salt, and
discretionary salt use will help to determine the role which iodised salt plays in the
iodine intakes of Australian school-aged children. This information is important
when evaluating the potential impact which sodium reduction targets might have
on the iodine intakes of Australian school-aged children. Furthermore, the
identification of alternative food sources of iodine which are not dependent on
iodised salt could help in the development of strategies to ameliorate the potential
impact of sodium reduction strategies on iodine intakes.
2.8 Summary
Iodine is an essential nutrient in the synthesis of thyroid hormones which
are important for normal growth and development (62). These hormones are
particularly important in periods of rapid growth and development, such as
childhood, with studies in children observing a significant association between
iodine intakes and cognition (6, 7). Current recommendations by the WHO endorse
the use of spot urine samples to determine median UIC as the most appropriate
method for determining the iodine status of a population (142). These
recommendations are based on the assumption that spot UIC can be used as a
surrogate measure of the iodine intakes of individuals within the population.
However, only in populations where daily urine volume is equal to 1L would spot
UIC be equivalent to daily iodine intake (15). Whilst the use of UIC has been validated
for identifying populations at risk of deficiency, its use as an indicator of daily intake
is less reliable as it is based on the assumption of a daily urine excretion of 1L.
Review of the Literature
~ 47 ~
However, in populations where daily urine volume is less than 1L, such as children,
the overestimation of daily iodine intake may occur which could result in the
misclassification of children with inadequate iodine intakes as iodine sufficient. To
date, however, there has been no systematic evaluation of the 24-hour urine
volume of school-aged children to determine the appropriateness of current
recommendations for assessing the iodine nutrition of schoolchildren.
Following the detection of iodine deficiency in a proportion of the
Australian population in the late 1990s (33), mandatory fortification of all
commercially produced bread, excluding organic and homemade varieties, with
iodised salt was introduced in 2009 (44). Whilst studies utilising spot urine samples
have observed an improvement in the iodine status of the Australian school-aged
children since the implementation of fortification in 2009 (14, 34, 42, 43, 130), no studies
have examined the iodine intakes of a sample of Australian school-aged children
determined using 24-hour urine samples. Although the 2011-13 AHS utilised 24-
hour food recalls to identify the food sources of iodine and estimate daily dietary
iodine intake, variations in the iodine content of foods not captured by food
databases may have resulted in an inaccurate estimate of daily iodine intake.
Furthermore dietary assessment does not account for discretionary use of iodised
salt, which might lead to the underestimation of total iodine intake. Understanding
the food sources of iodine can assist in determining the success of fortification
strategies as well as help in identifying alternative food sources of iodine which are
less reliant on iodised salt for their iodine content.
Due to the adverse health effects known to be associated with high salt
intakes (57, 180, 181, 189) the WHO recommends a reduction in salt intake to <5g/day
among adults by 2025 worldwide (58) with further reduction to <2g/day
recommended for children based on the energy requirements of children relative
to those of adults (190). The most prominent strategy implemented to reduce
sodium reductions is food reformulation, with the implementation of sodium
reduction targets for nine food categories, including bread, in 2009 resulting in a
10% reduction in the sodium content of commercially available breads in Australia
(59). As bread was found to be a significant contributor to total dietary iodine intake
Review of the Literature
~ 48 ~
in the 2011-13 AHS, due to the addition of iodised salt to bread during processing,
there are concerns that further reductions in iodised salt use during bread
processing as a result of sodium reduction strategies could have a negative impact
on the iodine intakes of Australians (197). Establishing the relationship between
iodine and sodium intakes determined using an objective measure of intake (i.e.
observed 24-hour UIE) will help to determine the role which iodised salt, added
either during processing or as discretionary salt (i.e added at the table or during
cooking) plays in the iodine intakes of Australian schoolchildren. This information
is important when evaluating the potential impact which sodium reduction
strategies, including product reformulation, might have on the iodine intakes of
Australian school-aged children. The lack of data pertaining to daily iodine intakes
of Australian school-aged children measured using 24-hour urine samples, an
objective measure of intake, along with limited data exploring the relationship
between food sources of iodine and iodine intakes formed the rationale for the
work in this thesis.
~ 49 ~
Chapter Three:
Study 1: Meta-analysis of average 24-hour
urinary volume of children and adolescents
3.1 Introduction
Monitoring the iodine nutrition of populations and individuals is important
in order to identify those at risk of deficiency, as deficiencies during childhood have
been linked with impaired cognitive and motor functions in schoolchildren (6, 7).
Current recommendations for assessing the iodine nutrition of populations using
spot urine samples from school-aged children were developed by the World Health
Organization over a number of years (1986-2007) (37, 38, 102, 112, 142, 152). Whilst the
original version of these recommendations were based on the association between
a daily estimated iodine intake, extrapolated from creatinine excretion, equivalent
to 100 µg and reduced goiter prevalence among children and adults (117), later
iterations extrapolated this value to represent a concentration, urinary iodine
concentration (UIC) expressed as µg/L(37). In some instances where UIC is used as a
marker of iodine intake, issues may arise as UIC would only be reflective of daily
intake if urine volume was equivalent to 1L. For example, in a population with a
daily urinary volume of 1L, a UIC of 100 µg/L could be extrapolated to be indicative
of a daily iodine intake of 100 µg/24-hours. As this value is equal to the daily intake
originally associated with reduced goiter prevalence (117), this population can be
classified as having sufficient iodine intakes. However, in a population of children
with a daily urine volume closer to 0.5L a UIC of 100 µg/L would be indicative of a
daily iodine intake closer to 50 µg/24-hours. This could result in the
misclassification of a population as iodine sufficient when their daily iodine intakes
may, in fact, be placing them at risk of developing iodine deficiency disorders.
Therefore, iodine monitoring programs which have extrapolated daily
iodine intake from UIC determined from spot urine samples in populations of
children and adolescents (8, 144, 146-149) and have not taken the lower daily urinary
output into account, may be inaccurately estimating and reporting iodine intakes.
As such, this may have resulted in the misclassification of populations as having
Study 1: Meta-analysis of average 24-hour urinary volume of children and adolescents
~ 50 ~
sufficient iodine intakes based on a UIC > 100 µg/L, when their true intakes may be
lower than the 100µg/day originally associated with reduced goiter prevalence.
Such misclassifications may have prevented the implementation of necessary
iodine fortification programs which may have led to the subsequent development
of iodine deficiency disorders in these populations. To date, there has been no
systematic evaluation of the average 24-hour urine volume of children and
adolescents from around the world. This information would be useful to help
researchers interpret the interplay between UIC determined from spot urine
samples and iodine intakes, in order to understand the appropriateness of the
assumption that UIC can be used as a marker of the iodine intakes of children and
adolescents.
3.2 Aim
Using a systematic review, to produce an estimate of the average 24-hour urine
volume of healthy children and adolescents across the world
3.3 Methods
This protocol adheres to the Preferred Reporting Items for Systematic
Review and Meta-Analysis Protocols (PRISMA-P) 2015 statement (200) and was
registered with the International Prospective Register of Systematic Reviews
(PROSPERO) (registration number CRD42016033682).
3.3.1 Information Sources and Search
A search strategy was developed to identify papers which have reported
the 24-hour urine volume of children and adolescents (>1y and 19y). An electronic
literature search of EBSCOHOST (MEDLINE complete, CINAHL, Academic Search
Complete and Global Health) and EMBASE databases was conducted. The search
strategy was developed in consultation with a research librarian. Free text
keywords were used to conduct the search. Search criteria specific to each
database are outlined in Table 3.1. The search strategy was piloted across each
database to improve the effectiveness of the final search. Only peer-reviewed
Study 1: Meta-analysis of average 24-hour urinary volume of children and adolescents
~ 51 ~
original research articles published in English and conducted in humans were
included. It is beyond the scope of this review to include and examine sources from
‘grey’ literature. The reference lists of included studies identified through the
search were also reviewed. The search was then re-run in October 2017, to identify
any new studies published since the initial search in June 2016.
Table 3.1: Search criteria specifications for each database
Database Search options Search terms
EBSCOHOST
Academic Search Complete
Limiters - Full Text; Scholarly (Peer Reviewed) Journals; Language: English Search modes - Boolean/Phrase
(“24 hour urin*” OR “twenty four hour urin*” OR "24 h urin*") AND (sampl* OR collection* OR volume* OR excretion* OR output*) AND (schoolchild* OR child* OR adolescen* OR teen*)
CINAHL Complete
Limiters - English Language; Peer Reviewed Search modes - Boolean/Phrase
Global Health
Limiters - Language: English Search modes - Boolean/Phrase
MEDLINE Complete
Limiters - English Language; Human Search modes - Boolean/Phrase
EMBASE
Advanced search No mapping options used No date limits specified Sources: Embase only (Medline not selected as separate search) Field labels: abstract, article title, index term and subheading Quick limits: human, only in English Publication types: article, article in press EBM, gender, age and animal advanced options left blank
#1: '24 hour urin*' OR 'twenty four hour urin*' OR '24 h urin*' OR 'twenty four h urin*' #2: sampl* OR collection* OR volume* OR excretion*or AND output* #3: child* OR adolescen* OR teen* #4: #1 AND #2 AND #3
Study 1: Meta-analysis of average 24-hour urinary volume of children and adolescents
~ 52 ~
3.3.2 Inclusion/Exclusion criteria
Only peer-reviewed original research studies were included and any
reviews, meta-analyses, editorials, case reports, conference proceedings or other
grey literature identified through the search were excluded at the screening stage.
As the primary focus of this review was to determine the average urinary output of
children and adolescents, only studies which reported the 24-hour urinary output
of children and adolescents >1 and 19 years of age were included and studies
outside of this age range or studies where spot urine samples were used were
excluded. Finally, only studies in healthy participants were included, and any study
in a sample where an illness or diseased state (including diabetes, malnourishment,
kidney disease, liver failure, cancer, chronic asthma) existed was excluded. If
multiple published reports were available from the same study, the most recently
published and/or the study with the largest sample size was included.
All papers identified from the initial electronic search process were
imported into an Endnote library, and duplicates removed. Titles and abstracts
were screened and studies included based on the eligibility criteria as outlined
above. Following this screening process, the full text of eligible studies was
retrieved and studies which collected 24-hour urine samples but did not report the
final 24-hour urine volume were excluded. At this stage, the reference lists of
included studies were scanned, and the full text of any relevant studies retrieved
and reviewed for inclusion. The PRISMA flow chart (201) was used to document the
number of studies identified during the search process and those excluded and
included according to the outlined eligibility criteria (Figure 3.1).
Study 1: Meta-analysis of average 24-hour urinary volume of children and adolescents
~ 53 ~
As multiple studies had utilised data from the Dortmund Nutritional and
Anthropometric Longitudinally Designed (DONALD) Study (202), cross-checking of
study dates and participant characteristics was carried out to minimise participant
overlap between the studies. Some studies (n=7) (203-209) were excluded from the
final analysis as they did not report which years of data collection had been
analysed, therefore possible participant overlap with other studies could not be
determined. Authors were contacted for information where possible, however no
additional information was collected. Where participant overlap was possible, the
study with the larger participant number was included in the final analysis. Of the
Figure 3.1: PRISMA flow chart of study selection
Study 1: Meta-analysis of average 24-hour urinary volume of children and adolescents
~ 54 ~
27 DONALD studies initially identified, 6 studies (115, 176, 210-213) were included in the
final analyses as they captured the full range of data collection years and included
the largest number of participants whilst minimising possible participant overlap
(Appendix. B).
3.3.3 Data extraction and synthesis
Data extraction was completed using a data extraction template (Table 3.2).
The template was initially piloted on 5 eligible studies and modifications made
where necessary. As 24-hour urinary creatinine excretion either alone, in relation
to expected creatinine based on sex and/or weight, is often used as a marker for
complete urine collection under the assumption that urinary creatinine excretion,
as an indicator of body mass is stable within individuals from day to day (121, 214, 215),
data pertaining to 24-hour excretion of creatinine was also extracted where
reported.
Table 3.2: Data extracted from included studies
Study overview
Aim(s) Study design Study year(s) Description of country where the study was conducted Season of the year Setting (i.e. home/school)
Methods
Recruitment method Inclusion criteria (main study - not urine specific) Specific exclusion criteria (main study - not urine specific) Data collection overview
24-hour urine collection protocol
24-hr urine protocol description Criteria for completeness of urine samples
- time of collection (hours) - volume of collection - creatinine cut-off - number of missed collections reported by child/parent
Specific exclusion criteria for urine samples Adjustment for collection time/normalised? Other nutrients analysed
Study 1: Meta-analysis of average 24-hour urinary volume of children and adolescents
~ 55 ~
Participant characteristics
Total no. participating No. exclusions No. withdrawals Final n included in analyses % male participants Total no. urine samples Age, mean and range Weight category/BMI Race/Ethnicity SES (include description of SES definition)
Results
Urine volume (L/24h) - Mean, SD/SEM, Median, Range Creatinine - Mean, SD/SEM, Median, Range
3.3.4 Quality Assessment
The quality of the studies included in this review was assessed using a
modified version of the Newcastle-Ottawa scale (NOS) for cohort studies (216), as all
studies included in the final synthesis were of a cross-sectional study design
(Appendix C). The NOS was modified to suit the context of the studies included in
the review and particular consideration was made towards the 24-hour urine
collection methods used in each study. This scale assigns stars to indicate higher
quality based on three broad criteria specific to the design of the study: i) Selection
(representativeness of the study sample); ii) Comparability of the findings
(normalisation of the results to a 24-hour period); and iii) Assessment of outcome
(quality of the reported 24-hour urine collection methodology). Studies were
categorised as ‘high’ ‘medium’ or ‘low’ quality according to the number of stars
which they received (out of a maximum of 10 stars: low: 0-3; medium: 4-7 ; high 8-
10). As only 2 studies provided sufficient detail on their urine collection protocol to
be classified as “high” quality (188, 217), we included a second category of quality
assessment, based on studies which had reported at least one criteria for the
assessment of urine collection completeness.
Study 1: Meta-analysis of average 24-hour urinary volume of children and adolescents
~ 56 ~
3.3.5 Statistical Analysis
Following data extraction, data was collated and imported into STATA/SE
15.0 (StataCorp LP, College Station, TX, USA) for analysis. The main outcome
variable was 24-hour urine volume, presented in mL/24-hours. Of the 53 studies
originally included, five did not include a measure of spread/dispersion (218-222) and
were subsequently excluded (Figure 3.2). Most studies (n=36) reported urine
volume as mean (SD) or mean (SEM) (188, 217, 223-256) (Table 3.3). Thirteen studies
reported urine volume as either median (min, max)(20, 257-259), median (IQR)(115, 176,
210, 212, 213, 260, 261), median (P3, P97)(262) or median (no range) (218). In seven studies,
the 24-hour urine volume was reported as median (IQR) (n=7) (115, 176, 210, 212, 213, 260,
261) (Table 3.4) . The mean (SD) was extrapolated from the median (IQR) by using
the median as a proxy for the mean and the IQR as a proxy for the SD (i.e. P75-
P25=SD)(263). The calculated mean (SD) for these studies was then pooled with the
results of those studies which reported urine volume as mean (SD). As such, a total
of 43 studies were considered for the primary analysis.
Due to the wide age range of participants of the included studies, studies
were grouped into three groups according to the age of the participants; 2-6 (n=19)
(176, 212, 217, 223-225, 230, 231, 234-237, 240, 242, 248, 252, 254, 255, 262), 7-11 (n=19) (188, 210, 213, 217, 225-
228, 232, 234, 238, 239, 243-246, 251, 256, 260) and 12-19 years (n=12) (115, 176, 210, 217, 229, 233, 234,
243, 245, 247, 249, 260). These cut-points were chosen based on the age range of the
individual studies, with the cut-point of 12 years for the older age group as children
typically begin secondary education at 12 years of age. As some studies presented
results broken down by age group, a single study may have been assigned to
multiple age groups. Studies which crossed the age group cut-offs were assigned
to the age group in which the majority of the participants would fall (e.g. a study
with participants 9-13 years (239) would fall into the 7-11 year age group. Three
studies (250, 253, 261) which encompassed very large age ranges (i.e. >8 years) were
excluded from the sub group analyses using age cut offs.
Study 1: Meta-analysis of average 24-hour urinary volume of children and adolescents
~ 57 ~
Initial analysis
The overall mean (95% confidence interval (CI)) estimate of urine volume
for all 43 studies was determined using a random effects model and presented for
the group as a whole (i.e 2-19 year olds), as well as broken down by age group.
Primary analysis – studies with ≥1 criteria for assessing the completeness
of urine samples
As the inclusion of criteria for assessing the completeness of urine
collections can result in the exclusion of over/under collectors, the primary analysis
was limited to only those studies which reported at least one criteria for assessing
the completeness of the included urine samples (n=26, “Primary Analysis, Figure
3.2). The overall mean (95%CI) estimate of urine volume was determined using a
random effects model and displayed in forest plots, broken down by age group.
A one-way ANOVA was used to assess the differences in urine volume
across the three age groups. In addition, a one-way ANOVA was used to assess
differences in the urine volume between those studies which did not report any
criteria for assessing the completeness of included urine samples and those which
reported >1 and >2 criteria. A two-sample t-test used to assess the difference in
volumes determined for the initial analysis compared to the primary analysis (i.e.
limited to studies with >1 criteria for assessing the completeness of the urine
samples) across the 3 age groups. As seven studies had presented the results
broken down by gender (115, 176, 212, 213, 246, 250, 260), a two-sample t-test was used to
evaluate the difference in 24-hour urine volume between genders.
Study 1: Meta-analysis of average 24-hour urinary volume of children and adolescents
~ 58 ~
*Some studies reported results for more than one age group
Figure 3.2: Flow chart of studies included in analyses
Tab
le 3
.3: C
hara
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isti
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f st
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fo
r pr
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as p
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(SD
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), n
=36
stu
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Stu
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Stu
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Year
(s)
n
Mal
e,
n(%
)
Val
id
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ne
sam
ple
s
Age
ra
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(y
ears
)
Age
, m
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(SD
) ye
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Co
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Excl
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crit
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(m
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Ab
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n
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216
1
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Gaz
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(2
24)
n
ot
des
crib
ed
32
n
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32
3
-5
4.1
(0
.8)
Car
acas
, V
enez
uel
a n
ot
des
crib
ed
2
31
3
1
3-5
4
.3 (
1.3
) Sa
n J
uan
de
los
Mo
rro
s,
Ven
ezu
ela
Alle
vard
-
Bu
rgu
buru
(198
1) (2
25)
no
t d
escr
ibed
7
no
t d
escr
ibed
7 2
-2.9
no
t d
escr
ibed
n
ot
des
crib
ed
no
t d
escr
ibed
0
13
1
3
3-4
.9
16
1
6
5-6
.9
16
1
6
7-8
.9
10
1
0
9-1
1
Ap
aric
io
(201
5)
(22
6)
201
4
205
1
09 (
53%
) 2
05
7
-11
8
.8 (
1.2
) Sp
ain
cr
eati
nin
e ex
cret
ion
<0
.1m
mo
l/kg
/day
0
Study 1: Meta-analysis of average 24-hour urinary volume of children and adolescents
~ 59 ~
Stu
dy
Stu
dy
Year
(s)
n
Mal
e,
n(%
)
Val
id
uri
ne
sam
ple
s
Age
ra
nge
(y
ears
)
Age
, m
ean
(SD
) ye
ars
Co
unt
ry
Excl
usi
on
crit
eria
fo
r u
rine
sa
mp
les
NO
S sc
ore
(m
ax 1
0 p
oin
ts)
Bal
lau
ff
(198
8) (2
27)
n
ot
des
crib
ed
21
1
0 (
48%
) 2
1
6-1
1
8.8
(1
.4)
no
t d
escr
ibed
n
ot
des
crib
ed
4
Cla
rk
(199
6) (2
28)
no
t d
escr
ibed
2
04
89
(47
%)
19
0
9-1
0
9.6
(0
.2)
Salis
bu
ry, U
nit
ed
Kin
gdo
m
"Fo
urt
een
uri
ne
sam
ple
s w
ere
excl
ud
ed b
eca
use
of
an
in
corr
ect
colle
ctio
n p
erio
d
(n=4
), a
uri
ne
volu
me
alm
ost
4
sta
nd
ard
dev
iati
on
s b
elo
w t
he
geo
met
ric
mea
n (
n=1
), o
r b
act
eria
l or
oth
er
con
tam
ina
tio
n (
n=9
)"
4
Fujis
him
a (1
983)
(22
9)
198
0
84
8
4 (
100
%)
76
1
5-1
8
no
t d
escr
ibed
Ka
nag
awa,
Jap
an
no
t d
escr
ibed
2
Gri
mes
(2
016)
(18
8)
201
0 -
201
3
168
9
6 (
57%
) 1
68
4
- 7
.9
6.9
(0
.7)
Mel
bo
urn
e,
Au
stra
lia
On
e o
r m
ore
of
the
follo
win
g cr
iter
ia:
i) c
olle
ctio
n t
ime
<20
or
>28
h
ii) t
ota
l vo
lum
e <
30
0m
l iii
) p
arti
cip
ant
rep
ort
ed
mis
sin
g >1
co
llect
ion
, or
iv
) u
rin
ary
crea
tin
ine
excr
etio
n
<0.1
mm
ol/
kg/d
ay
10
498
2
69 (
54%
) 4
98
8
- 1
2
10
.1 (
1.2
)
~ 60 ~
Study 1: Meta-analysis of average 24-hour urinary volume of children and adolescents
Stu
dy
Stu
dy
Year
(s)
n
Mal
e,
n(%
)
Val
id
uri
ne
sam
ple
s
Age
ra
nge
(y
ears
)
Age
, m
ean
(SD
) ye
ars
Co
unt
ry
Excl
usi
on
crit
eria
fo
r u
rine
sa
mp
les
NO
S sc
ore
(m
ax 1
0 p
oin
ts)
Haf
tenb
erge
r (2
001)
(23
0)
199
8
11
6
(5
5%)
11
3
-6
4.2
(1
.3)
Dre
sden
, G
erm
any
no
t d
escr
ibed
0
Hag
a (2
010)
(23
1)
200
5
29
1
3 (
45%
) 2
9
3 -
4
no
t d
escr
ibed
M
iyag
i, Ja
pan
n
ot
des
crib
ed
2 3
3
18
(55
%)
33
4
.1 -
5
17
8
(4
7%)
17
5
.1 -
6
He
(201
5) (2
32)
2
013
138
6
7 (
49%
) 1
38
9
-11
1
0.2
(0
.5)
Ch
angz
hi,
Ch
ina
i) u
rin
e vo
lum
e <3
00
ml/
24
-h
ou
r o
r
ii) c
reat
inin
e <
5th
cen
tile
(<2
.5
mm
ol/
24
-ho
ur
for
girl
s an
d
<2.9
mm
ol/
24
-ho
ur
for
bo
ys)
7
141
6
7 (
48%
) 1
41
9
-12
1
0.0
(0
.5)
Hes
se
(198
6) (2
33)
n
ot
des
crib
ed
25
2
5 (
100
%)
25
1
5-1
9
no
t d
escr
ibed
n
ot
des
crib
ed
no
t d
escr
ibed
0
25
0
(0
%)
25
1
5-1
9
Hö
llrie
gl
(201
1) (2
34)
200
8
9
no
t d
escr
ibed
8 3
-5
no
t d
escr
ibed
A
kure
, Nig
eria
uri
nar
y cr
eati
nin
e va
lues
o
uts
ide
of
the
ran
ge o
f 0
.2-
3.0
g/L
3 2
8
24
6
-10
12
5
11
-15
~ 61 ~
Study 1: Meta-analysis of average 24-hour urinary volume of children and adolescents
Stu
dy
Stu
dy
Year
(s)
n
Mal
e,
n(%
)
Val
id
uri
ne
sam
ple
s
Age
ra
nge
(y
ears
)
Age
, m
ean
(SD
) ye
ars
Co
unt
ry
Excl
usi
on
crit
eria
fo
r u
rine
sa
mp
les
NO
S sc
ore
(m
ax 1
0 p
oin
ts)
Juar
ez-L
ope
z (2
016)
(23
5)
no
t d
escr
ibed
2
0
30
(54
%)
20
3
-5
3.8
(0
.9)
Stat
e o
f M
exic
o
excr
etio
n r
ate
bel
ow
9 μ
g F/
hr
3
Ketl
ey
(200
1) (2
37)
n
ot
des
crib
ed
13
n
ot
des
crib
ed
65
5
-6
5.8
(0
.5)
Mer
seys
ide,
En
glan
d
uri
nar
y fl
ow
rat
e <9
mL/
h
3
Ketl
ey
(200
4) (2
36)
199
4-1
996
19
no
t d
escr
ibed
19
1
.5-3
.5
3.4
(0
.2)
Co
rk, I
rela
nd
uri
nar
y fl
ow
rat
e o
f <
9 m
l/h
or
>42
0 m
l/h
6
18
1
8
1.5
-3.5
3
.1 (
0.6
) Kn
ow
sley
, En
glan
d
18
1
8
1.5
-3.5
3
.1 (
0.4
) O
ulu
, Fin
lan
d
4
4 1
.5-3
.5
3.6
(0
.3)
Rey
kjav
ik, I
cela
nd
6
6 1
.5-3
.5
3.2
(0
.5)
Haa
rlem
, th
e N
eth
erla
nd
s
21
2
1
1.5
-3.5
3
.1 (
0.4
) A
lmad
a/Se
tub
al,
Po
rtu
gal
Khan
dare
(2
002)
(23
8)
no
t d
escr
ibed
1
8
18
(10
0%
) 1
8
9-1
1
10
.7 (
1.4
) A
nd
hra
Pra
des
h,
Ind
ia
no
t d
escr
ibed
0
Kird
pon
(2
006)
(23
9)
no
t d
escr
ibed
1
3
13
(10
0%
) 1
3
9-1
3
12
.4 (
0.3
) n
ot
des
crib
ed
no
t d
escr
ibed
0
~ 62 ~
Study 1: Meta-analysis of average 24-hour urinary volume of children and adolescents
Stu
dy
Stu
dy
Year
(s)
n
Mal
e,
n(%
)
Val
id
uri
ne
sam
ple
s
Age
ra
nge
(y
ears
)
Age
, m
ean
(SD
) ye
ars
Co
unt
ry
Excl
usi
on
crit
eria
fo
r u
rine
sa
mp
les
NO
S sc
ore
(m
ax 1
0 p
oin
ts)
Kris
tbjo
rnsd
ott
ir
(201
2) (2
40)
n
ot
des
crib
ed
76
3
0 (
52%
) 5
8
5-6
6
(0
.1)
Rey
kjav
ik, I
cela
nd
P
AB
A r
eco
very
<8
5%
5
Mag
uir
e (2
013)
(24
1)
no
t d
escr
ibed
12
no
t d
escr
ibed
12
6
-7
6.6
(0
.3)
No
rth
ern
En
glan
d
i) u
rin
ary
flo
w <
5m
l/h
ou
r fo
r <
6 y
ear
old
ss a
nd
< 9
mL/
ho
ur
for
child
ren
≥6
yea
rs
ii) c
reat
inin
e ex
cret
ion
<1
1.3
m
g/kg
/day
or
>21
.1 m
g/kg
/day
7 1
1
11
6
-7
6.6
(0
.5)
13
1
3
6-7
7
.0 (
0.7
)
Mar
rero
(201
4) (2
17)
200
7-2
010
150
6
1 (
52%
) 1
26
5
-6
5.5
(0
.6)
Lon
do
n, E
ngl
and
i) t
he
par
tici
pan
t ad
mit
ted
to
h
ave
mis
sed
at
leas
t o
ne
uri
ne
colle
ctio
n
ii) 2
4-h
ou
r u
rin
ary
crea
tin
ine
of
< 0
.1m
mo
l/kg
/d
iii)
uri
ne
ou
tpu
t o
f <0
.5m
l/kg
/h
for
5-6
an
d 8
-9 y
ear
old
s o
r <5
00
mL/
24
-ho
ur
for
13
-17
ye
ar o
lds,
an
d/o
r
iv)
if t
he
tim
ing
of
the
colle
ctio
n w
as <
20
ho
urs
or
>
28
ho
urs
8 1
67
56
(50
%)
11
1
8-9
8
.5 (
0.5
)
125
5
7 (
55%
) 1
03
1
3-1
7
14
.6 (
1.3
)
~ 63 ~
Study 1: Meta-analysis of average 24-hour urinary volume of children and adolescents
Stu
dy
Stu
dy
Year
(s)
n
Mal
e,
n(%
)
Val
id
uri
ne
sam
ple
s
Age
ra
nge
(y
ears
)
Age
, m
ean
(SD
) ye
ars
Co
unt
ry
Excl
usi
on
crit
eria
fo
r u
rine
sa
mp
les
NO
S sc
ore
(m
ax 1
0 p
oin
ts)
Mar
tins
(2
011)
(24
2)
200
8
11
5
(4
5%)
11
2
-4
3.7
Ib
iá, B
razi
l(24
2)
no
t d
escr
ibed
2
Mar
uha
ma
(198
6) (2
43)
n
ot
des
crib
ed
11
6
(5
5%)
11
6
-9.9
8
(1
.3)
no
t d
escr
ibed
n
ot
des
crib
ed
0 1
1
5 (
45%
) 1
1
10
-18
1
4 (
1.9
)
Mat
kovi
c (1
995)
(24
4)
no
t d
escr
ibed
3
81
0 (
0%
) 3
59
8
-13
1
0.9
(7
.7)
Oh
io, U
nit
ed
Stat
es
"in
ap
pro
pri
ate
uri
ne
colle
ctio
ns
iden
tifi
ed b
y re
sid
ua
l an
aly
sis
aft
er f
itti
ng
a
reg
ress
ion
eq
ua
tio
n o
f 2
4-h
cr
eati
nin
e ex
cret
ion
on
LB
M a
s o
bta
ined
by
du
al-
ener
gy
X-r
ay
ab
sorp
tio
met
ry"
5
Mel
se-B
oo
nst
ra
(199
8) (2
56)
1
996
9
7
(1
00%
) 7
6-9
8
.1
Gu
atem
ala,
C
entr
al A
mer
ica
no
t d
escr
ibed
2
13
1
3(10
0%
) 1
3
8-1
2
9.7
B
enin
, Wes
t A
fric
a
Mo
ri
(201
0) (2
45)
2
002
56
5
4 (
46%
) 5
4
6-1
1
8.1
(1
.4)
Jap
an
no
t d
escr
ibed
3
364
0
(0
%)
19
3
13
-18
1
6.7
(1
.3)
Study 1: Meta-analysis of average 24-hour urinary volume of children and adolescents
~ 64 ~
Stu
dy
Stu
dy
Year
(s)
n
Mal
e,
n(%
)
Val
id
uri
ne
sam
ple
s
Age
ra
nge
(y
ears
)
Age
, m
ean
(SD
) ye
ars
Co
unt
ry
Excl
usi
on
crit
eria
fo
r u
rine
sa
mp
les
NO
S sc
ore
(m
ax 1
0 p
oin
ts)
Pad
rao
(201
6) (2
46)
201
4
86
8
6 (
100
%)
86
7
-11
8
.7 (
0.8
) P
ort
uga
l cr
eati
nin
e ex
cret
ion
<0
.1m
mo
l/kg
/day
6
86
0
(0
%)
86
7
-11
Raf
ie
(201
7) (2
47)
201
5 -
201
6
128
4
2 (
33%
) 1
28
1
1-1
8
14
.4 (
2.0
)
Isaf
ahn
, Ira
n
i) v
olu
me
<50
0m
L, a
nd
/or
ii) c
reat
inin
e ex
cret
ion
<0
.1m
mo
l/kg
/day
4
129
5
7 (
44%
) 1
29
1
1-1
8
14
.3 (
2.2
)
117
5
5 (
47%
) 1
17
1
1-1
8
14
.6 (
2.1
)
Ru
gg-G
unn
(199
3) (2
48)
no
t d
escr
ibed
27
2
7 (
100
%)
27
4
-6
no
t d
escr
ibed
Dam
bu
lla, S
ri
Lan
ka
no
t d
escr
ibed
4
26
0
(0
%)
26
4
-6
20
2
0 (
100
%)
20
4
-6
New
cast
le,
Engl
and
2
4
0 (
0%
) 2
4
4-6
Sin
aiko
(1
994)
(24
9)
no
t d
escr
ibed
40
2
0 (
50%
) 4
0
11
-14
1
3.9
(1
.3)
Min
nes
ota
, U
nit
ed S
tate
s n
ot
des
crib
ed
1
243
1
22 (
50%
) 2
43
1
1-1
4
13
.3 (
1.6
)
Study 1: Meta-analysis of average 24-hour urinary volume of children and adolescents
~ 65 ~
Stu
dy
Stu
dy
Year
(s)
n
Mal
e,
n(%
)
Val
id
uri
ne
sam
ple
s
Age
ra
nge
(y
ears
)
Age
, m
ean
(SD
) ye
ars
Co
unt
ry
Excl
usi
on
crit
eria
fo
r u
rine
sa
mp
les
NO
S sc
ore
(m
ax 1
0 p
oin
ts)
Stae
ssen
(1
983)
(25
0)
197
9 -
198
1
82
8
2 (
100
%)
82
1
0-1
9
14
.3 (
3.0
)
Bel
giu
m
"Uri
na
ry c
rea
tin
ine
excr
etio
n
wa
s p
lott
ed a
ga
inst
bo
dy
wei
gh
t af
ter
stra
tifi
cati
on
fo
r a
ge
an
d s
ex. S
ub
ject
s w
ho f
ell
ou
tsid
e th
e tw
o s
tan
da
rd
dev
iati
on
ra
ng
e o
f th
e re
gre
ssio
n li
nes
wer
e ex
clu
ded
"
4
78
0
(0
%)
78
1
0-1
9
14
.4 (
2.6
)
Tou
itou
(2
010)
(25
1)
no
t d
escr
ibed
9
9
(1
00%
) 9
9-1
1
10
.8 (
0.1
1)
Fran
ce
no
t d
escr
ibed
0
Vill
a (2
000)
(25
2)
no
t d
escr
ibed
2
0
20
(10
0%
) 2
0
3-6
4
.4 (
0.8
) Sa
nti
ago
, Ch
ile
no
t d
escr
ibed
3
Zhan
g (2
015)
(25
3)
201
2
10
5
(5
0%)
16
2
-11
1
0.0
(3
.2)
Ch
ina
uri
nar
y cr
eati
nin
e u
sed
- c
uto
ff
no
t d
escr
ibed
3
Zoh
ou
ri
(200
0) (2
54)
1
995
-1
996
7
8
no
t d
escr
ibed
7
8
3-4
.9
no
t d
escr
ibed
Fa
rs P
rovi
nce
, Ir
an
crea
tin
ine
excr
etio
n <
14
m
g/kg
/day
or
>20
mg/
kg/d
ay
3
Zoh
ou
ri
(200
6) (2
55)
200
2
7
5 (
71%
) 7
1-3
3
(0
.6)
New
cast
le,
Engl
and
" va
lida
ted
by
mea
suri
ng
th
e u
rin
ary
exc
reti
on
of
crea
tin
ine
in e
ach
24
-h u
rin
e sa
mp
le a
nd
co
mp
ari
ng
th
is w
ith
th
e st
an
da
rd r
efer
ence
va
lue
for
crea
tin
ine
excr
etio
n"
1
NO
S –
New
cast
le-O
tta
wa
Sca
le f
or
coho
rt s
tud
ies
~ 66 ~
Study 1: Meta-analysis of average 24-hour urinary volume of children and adolescents
Tabl
e 3.
4: C
hara
cter
isti
cs o
f st
ud
ies
con
side
red
fo
r th
e p
rim
ary
anal
ysis
wh
ere
24-h
ou
r u
rine
vo
lum
e w
as p
rese
nted
as
med
ian
(IQ
R),
n=7
stu
die
s
Stu
dy
Stu
dy
Year
(s)
n
Mal
e,
n(%
)
Val
id
uri
ne
sam
ple
s
Age
ra
nge
(y
ears
)
Age
, m
ean
(SD
) ye
ars
Co
un
try
Excl
usi
on
crit
eria
fo
r u
rine
sa
mp
les
NO
S sc
ore
(m
ax 1
0 p
oin
ts)
Cam
pan
ozz
i (2
015)
(26
0)
no
t d
escr
ibed
303
3
03 (
100
%)
303
6
-9
10
.1 (
2.9
) It
aly
crea
tin
ine
excr
etio
n
<0.1
mm
ol/
kg/d
ay (2
60)
6
228
2
28 (
100
%)
228
9
-11
.3
235
2
35 (
100
%)
235
1
1.4
-18
162
0
(0
%)
162
6
-9
180
0
(0
%)
180
9
-11
.3
316
0
(0
%)
316
1
1.4
-18
Deg
en
(201
1) (2
10)
1
985
-198
9
69
35
(51
%)
164
6
-10
1
0.2
(*)
Do
rtm
un
d, G
erm
any
i) c
reat
inin
e ex
cret
ion
<0
.1m
mo
l/kg
/day
ii)
sam
ple
s re
po
rted
or
fou
nd
to
co
nta
in
inco
mp
lete
mic
tura
tio
ns
4
199
0-1
994
7
0 3
5 (
50%
) 1
97
11
-13
1
3.0
(*)
Gra
ses
(2
015)
(26
1)
n.d
1
05
64
(61
%)
105
5
-17
1
2.0
(3
.0)
Maj
orc
a, S
pai
n
no
t d
escr
ibed
1
~ 67 ~
Study 1: Meta-analysis of average 24-hour urinary volume of children and adolescents
Stu
dy
Stu
dy
Year
(s)
n
Mal
e,
n(%
)
Val
id
uri
ne
sam
ple
s
Age
ra
nge
(y
ears
)
Age
, m
ean
(SD
) ye
ars
Co
un
try
Excl
usi
on
crit
eria
fo
r u
rine
sa
mp
les
NO
S sc
ore
(m
ax 1
0 p
oin
ts)
Lib
uda
(2
012)
(17
6)
200
3-2
009
15
15
(10
0%
) 1
8 3
-3.9
3
.1 (
*)
Do
rtm
un
d, G
erm
any
crea
tin
ine
excr
etio
n
<0.1
mm
ol/
kg/d
ay
6
54
54
(10
0%
) 8
3 1
3-1
4.9
1
4.0
(*)
66
66
(10
0%
) 1
45
15
-18
1
6.2
(*)
24
0 (
0%
) 2
5 3
-3.9
3
.2 (
*)
56
0 (
0%
) 8
4 1
3-1
4.9
1
4.0
(*)
70
0 (
0%
) 1
44
15
-18
1
6.2
(*)
Mo
nten
egro
-B
etha
nco
urt
(2
013)
(21
2)
200
0-2
010
146
1
46 (
100
%)
269
4
-6.9
5
.0 (
*)
Do
rtm
un
d, G
erm
any
i) c
reat
inin
e ex
cret
ion
<0
.1m
mo
l/kg
/day
ii)
co
llect
ion
tim
e <2
0 h
ou
rs
7
147
0
(0
%)
264
4
-6.9
5
.0 (
*)
Mo
nten
egro
-B
etha
nco
urt
(2
015)
(11
5)
199
6-2
002
30
30
(10
0%
) 3
0 1
3-1
8
15
.0 (
*)
Do
rtm
un
d, G
erm
any
i) c
reat
inin
e ex
cret
ion
<0
.1m
mo
l/kg
/day
ii)
no
rep
ort
ed m
isse
d
colle
ctio
ns
30
0 (
0%
) 3
0 1
3-1
8
14
.0 (
*)
Mo
nten
egro
-B
etha
nco
urt
(2
015b
) (2
13)
199
3-2
010
2
65
265
(100
%)
985
6
-13
9
.0 (
*)
Do
rtm
un
d, G
erm
any
crea
tin
ine
excr
etio
n
<0.1
mm
ol/
kg/d
ay
6
25
1
0 (
0%
) 9
74
6
-13
9
.0 (
*)
NO
S –
New
cast
le-O
tta
wa
Sca
le f
or
coho
rt s
tud
ies
~ 68 ~
Study 1: Meta-analysis of average 24-hour urinary volume of children and adolescents
7
Study 1: Meta-analysis of average 24-hour urinary volume of children and adolescents
~ 69 ~
3.4 Results
3.4.1 Summary of studies considered for primary analysis
The 43 studies considered for inclusion in the primary analysis were
published from 1981-2017 (Tables 3.3 & 3.4). Of these, 14 reported findings from
Europe (115, 176, 210, 212, 213, 226, 230, 236, 240, 246, 250, 251, 260, 261), seven from the United
Kingdom (217, 228, 236, 237, 241, 248, 255), seven from Asia (229, 231, 232, 238, 245, 248, 253), four
from North America (235, 244, 249, 256), three from South America (224, 242, 252), three
from the Middle East (223, 247, 254), two from Africa (234, 256), and one from Australia
(188). Twenty-four studies reported creatinine excretion (20, 115, 188, 210, 217, 223, 225, 226,
229, 232-234, 238, 241, 243, 244, 247, 249-251, 253, 255, 257, 260), 17 as 24-hour excretion
(mmol/24hours, mg/24hours, g/24hours) (115, 188, 217, 225, 226, 229, 232-234, 238, 243, 244, 249,
250, 253, 260), six as a ratio of creatinine to body weight (mmol/kg, mg/kg) (210, 241, 247,
251, 255, 257) and two as a ratio to urine volume (20, 223).
3.4.2 Quality of studies considered for primary analysis
The criteria used to evaluate the completeness of the urine samples was
inconsistent between studies, with 18 of the studies not providing information on
criteria used to assess the completeness of the urine samples (224, 225, 227, 229-231, 233,
238, 239, 242, 243, 245, 248, 249, 251, 252, 256, 261). Of the 25 studies which reported their urine
assessment criteria, 20 used creatinine excretion per kilogram of bodyweight (115,
176, 188, 210, 212, 213, 217, 223, 226, 232, 234, 241, 244, 246, 247, 250, 253-255, 260) based on established
age and gender specific cutoffs (116). The remaining five studies relied solely on
urine volume (236, 237), the number of reported missed collections (228), the excretion
of other nutrients (i.e. fluoride)(235), and one study utilised paraminobenzoic acid
(PABA) recovery as a measure of completeness (240). A total of nine studies utilised
urinary volume as an indicator of completeness (188, 217, 223, 228, 232, 236, 237, 241, 247), two
(188, 232) used the cut-off of 300mL/24hour based on previously published criteria
(264), two studies (236, 241) utilised the WHO criteria of <5mL/hour and <9mL/hour for
<6 and 6 year olds respectively, and two studies (217, 247) in older children (13-19
years) used the cutoff of <500mL/24hour, based on previously published criteria
Study 1: Meta-analysis of average 24-hour urinary volume of children and adolescents
~ 70 ~
(264). The cut-offs used by the remaining three studies (223, 228, 235) were based on the
distribution of volume in the sample, enabling the exclusion of extreme outliers
(e.g. 4SDs below the geometric mean (228)). Of the 25 studies which reported the
urine exclusion criteria, 6 did not report the number of urine samples excluded
from the final analysis (210, 234, 253-255, 261).
As a result of the inconsistency in the criteria used to assess the
completeness of the urine samples between studies, 23 studies (54%) scored low
on the NOS quality scale (224-226, 229-231, 233-235, 237-239, 242, 243, 245, 249, 251-256, 261) (Tables
3.3 & 3.4). Eighteen studies (42%) were classified as “medium” (115, 176, 210, 212, 223, 227,
228, 232, 236, 240, 241, 244, 246-248, 250, 260), and only two studies provided sufficient detail
regarding the 24-hour urine collection procedure to be classified as “high” quality
(188, 217) (Tables 3.3 & 3.4).
3.4.3 Initial analysis
The overall urine volume estimate (95% CI) for all 43 studies was 718 (682,
755) mL/24-hours. When broken down by age group, 19 studies reported results
for 2-6 year olds (n=1340, 1593 urine samples), 19 for 7-11 year olds (n=3736, 5174
urine samples) and 12 for 12-19 year olds (n=2230, 2359 urine samples). The
overall estimate (95% CI) for each of the three age groups were 470 (424, 516)
(Appendix D), 769 (735, 802) (Appendix E) and 1048 (973, 1123) (Appendix F)
mL/24-hours, respectively. There was a significant difference in the mean urine
volume across the three age groups (P<0.001).
3.4.4 Primary analysis limited to studies with > 1 urine assessment
criteria
Twenty-five studies reported >1 criteria for assessing the completeness of
the urine samples (n=6191, 8200 urine samples) (115, 176, 188, 210, 212, 213, 217, 223, 226, 228,
235-237, 240, 241, 244, 246, 247, 250, 253-255, 260). The overall urine volume estimate (95% CI) for
these studies was 774 (654, 893) mL/24-hours. When broken down by age group,
12 studies reported results for 2-6 year olds (n=1084, 1337 urine samples) (176, 212,
217, 223, 234-237, 240, 241, 254, 255), 11 for 7-11 year olds (n=3628, 5070 urine samples) (188,
Study 1: Meta-analysis of average 24-hour urinary volume of children and adolescents
~ 71 ~
210, 213, 217, 226, 228, 232, 234, 244, 246, 260) and seven for 12-19 year olds (n=1438, 1746 urine
samples) (115, 176, 210, 217, 234, 247, 260). The overall estimate (95% CI) for each of the
three age groups were 539 (468, 611) (Figure 3.3), 786 (749, 823) (Figure 3.4), and
1067 (855, 1279) (Figure 3.5) mL/24-hours, respectively. There was a significant
difference in the mean urine volume across the three age groups (P<0.001).
Children in the oldest age group had a 26% higher 24-hour urine volume compared
to those aged 7-11 years (1067 vs. 786 mL/24-hours, P<0.001) and a 49% higher
urine volume compared to those aged 2-6 years (1067 vs. 539 mL/24-hours,
P<0.001). Similarly, those aged 7-11 had a 31% higher volume compared to 2-6
year olds (786 vs. 539 mL/24hours, P<0.001).
The only difference in mean urine volume between those studies which had
reported at least one criteria for assessing the completeness of urine samples and
those which had reported none was amongst the 2-6 year old age group. The mean
urine volume in the initial analysis (i.e. all studies were included) was 13% lower
compared to the primary analysis (i.e. when the analysis was limited to only those
studies with >1 criteria for assessing the completeness of urine samples (470 vs.
539 mL/24-hours, P=0.04). There was no significant difference in the overall urine
volume estimate and the estimates for the other two age groups between the
initial and primary analyses (overall: 718 vs. 774 mL/24-hours; 7-11 y/olds: 769 vs.
and 786 mL/24-hours; and 12-19 y/olds: 1048 vs. 1067 mL/24-hours; all P>0.05).
Of the 25 studies with more than one criteria for assessing the
completeness of the urine samples, only eleven (115, 188, 210, 212, 217, 223, 228, 232, 235, 241,
244) had more than two urine criteria (n=2736, 3060 urine samples). In these eleven
studies, the mean (95% CI urine volume estimate was 725 (619, 832) mL/24-hours.
There was no difference in the mean (95% CI) urine volume estimate of these
studies, compared to those with only one assessment criteria (n= 14, 798 (664,
932) mL/24-hours, P=0.33) or those with none (n= 18, 635 (577, 692) mL/24-hours
P=0.28).
~ 72 ~
Study 1: Meta-analysis of average 24-hour urinary volume of children and adolescents
Figu
re 3
.3: F
ore
st p
lot
of
stud
ies
asse
ssin
g 2
4-h
ou
r u
rin
e vo
lum
es o
f 2
-6 y
ear
old
s w
ith
>1
uri
ne
asse
ssm
ent
crit
eria
(n
=10
84)
Test
fo
r h
eter
oge
nei
ty C
hi-
squ
are=
51
4.8
, df=
20
, P<0
.00
1, I
2 =9
6.7
%
Test
fo
r o
vera
ll ef
fect
z=1
4.9
, P<0
.00
1
~ 73 ~
Study 1: Meta-analysis of average 24-hour urinary volume of children and adolescents
Figu
re 3
.4: F
ore
st p
lot
of
stud
ies
asse
ssin
g 2
4-h
ou
r u
rin
e vo
lum
es o
f 7
-11
year
old
s w
ith
>1 u
rin
e as
sess
men
t cr
iter
ia (
n=3
628
)
Test
fo
r h
eter
oge
nei
ty C
hi-
squ
are=
24
8.1
, df=
17
, P<0
.00
1, I
2 =9
3.1
%
Test
fo
r o
vera
ll ef
fect
z=4
1.6
, P<0
.00
1
~ 74 ~
Study 1: Meta-analysis of average 24-hour urinary volume of children and adolescents
Figu
re 3
.5: F
ore
st p
lot
of
stud
ies
asse
ssin
g 2
4-h
ou
r u
rin
e vo
lum
es o
f 1
2-19
yea
r o
lds
wit
h >1
uri
ne
asse
ssm
ent
crit
eria
(n
=14
38)
Test
fo
r h
eter
oge
nei
ty C
hi-
squ
are=
43
52
.9, d
f=1
3, P
<0.0
01
, I2 =
99
.7%
Te
st f
or
ove
rall
effe
ct z
=9.8
9, P
<0.0
01
Study 1: Meta-analysis of average 24-hour urinary volume of children and adolescents
~ 75 ~
3.5 Discussion
This is the first study to systematically review the 24-hour urine volume of
children and adolescents. The overall 24-hour urine volume of 2-19 year olds was
less than 1L. As expected, older children had higher urine volumes with children in
the oldest age group having a 26% higher 24-hour urine volume compared to those
aged 7-11 years and a 49% higher urine volume compared to those aged 2-6 years.
Similarly, those aged 7-11 had a 31% higher volume compared to 2-6 year olds.
As approximately 90% of ingested iodine is excreted in the urine within 24-
48 hours (64), current recommendations for assessing the severity of iodine
deficiency within a population are based on the measurement of urinary iodine
concentration (UIC), expressed as µg iodine per liter of urine, in random ‘spot’ urine
samples collected from school-aged children (i.e 6-12 years (37)). Although these
recommendations were originally based on the observation that goiter prevalence
was <10% in populations of children and adults where the average daily iodine
intakes were >100 µg, later iterations extrapolated this value to represent a
concentration, expressed as µg/L. However, only in populations where mean urine
volume is equal to 1L would UIC provide an accurate reflection of total daily iodine
intake (15). Results from this analysis indicate that the average 24-hour urine volume
of school-aged children, the group commonly recommended for use in population
ioding monitoring, may not be 1L. This finding may impact on the findings of studies
conducted in children and adolescents, whereby spot UIC has been used as an
estimate of daily iodine intake as UIC would not be equivalent to daily iodine
excretion.
Furthermore, whilst these recommendations are primarily meant for use in
school-aged children, and were derived primarily on data based on goiter
prevalence estimates in school-aged children, they are often used to define the
iodine status of adult populations (265-268). Issues concerning different urinary
volume outputs among different subsets of the population and implications for
iodine nutrition assessment have previously been identified by Zimmerman and
Andersson (15). In this case, it was highlighted that as the urine volume of adults is
Study 1: Meta-analysis of average 24-hour urinary volume of children and adolescents
~ 76 ~
closer to 1.5L (269, 270), the use of the median UIC determined using spot urine
samples could result in the underestimation of the iodine intakes of individuals
within the population (15). This was demonstrated in a recent study in 301 adults
(18-64 years) from New Zealand, which compared median UIC from 24-hour urine
samples to the WHO criteria, both with and without adjustment for total urine
volume (266). This sample of adults was classified as iodine deficient using the WHO
criteria, based on a median UIC of 73 µg/L. However, the measured 24-hour UIE,
which accounts for urine volume, was closer to 127 µg/day (266). This value is in
excess of the 100 µg/day originally associated with reduced goiter prevalence (117),
and would indicate that the iodine intakes of this group of adults may be sufficient
(117). This study demonstrates the potential impact which not accounting for the
daily urine volume may have on the assessment of iodine deficiency in populations,
when UIC determined from spot urine samples is used as a surrogate index of
iodine intake.
Whilst UIC may provide an index of daily iodine intake in populations where
the daily urine volume is 1L , problems may arise if the assumption of 1L is made in
populations where the urine volume is less than 1L. For example, if we were to
assume that the average 24-hour urinary output of a population of school aged
children was 786 mL/24 hours as was determined for the 7-11 year age group, a
median UIC of 100 g/L, which indicates iodine adequacy according to the WHO
criteria (38), would correspond to an actual iodine intake of approximately 79
g/day. This level of intake is below the 100 µg/24-hours originally associated with
reduced goiter prevalence (117), and could suggest that this population may be at
risk of mild iodine deficiency. Therefore, studies which have utilised median UIC
determined from spot urine samples, as a surrogate marker of the iodine intake of
populations where the daily urinary output is less than 1L could be inaccurately
estimating and reporting iodine intakes when total daily urine volume is not
accounted for.
It is important to note that the included studies did not consistently report
the 24-hour urine collection protocol. As over/under collection of 24-hour urine
samples can bias results, studies which reported having indicators for assessing the
Study 1: Meta-analysis of average 24-hour urinary volume of children and adolescents
~ 77 ~
completeness of the included urine samples could be considered more reliable as
they are more likely to excluded over/under collectors. In the present review, 17
studies (40%) did not report at least one indicator for assessing the completeness
of the included urine samples. However, the only difference in the mean urine
volume estimate between the initial analysis including all studies and the primary
analysis limited to those studies with 1 indicator for assessing the completeness
of urine samples, was amongst the youngest age group. A recent systematic review
of methods for assessing the completeness of 24-hour urine collections in adults
and children (15-89 years) concluded that that the use of two or more indicators
for assessing urine completeness increases the likelihood of detecting incomplete
samples, thus increasing the validity of the results (215). In the present review, only
11 studies utilised more than one criteria (115, 188, 210, 212, 217, 223, 228, 232, 235, 241, 244),
however there was no difference in mean 24-hour urine volume estimated from
these studies compared to the overall estimate from all 43 studies. As such,
although the inclusion of only studies with >2 urine assessment criteria may result
in a more accurate overall volume, limiting the analysis to studies with a minimum
of 1 assessment criteria is sufficient to determine the overall urine volume of this
sample of children and adolescents.
It is also important to note that there was much wider variation in the 24-
hour urinary excretion of the oldest age group (12-19 years), compared to the
younger age groups. This is likely due to the fact that this age group encompassed
a much larger range of ages (i.e. 7 years), when compared to the other two age
groups. In this analysis it was not possible to further break this age group down into
two smaller groups, due to the age range of the included studies, and this is a
limitation of the present review which should be considered when interpreting its
findings. In addition, the adolescent growth spurt during the teenage years can
result in a rapid increase in growth over a relatively short period of time as well as
considerable variations in body size both within and between age and gender
groups (116). These variations in body size could result in subsequent variations in
overall fluid intake and as a result, variations in overall urine volume (264).
Study 1: Meta-analysis of average 24-hour urinary volume of children and adolescents
~ 78 ~
The impact of these findings on the use of UIC as an indicator of iodine
nutrition should be interpreted with caution, as urinary excretion of iodine is
dependent not only on urine volume, and can be influenced by a number of other
factors including gender, age, socio-cultural and dietary factors, drug interferences,
geographical location, and season (3-5, 18). In addition, another factor which may
need to be considered is the variability in iodine excretion within days. A number
of studies have demonstrated the wide variation in iodine excretion both within
and between days in individuals (16, 18, 26, 111, 126, 271). One study conducted in 42
adults and children (aged 4-60 years) found that urinary iodine excretion varied
significantly by timing of collection (P<0.001), with lowest levels occurring in the
morning and peaks observed following meals (16). Furthermore, a study in adults
observed that UIC determined from a fasting spot urine samples was 10% lower
than that determined in a non-fasting spot urine sample (18). Although this variation
has yet to be assessed in children, this study indicates that the timing of the spot
urine used to estimate the iodine intakes of a population may also have a significant
impact on the overall assessment of iodine nutrition. Therefore it is clear that a
number of factors need to be considered when assessing the suitability of current
recommendations for assessing the iodine nutrition of different age groups.
3.6 Conclusion
This is the first systematic review of the average 24-hour urine volume of
children and adolescents. Our ability to combine data and compare different
studies was limited by inconsistencies in the published urine collection protocol
and criteria used to define incomplete 24-hour urine collections. However, the
large number of studies representing 9,407 individuals demonstrate that the mean
urine volume of school-aged children (7-11 years) was less than 1L. This finding has
potential implications for the use of median UIC from spot urine samples as a
surrogate index of the iodine intakes of populations of children, as only in
populations where the mean urine volume is 1L would UIC provide an accurate
reflection of the iodine intakes of that population. More research is needed to
evaluate the appropriateness of current recommendations for assessing the iodine
Study 1: Meta-analysis of average 24-hour urinary volume of children and adolescents
~ 79 ~
status of populations where the average daily urine volume is not 1L. Future
research should focus on the use of functional tests of iodine deficiency, such as
measurement of serum thyroid hormone levels or thyroid volume, alongside
determination of UIC from spot urine samples in different subgroups of the
population. Such studies would help in the development more specific cut-offs for
assessing the iodine nutrition of populations where the daily urine output is not
equal to 1L using spot urine samples.
~ 80 ~
~ 81 ~
Chapter Four:
The Salt and Other Nutrient Intake in Children
(SONIC) Study Methodology
Components of this chapter have been reproduced directly from the methodological
paper describing the SONIC study published by Grimes CA, Baxter JR, Campbell KJ,
Riddell LJ, Rigo M, Liem DG, et al. Cross-Sectional Study of 24-Hour Urinary
Electrolyte Excretion and Associated Health Outcomes in a Convenience Sample of
Australian Primary Schoolchildren: The Salt and Other Nutrients in Children (SONIC)
Study Protocol. JMIR Res Protoc. 2015;4(1):e7.
4.1 Participant recruitment
The SONIC study was a cross-sectional study conducted within primary
schools located in Victoria, Australia from 2009-2013. Ethics approval was obtained
by the Deakin University Human Research Ethics Committee (Project No: EC 62-
2009).Victorian school-aged children attending government and non-government
primary schools were targeted for the Salt and Other Nutrient Intakes in Children
(SONIC) study. To enable a representative sample of children across different
socioeconomic groups, this study was initially designed to take place in government
schools. However, as this was the first Australian study to propose the collection of
24-hour urine collections within the school sector, there were difficulties in
obtaining approval from the governing education authority to conduct the study in
government schools. In order, to demonstrate the feasibility of collecting 24-hour
urine samples from schoolchildren, the study was piloted in a smaller sample of
children within the non-government school sector. This was possible as permission
to conduct research within non-government schools is granted on a school-by-
school basis by either the school board or principal.
After the successful completion of Phase 1 within non-government schools,
permission to enter government schools was granted by the Victorian Department
of Education and Early Childhood Development (2011_001151). Due to the overall
difficulties in recruiting schools to participate, a convenience sampling framework
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was used. To maximise recruitment, participation was open to all children
attending the primary school, however in some instances, the school principal did
not think it was appropriate for very young (i.e. prep – year 2) children to participate
in the study. Therefore, with respect to the requests of individual schools, the grades
invited to participate varied across schools. Participants were recruited in two
phases, first in non-government privately funded schools, and secondly in Victorian
government schools.
4.1.1 Phase One: Victorian non-government privately funded
schools
A web-based school locater search engine was used to identify all non-
government Victorian schools with enrolments of primary school children (n=193).
From this list a convenience sample of schools was selected and the principal of the
school contacted where the school was invited to participate in the study. In total
104 schools were contacted between June 2010 and June 2011, of which nine
schools agreed to participate in the study (response rate=9%). A short presentation
outlining the purpose of the study, was then presented at the school assembly.
Children were provided with information packs containing written materials
addressed to parents inviting them to take part in the study. Of the potential 1464
students, 269 agreed to participate (response rate 18%) of which 9 later dropped
out of the study. Data from six participating children were later excluded, as they
did not fall within the target age group (i.e primary school children,<13 years of
age). Written consent was obtained from the child, as well as the child’s
parent/caretaker. Children received a $20 book voucher to thank them for their
participation in the study.
4.1.2 Phase Two: Victorian government schools
Victorian government schools with enrolments for primary school children
(n=649) were identified using the Department of Education and Early Childhood
Development online school locater. A convenience sample of schools was selected
from the Eastern Metropolitan and Northern Metropolitan regions of Victoria due
to their proximity to the Burwood campus of Deakin University. No schools from
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the Western Metropolitan region were recruited as by this stage the study had
reached its funding capacity. Schools were contacted in the same manner as those
in Phase 1. In total 316 Victorian government schools were contacted between
November 2011 and May 2013, of which 47 agreed to participate. The recruitment
strategy for children differed between participating government schools. Due to
constraints on the amount of access given to the project officer within each school,
it was not always possible for the short presentation to be given in some of the
schools, whilst the information pack was not distributed to all the children at other
schools. In these instances the project officer provided a ‘recruitment starter pack’
to the school principal. These packs contained the study information packs, which
were distributed to the children at the discretion of the school principal. Across all
schools the study was advertised in the school newsletter and parents could then
contact the project officer directly to express their interest in the study and request
an information pack.
Of the potential 13,045 students invited to participate in the study, 582
agreed to participate (response rate=4.5%). Children from schools where there
were less than 10 participants (n=11) were informed that to participate they would
need to travel to Deakin University to complete testing on a Saturday. Of the 40
children that this applied to, 15 agreed to visit Deakin University; however, 7 of
these did not attend (i.e. dropouts) on the scheduled day of data collection. A
further 25 children dropped out of the study; reasons for attrition included no
longer interested in participating (n=7) or being absent on the day of data collection
(n=18). Finally, one child from a school that refused to participate attended the
Deakin University data collection day. This child was aware of the study as their
mother worked at Deakin University. Written consent was obtained from the child
as well as their parent/caretaker. Due to guidelines for inducements for study
participation in government schools, either a book voucher to the value of $20 per
participant or $100 per school was issued to the school library to thank the children
for their participation. In total 254 children from Phase 1 and 526 children from
Phase 2 participated in the study, totalling 780 children. Figure 4.1 outlines the flow
of recruitment and participation in the SONIC study (272).
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4.2 Testing Procedures
Testing procedures were conducted at the participating schools by a team
of research staff, with the exception of the one day of data collection completed at
Deakin University. Data for Phase 1 were collected across two time blocks, June-
December 2010 and May-June 2011. Data for Phase 2 were collected as schools
were recruited between November 2011 and May 2013.
4.2.1 Demographic characteristics
A health and medical questionnaire was used to collect information on the
child’s age, gender, birth weight, existing medical conditions, and the use of
medication and dietary supplements, and was completed by the child’s primary
Figure 4.1: Outline of recruitment and participation in the SONIC study
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caregiver. The questionnaire also collected information on the highest level of
education attained by the child’s primary caregiver, as a measure of Socioeconomic
Status (SES). The use of parental education as a marker of SES has consistently been
used in dietary studies in Australian children and adolescents (273-275). For the
present analyses SES will be defined as: i) high: includes those with a
university/tertiary qualification, ii) mid: includes those with an advanced diploma,
diploma or certificate III/IV or trade certificate and iii) low: includes those with a
high school diploma or lower. As this data was not available for all participants,
Socio-Economic Indexes for Areas, Index of Relative Socio-Economic Disadvantage
(SEIFA) , was used to group schools, based on school postcode, into tertiles of socio-
economic disadvantage. This marker was used as a second marker of SES, whereby
the participant was grouped as either low, mid or high SES with reference to the
tertile that the school they attended fell within.
4.2.2 Discretionary salt use characteristics
The demographic questionnaire included questions assessing the
participant’s discretionary salt use habits, relating to the primary caregiver’s use of
salt during cooking, “Do you add salt during cooking?”, as well as their child’s
addition of salt at meal times, “Does your child add salt to their meal at the table or
sandwich preparation?”. In addition, the child was also asked about their addition
of salt at the table, “Do you add salt to your meal at the table?” Responses for these
questions included ‘yes, usually’, ‘yes, sometimes’, ‘no’ or ‘don’t know’.
4.2.3 Anthropometric measurements
Height and weight were measured in participants wearing light clothing,
with shoes removed, according to standardised protocol (276). A calibrated portable
stadiometer SECA model 220 (Hamburg, Germany) was used to measure height to
the nearest 0.1cm and calibrated Scaleman FS-127-BRW portable electronic scales
(Bradman, MA, USA) were used to measure weight to the nearest 0.1 kg. A
minimum of two measurements were taken for height and weight. BMI was
calculated as body weight (kg) divided by the square of body height (m2).
Participants were grouped into weight categories (very underweight, underweight,
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healthy weight, overweight, obese) using the International Obesity Taskforce BMI
reference cut-offs for children (277, 278). Waist and hip circumference were measured
to the nearest 0.1 cm using a Lufkin Executive Thinline W606PM pocket tape
(Sparks, MD, USA) according to standardised protocol (276). A minimum of two
measurements were taken for waist and hip circumference.
4.3 24-hour urine collection
4.3.1 Procedure
For the 24-hour urine collection, each participant could elect to commence
his or her 24-hour urine at school on a weekday or at home on the weekend.
Written instructions, tailored for either a school or weekend day collection, were
provided for parents, with simplified pictorial instructions provided for the
children. Each participant was instructed to commence the collection by first
emptying their bladder, this urine was discarded and the time recorded as the 24-
hour collection start time. All urine voided during the following 24-hours was
collected into a 2.4 L wide-rimmed mouthed propylene bottle. Additional 500mL
plastic handled jugs were provided to assist with urine collection. Any missed
collections or spillages were recorded on a urine collection slip, returned with the
24-hour urine sample.
School day collections commenced at the start of the school day (i.e. 8:30-
9:30 am), with children collecting their materials to continue the collection at home
at the end of the school day (i.e. 3:00-3:30 pm). At the commencement of school
on the following day, children were instructed to visit the research staff, where
they completed the 24-hour collection by providing one final void. Children who
chose to complete the 24-hour urine collection at home on the weekend were able
to complete the collection over any 24-hour period over the weekend. Parents
were instructed to record the start and finish times on both the urine collection
bottle, as well as the urine collection slip. The following Monday morning children
returned the completed samples to the research staff at their school. The samples
were then weighed to determine the total 24-hour urine volume and following the
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original analysis for sodium (described below), 2 x 10 mL aliquots were taken per
participant and transferred to -80°C conditions for storage.
4.3.2 Validity of urine samples
If the duration of the collection was not exactly 24-hours (but within 20-28
hours) urinary sodium, iodine, creatinine and total volume were normalised to a
24-hour period (i.e. (24 h/urine duration (h)) × urinary measure). Following this
urine collections were considered incomplete and excluded if they met one or
more of the following criteria: i) the timing of the collection was <20 hours or >28
hours ;ii) total volume was <300 mL; iii) the participant reported missing more than
one collection; iv) urinary creatinine excretion was less than 0.1 mmol/Kg body
weight/day (116). Fifteen participants did not return their urine collection slip, so it
was not possible to confirm if they had missed any collections or spillages. In these
children, the completeness of the 24h urine collection was assessed based on the
other three criteria. Of the 780 participants, 757 (97%) had available results from
the 24-hour urine collection. Based on the completeness criteria 90 participants
(12%) were classified as providing invalid 24-hour urine samples and were excluded
from analyses (Figure 4.2). From the 667 participants who provided valid 24-hour
urines, 650 had at least one 10mL aliquot of urine stored in -80°C conditions. Thus,
a final sample size of 650 participants with a valid 24-hour urine sample was used
for the analyses in the present thesis.
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4.3.3 Biochemical Analysis
Sodium
Urinary sodium concentration was assessed using indirect ion selective
electrodes and urinary creatinine concentration was assessed using the Jaffe
reaction on the Siemens Advia 2400 analyser (Dorevitch Pathology, Melbourne,
Vic, National Association of Testing Authorities and Royal College of Pathologists of
Australia, accredited pathology laboratory). In the analyses involving urinary
sodium excretion, one extreme outlier for sodium excretion (mean (SD) 531 (9)
mmol/24-hour) was excluded, leaving a sample size of 649 participants.
Figure 4.2: Flow chart of urines included in iodine analysis
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Iodine
A single 10ml aliquot per participant was defrosted at room temperature
and re-aliquoted into 2mL HDPE, preservative free tubes. These samples were
immediately re-frozen and shipped on dry ice to the University of Otago, Dunedin,
New Zealand, where they were stored at -80°C until analysis under the supervision
of Associate Professor Sheila Skeaff in February-March 2015.
A modification of the method established by Pino et al (1998) (279) was used
to determine the iodine concentration of the urine samples. First, each 2mL sample
was digested with ammonium persulfate at 110°C for one hour. Arsenious acid and
ceric ammonium sulphate were then added to the cooled digested samples. During
this reaction iodine catalyses the reduction of ceric ammonium sulphate (yellow
colour) to the cerous form (colorless), known as the Sandell-Kolthoff reaction (280).
The urinary iodine concentration (UIC) of the sample (µg/L) was then determined
by measuring the extinction of the samples in a microplate reader at 405nm, and
plotting against a standard curve constructed with known amounts of iodine (range
0-300 µg/L). The internal standard used was a pooled urine sample (mean (SD)
iodine concentration of 84.1(3.8) µg/L) which gave a CV of 4.5% (n=54). Seronorm
(Sero As, Billingstad, Norway) was used as an external standard, which had a mean
(SD) iodine concentration of 131.2 (1.3) µg/L (expected range 131-150 µg/L) and a
CV of 1.0% (n=54). To determine the iodine intakes of the study population,
adjusting for the urine volume and the fact that only ~92% of iodine ingested is
excreted in urine (64), urinary iodine excretion expressed as µg/24-hour, was
determined from the urinary iodine concentration (µg/L) using the following
equation :
UIE (µg/24-hour) = UIC (μg L⁄ )×24-hour urine volume (L 24⁄ hour)
0.92
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4.4 24-hour food recall
A single three pass 24-hour dietary recall was used to determine all food
and beverages consumed from midnight to midnight on the day prior to the
interview. Recalls were completed on the day of testing at an allocated space within
the school. The method used was consistent with that used in the 2007 Australian
Children’s National Nutrition and Physical Activity Survey (CNPAS) (281). The three-
pass method includes the following stages:
1. First Pass: A ‘quick list’ of all foods and beverages and dietary supplements
consumed from midnight to midnight the day before the interview. Each ‘quick
list’ item has a unique series of probe questions which follow in the second
pass.
2. Second Pass: The ‘probe questions’ allow for further, more detailed
information, on each of the food items consumed to be collected. This includes
the time and place of consumption, the amount consumed, any additions to
the food item, brand and product name (if relevant), and the meal occasion
(i.e. breakfast, morning tea, lunch, afternoon tea, dinner, or supper, as defined
by the participant). Portion sizes were estimated using a validated food model
booklet and standard household measures. All items were hand recorded on a
food intake form by research staff with a nutrition background, who had
received training from an Accredited Practising Dietitian.
3. Third Pass: The ‘recall review’ is used to validate all information collected, and
to make any necessary corrections or additions. The interviewer reads aloud
all items consumed, as well as the place and time of consumption, brand and
product name, recipe details and portion size. All elements of the recall could
be edited, items deleted and new items added.
Children aged 8 years and older are recognised as having the cognitive
ability required to recall their own food and beverage intake (282). Children younger
than 8 years of age require a proxy (i.e. parent or caretaker) to assist in recalling
intake. Proxy interviews were not used in the SONIC study, as the dietary recall
component was completed during school time. However, all children completed
the 24-hour recall component, in order to avoid a feeling of exclusion amongst the
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younger participants. In total 776 participants completed the 24-hour recall
component. Of these, 7 were excluded due to the participant having issues
recalling their intake and 217 were excluded as they were below the age of 8 years.
A total of 552 valid 24-hour recalls completed by participants over 8 years of age
were used for the dietary analysis..
The completed 24-hour recalls were entered into the nutrient analysis
software FoodWorks (version 8, Xyris, Australia), which is linked to the AUSNUT
2011-13 nutrient database , to determine total energy (kJ/day) and iodine (µg/day)
intakes. Each food and beverage item recorded was matched to an eight-digit food
code, which corresponded to a set of nutrient data. Each eight-digit food code was
derived from a five-digit food code that represented ‘minor’ food categories (e.g.
“12201: Breads, and bread rolls, white, mandatorily fortified”). Each minor food
category falls under a three-digit sub-major food category (e.g. “122: Regular
breads, and bread rolls (plain/unfilled/untopped varieties)”), which then falls
within a two-digit major food category (e.g. “12: Cereals and cereal products”). A
detailed list of the food group classification system can be found in the 2011-13
Australian Health Survey (AHS) user guide (158). This food group coding system was
used to calculate the contribution of iodine from major, sub-major, and minor food
groups, using the population proportion method (283).
The paediatric adjusted Goldberg cut-off method was used to identify
participants with implausible energy intakes. This method compares the
participant’s ratio of reported energy intake to estimated basal metabolic rate
(estBMR) with the Goldberg cut-off value. Age- and sex-specific Goldberg cut-off
values were determined using the original adult Goldberg equation (28). On this
basis, participants (n=32, 5.8%) with an EI:estBMR ratio less than 0.87 for 8-12 year
old males and 0.84 for 8-12 year old females were classified as a low energy
reporter and excluded. Thus, a total of 520 valid 24-hour recalls were included in
the final dietary analyses.
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Chapter Five:
Study 2: Iodine intakes of Victorian school-aged
children measured using 24-hour urinary iodine
excretion
Components of this chapter have been published in: Beckford K, Grimes C,
Margerison C, Riddell L, Skeaff S, Nowson C. Iodine Intakes of Victorian
Schoolchildren Measured Using 24-hour Urinary Iodine Excretion. Nutrients.
2017;9(9):961.
5.1 Introduction
Prior to the 1990s Australia was believed to be iodine-sufficient, with the
exception of the Australian Capital Territory (ACT) and the island of Tasmania
where endemic goiter was prevalent until the introduction of an iodine
supplementation program in 1950 (12, 13). However, studies conducted in a small
sample of pregnant women (33) and Tasmanian school-aged children (130) reported
iodine deficiency in the late 1990s. Following this, a number of studies documented
iodine deficiency in Australian school-aged children (34, 35, 151, 284, 285) and adults (178,
286-289). In order to combat the re-emergence of deficiency, mandatory fortification
of all commercially produced yeast leavened bread, excluding organic varieties,
with iodised salt was implemented from October 2009 (44). Studies conducted post-
fortification utilising spot urine samples, including the 2011–2013 Australian Health
Survey (AHS), have reported an improvement in iodine status among school-aged
children and adults, when compared to pre-fortification (29, 30, 46, 47). The most
common method for monitoring the iodine status of a population is usinf spot urine
samples, as approximately 90% of ingested iodine is excreted in the urine within
24-48 hours (64, 95, 109), with a median urinary iodine concentration (UIC) ≥100 μg/L
measured in spot urine samples indicative of sufficiency (38). Due to the
considerable variation in iodine excretion over the course of the day (16-19), spot
samples are not able to provide an accurate estimate of the actual iodine intake of
a population (20, 21), however the use of a 24-hour urine sample to determine
Study 2: Iodine intakes of Victorian school-aged children measured using 24-hour urinary iodine
excretion
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urinary iodine excretion (UIE) in μg/24-hour allows for a good estimate of recent
iodine intake (22-26). Whilst the 2011-13 AHS was able to estimate iodine intakes
using 24-hour food recalls , dietary assessment methodologies are not considered
as accurate as urine samples for estimating iodine intakes due to the wide
variations in the iodine content of foods such as iodised salt, bread and milk, which
are unlikely to be captured by food databases (15, 159). A single 24-hour urine sample
is able to provide a more objective measure of actual iodine intake. To date there
have been no studies utilising 24-hour urine samples to estimate the iodine intakes
of a sample of Australian school-aged children, post fortification of bread.
5.2 Aim
To determine the total daily iodine intake of a sample of Victorian school-
aged children on one day utilising 24-hour urinary excretion of iodine and to
assess differences across age, gender, and socioeconomic status.
5.3 Methods
The study design and full methodology for this study has been described in
detail in Chapter Four
5.3.1 Participants and recruitment
See section 4.1 Participant recruitment for details.
5.3.2 24-hour urine collection
See section 4.3 24-hour urine collection procedure for details.
5.3.3 Urinalysis
See section 4.3 Biochemical analysis for details. A total of 650 participants
provided a valid 24-hour urine samples which was analysed for iodine and included
in these analyses.
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5.3.4 Statistical analysis
All analyses were completed with STATA/SE 14.0 software (StataCorp LP,
College Station, TX, USA), and a P value <0.05 was considered statistically
significant. For analysis children were grouped into age groups (4–8 years and 9–
12 years) that are consistent with the National Health and Medical Research
Council (NHMRC) Nutrient Reference Values (NRVs) for Australia and New Zealand
reference age groups (2). In order to make comparisons with results from the 2011-
13 AHS (156), results for the subgroup of participants within the age range of 5–11
years have also been reported. Initially socioeconomic status (SES) was defined
based on the highest level of education attained by the child’s primary caregiver as
follows: i) high: includes those with a university/tertiary qualification, ii) mid:
includes those with an advanced diploma, diploma or certificate III/IV or trade
certificate and iii) low: includes those with some or no level of high school
education. However, as this data was not available for all participants (n=554, 85%),
an alternative measure of SES was also used. Socio-Economic Indexes for Areas,
Index of Relative Socio-Economic Disadvantage (SEIFA) , was used to group schools,
based on school postcode, into tertiles of socio-economic disadvantage. This
marker was used to define SES, whereby the participant was grouped as either low,
mid or high SES with reference to the tertile that the school they attended fell
within.
Descriptive statistics (mean values and standard deviations or proportions
and numbers) were used to describe participant characteristics, stratified by
gender. Normality of continuous variables was assessed using box plots, histograms
and the Shapiro-Wilk test. UIE (μg/24-hour), UIC (ug/L), creatinine (mmol/24-hour),
iodine:creatinine ratio (µg/mmol) and volume (L/24-hour) were expressed as mean
(SD) as they were determined to be sufficiently normally distributed. As UIC (μg/L)
is commonly expressed as median (IQR), this has also been reported to enable
comparisons to the literature. Differences in the proportion of participants by
gender and across sociodemographic characteristics was determined using χ2 tests.
Multiple linear regression, with adjustment for school cluster was used to assess
differences in urinary parameters between age groups and socioeconomic groups.
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Linear regression, adjusted for school clustering, was used to assess differences
across socioeconomic groups (adjusted for age and gender). The unstandardised
beta co-efficient (β) has been presented for both the adjusted and unadjusted
models. The underlying assumptions of linear regression (i.e., homoscedasticity,
normality) were confirmed using regression plots of residuals.
To assess the adequacy of UIE compared to dietary recommendations, the
proportion of the population with a UIE below the age and gender specific
estimated average requirement (EAR) (i.e. 65 μg/day for 4–8 year olds and 75
μg/day for 9–12 year olds) (2) was determined using the EAR cut-point method (5)
and expressed as n (%), and chi-square (χ2) test used to assess the difference in
proportions between age and gender groups exceeding the EAR. The proportion of
the population falling below the recommended UIC of 100 μg/L and 50 μg/L, as
recommended by the World Healt Organization (WHO) (38) was expressed as n (%),
and χ2 test used to assess the differences in proportions between age and gender
groups.
5.4 Results
5.4.1 Demographic characteristics
Overall 55% of children were male, the average age was 9.3 years and 62%
and 61% were of high socio-economic background based on school postcode SEIFA
and primary caregiver education index, respectively (Table 5.1). In total, 17% of
children were either overweight or obese and more than half completed the 24-
hour urine collection on a non-school day.
5.4.2 Urinary parameters, by gender
The mean (SD) UIE and median (IQR) UIC for all participants were 104 (54)
μg/24-hour and 124 (83, 172) μg/L, respectively (Table 5.1). Whilst only 2% of
participants (n=14) had a UIC in excess of 300 µg/L, 73% of participants had a UIE
greater than the recommended EAR for their age and gender group (2). The
proportion of participants falling below the WHO recommendation of 100 μg/L
Study 2: Iodine intakes of Victorian school-aged children measured using 24-hour urinary iodine
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based on UIC (38) was less than 50%, with only 8% of the population below 50 μg/L.
Overall, males had higher UIE and UIC, compared to females (P<0.01), and more
females had a UIE below the recommended age-specific EAR.(2). In addition, a
higher proportion of females fell below the WHO recommended UIC cut-offs of 50
μg/L and 100 μg/L (38) (Table 5.1).The mean UIE of participants classified as having
a UIC below 50 μg/L (n=49) was 42 (26) μg/24-hour and 73 (38) μg/24-hour for
those with a UIC below 100 μg/L (n=233).
Table 5.1: Descriptive characteristics and urinary parameters of SONIC participants All Boys Girls
Participants, n (%) 650 359 (55) 291 (45) Age (mean (SD), years) 9.3 (1.8) 9.3 (1.9) 9.2 (1.7) Age group
4–8 years, n (%) 280 (43) 157 (44) 123 (42) 9–12 years, n (%) 370 (57) 202 (56) 168 (58) SES 1
Bottom tertile, n (%) 105 (16) 45 (13) 60 (21)a
Mid tertile, n (%) 144 (22) 77 (22) 67 (23) High tertile, n (%) 401 (62) 237 (66)a 164 (56)
SES 2 Bottom tertile, n (%) 134 (24) 77 (25) 57 (24) Mid tertile, n(%) 84 (15) 54 (17) 30 (12) High tertile, n (%) 336 (61) 183 (58) 153 (64) BMI category
Underweight, n (%) 67 (10) 34 (9) 33 (11) Healthy, n (%) 473 (73) 270 (75) 202 (69) Overweight, n (%) 91 (14) 45 (13) 46 (16) Obese, n (%) 20 (3) 10 (3) 10 (4) Day of urine collection
School day, n (%) 304 (47) 168 (47) 136 (47) Non-school day, n (%) 346 (53) 191 (53) 155 (54) UVol (mean (SD), mL/24-hour) 873 (424) 897 (453) 843 (384) UCr (mean (SD), mmol/24-hour) 5.6 (2.0) 5.8 (2.1)b 5.3 (1.9)
I:Cr ratio (mean (SD), µg/mmol) 28 (19) 29 (20) 26 (18) UIE (mean (SD), μg/24-hour) 104 (54) 112 (57)b 93 (48)
<EAR *, n (%) 177 (27) 77 (21) 100 (34)a
>EAR *, n (%) 473 (73) 282 (79)a 191 (66)
UIC (μg/L) mean (SD) 133 (68) 141 (70)b 123 (64) median (IQR) 124 (83,172) 135 (88,180) 116 (75,161) <100 μg/L, n (%) 233 (36) 114 (32) 119 (41)a
<50 μg/L, n (%) 49 (8) 20 (6) 29 (10)a
SONIC: Salt and Other Nutrient Intakes in Children study (Victoria); SES: Socioeconomic status; BMI: body mass index; UVol: urine volume; UCr: urinary creatinine; UIE: urinary iodine excretion; EAR: estimated average requirement; UIC: urinary iodine concentration * EAR for 4–8 year olds: 65 μg/day, 9–13 year olds: 75 μg/day (2) 1 SES based on state-based socioeconomic indexes for areas, index of relative socioeconomic disadvantage ; 2 SES based on primary caregiver education—data not available for all 650 participants, n=554 a χ2 test p<0.05 for differences between genders; b Multiple regression adjusted for age and school cluster p<0.05 for difference between genders.
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5.4.3 Urinary parameters, by age
A 1 year increase in age was associated with a 6 μg/24-hour increase in
iodine excretion and accounted for 4% of the variance in UIE (R2=0.04, β(SE)=5.83
(1.40, P<0.001). This association remained significant after adjustment for gender
(R2=0.07, β=5.71 (1.37), P<0.001). Children in the 9–12 year age group had a 15%
higher mean UIE compared to the 4–8 year old participants (Table 5.2, P<0.001).
There was no significant difference in UIC or the proportion of participants falling
below 100 and 50 μg/L between the two age groups, nor was there a difference in
the proportion of participants with a UIE meeting the age-specific EAR. When
broken down into the AHS age group of 5–11 year olds (n=617), the median (IQR)
UIC was 124 (83, 172) μg/L and mean (SD) UIC and UIE were 133 (67) μg/L and 102
(52) μg/24-hour, respectively. The proportion of 5–11 year old participants with
median UIC below 50 and 100 μg/L were 36% and 7%, respectively.
Table 5.2: Urinary parameters of SONIC participants, by age group (n=650). Age Group (Years)
4–8 (n=280)
9–12 (n=370)
UVol (mean (SD) , mL/24-hour) 749 (341) 966 (456) a
UCr (mean (SD), mmol/24-hour) 4.3 (1.3) 6.5 (2.0) a
I:Cr ratio (mean (SD), µg/mmol) 35 (23) 22 (13) a UIE (mean (SD), μg/24-hour) 94 (48) 111 (57) a
<EAR *, n (%) 80 (29) 97 (26)
>EAR *, n (%) 200 (71) 273 (74)
UIC (mean (SD), μg/L) mean (SD) 138 (69) 129 (67)
median (IQR) 127 (86,175) 122.3 (80,170) <100 μg/L, n (%) 89 (32) 144 (39)
<50 μg/L, n (%) 19 (7) 30 (8)
SONIC: Salt and Other Nutrient Intakes in Children study (Victoria); UVol: urine volume; UCr: urinary
creatinine; UIE: urinary iodine excretion; EAR: estimated average requirement; UIC: urinary iodine
concentration
* EAR for 4–8 year olds: 65 μg/day, 9–13 year olds: 75 μg/day (2) a Linear regression (adjusted for gender and school cluster) p < 0.05 for differences between age
groups
Study 2: Iodine intakes of Victorian school-aged children measured using 24-hour urinary iodine
excretion
~ 99 ~
5.4.4 Urinary parameters, by socioeconomic status
There was no significant effect of SES based on school postcode on UIC, UIE,
or the proportion meeting the recommendations for EAR or UIC cut-offs (Table 5.3).
When SES was based on primary caregiver education there was no change in these
findings (Table 5.4).
Table 5.3: Urinary parameters of SONIC participants by school postcode socioeconomic status mean (SD) (n=650)
Table 5.4: Urinary parameters of SONIC participants, by parental education socioeconomic status mean (SD) (n=554)1
SES category
Bottom tertile
(n=134)
Mid tertile
(n=84)
Top Tertile
(n=336)
UVol (mean (SD), ml/24-hour) 817 (408) 897 (366) 868 (419)
UCr (mean (SD), mmol/24-hour) 5.7 (2.3) 5.5 (1.7) 5.3 (2.0)
I:Cr ratio (mean (SD), µg/mmol) 28 (23) 25 (18) 29 (19)
UIE (mean (SD), mg/24-hour) 97 (46) 99 (52) 103 (56)
<EAR*, n(%) 38 (29) 25 (30) 98 (29)
>EAR*, n(%) 96 (72) 59 (70) 238 (71)
UIC (mg/L)
mean (SD) 135 (71) 124 (72) 133 (67)
median (IQR) 131 (75, 174) 109 (67, 172) 122 (84, 171)
<100mg/L, n(%) 46 (35) 38 (45) 123 (37
<50mg/L, n(%) 12 (9) 10 (12) 23 (7)
SONIC: Salt and Other Nutrient Intakes in Children study (Victoria); UVol: Urine volume; UCr: Urinary
creatinine; UIE: Urinary Iodine Excretion; EAR: Estimated Average Requirement; UIC: Urinary Iodine
Concentration 1 Data not available for all 650 participants; * EAR for 4-8 year olds: 65mg/day, 9-13 year olds: 75mg/day
SES Category
Bottom Tertile (n=105)
Mid Tertile (n=144)
Top Tertile (n=401)
UVol (mean (SD), mL/24-hour) 868 (478) 813 (405) 896 (415) UCr (mean (SD), mmol/24-hour) 5.7 (2.1) 5.1 (1.7) 5.7 (2.1) I:Cr ratio (mean (SD), µg/mmol) 29 (18) 31 (22) 26 (18) UIE (mean (SD), μg/24-hour) 115 (53) 100 (47) 102 (56) <EAR *, n (%) 20 (20) 38 (26) 119 (30) >EAR *, n (%) 85 (81) 106 (74) 282 (70) UIC (μg/L) mean (SD) 150 (70) 139 (72) 127 (65) median (IQR) 136 (89,195) 130 (85,175) 121(78,166) <100 μg/L, n (%) 32 (30%) 48 (33) 153 (38) <50 μg/L, n (%) 2 (2%) 11 (8) 36 (9)
SONIC: Salt and Other Nutrient Intakes in Children study (Victoria); UVol: urine volume;
UCr: urinary creatinine; UIE: urinary iodine excretion; EAR: estimated average requirement; UIC:
urinary iodine concentration
* EAR for 4–8 year olds: 65 μg/day, 9–13 year olds: 75 μg/day (2).
Study 2: Iodine intakes of Victorian school-aged children measured using 24-hour urinary iodine
excretion
~ 100 ~
5.5 Discussion
The mean UIE of both age groups exceeded the age-specific EAR indicating
that, overall, the iodine intakes of this group of schoolchildren are sufficient. These
data are supported by the observation that the median UIC of 124 μg/L exceeds
the recommended 100 μg/L set by the WHO indicative of adequate iodine status.
Age and male gender were significant predictors of UIE, albeit minimally, and this
is most likely due to a greater overall food intake in boys. There was, however, no
difference in UIE between the different socioeconomic groups. These findings,
along with those of other studies conducted post-fortification of bread with iodised
salt (32, 47), provide evidence that compared to pre-fortification data Australian
schoolchildren are now iodine replete. Therefore, it appears that the iodine intakes
of Australian schoolchildren have increased to sufficiency since the introduction of
mandatory fortification of bread with iodised salt.
The mean UIC of 5–11 year olds in our study, as determined using 24-hour
urine samples, was 124 μg/L compared to 178 μg/L in the same age group assessed
by spot urine samples in the 2011-13 AHS, with a higher proportion of participants
falling below the recommended cut-off of 100 μg/L when compared to the AHS
(36% vs. 20%) (45). It is not unusual to observe lower iodine excretion rates in
Victoria, when compared to the rest of Australia, with studies conducted both pre-
and post-fortification observing significantly lower iodine excretion amongst
Victorians (13, 34, 43, 156, 285). In the AHS in particular, Victorians aged 18 years and over
had a 10% lower median UIC compared to the Australian average (113 vs. 124 μg/L)
as well as 11% more participants with a UIC below 100 μg/L (42% vs. 37%)(156).
Reasons for the regional variation in iodine intakes within Australia are not well
established, but could be related to possible regional variations in the iodine
concentration of soil, milk, and differences in water iodine levels (290).
Another reason for the differences between the results in the present study
and those of the AHS may be due to the differences in the urinary methodologies.
Whilst the AHS utilised spot urine samples, the present study measured UIC in 24-
hour urine samples (16, 18). Previous studies comparing 24-hour UIC and spot UIC in
schoolchildren (20, 115) have found that spot UIC tends to be lower than 24-hour UIC,
Study 2: Iodine intakes of Victorian school-aged children measured using 24-hour urinary iodine
excretion
~ 101 ~
by approximately 10% (20, 115). Conversely, the 24-hour UIC observed in the present
study was 30% lower than the spot UIC observed in the AHS. This could be due to
the timing of the spot samples in the AHS compared to previous studies, as it has
been demonstrated that spot UIC can vary significantly depending on the timing of
the sample collection (18, 19, 111, 126). One study in 60 Brazilian adults observed a 30%
lower UIC in morning spot samples, compared to overnight samples (183 vs. 253
μg/24-hour, P<0.001) (19). It is important to note that the studies comparing spot
and 24-hour UIC in school-aged children utilised first morning spot samples (20, 115)
whereas the AHS did not specify a time for the spot urine collection (291). Therefore
the urine samples in the AHS could have been collected overnight when iodine
excretion is highest, and this might explain the higher UIC observed in the AHS,
when compared to the 24-hour UIC observed in the present study.
A recent systematic review of studies comparing spot and 24-hour urines
for estimating the iodine intakes of a population concluded that there is currently
not enough evidence to determine whether UIC determined from spot urine
samples provides an accurate reflection of 24-hour UIE (27). Subsequently the
authors of this review recommend that, whilst spot urines provide a good reflection
of the iodine status of a population, 24-hour urine samples should be used to
determine the iodine intakes of a population. In the present study, the mean 24-
hour UIE, as an indicator of daily iodine intake, of both age groups exceeded the
EAR without exceeding the recommended upper level of intake of 300 μg/day (2).
The iodine intakes determined using 24-hour UIE in the present study were 40%
lower than the iodine intakes determined using 24-hour food recalls in the AHS (i.e.
94 vs. 156 μg/day for 4–8 year olds and 111 vs. 179 μg/day in 9–13 year olds) (45).
As previously discussed, it is not unusual to observe lower iodine intakes in
Victorians and this could explain the lower intakes observed in the present study
compared to the AHS. Furthermore, the present study utilised 24-hour urine
samples which are able to provide a more objective measure of actual iodine intake
when compared to 24-hour food recalls. In addition to the recall and subject biases
associated with food recalls food composition databases often lack specificity
regarding the use of iodised salt during food production and the salt iodine content
Study 2: Iodine intakes of Victorian school-aged children measured using 24-hour urinary iodine
excretion
~ 102 ~
(49, 50, 159). Furthermore, the iodine content of dairy products in particular is highly
variable and can depend on a number of factors including the breed of cow,
supplementation of feed, the use of salt licks, farm location and contamination by
iodophore sanitisers during processing (165, 166, 168). These variations are often not
captured by food composition databases and this can result in inaccurate
estimations of iodine intakes when dietary assessment methodologies are used (15,
159, 167).
The present study also determined that iodine intake, as measured using
UIE, was significantly lower in females, with a higher proportion of female
participants having a UIE below the age-specific EAR. To date, this is the first
Australian study to utilise 24-hour urine samples to assess differences in iodine
intakes, as measured using UIE, between genders. The lower intake of iodine in
females is of concern as dietary habits tend to track into adulthood and low iodine
intakes during childhood could lead to females entering pregnancy with suboptimal
iodine status. Iodine is an important nutrient during pregnancy, and deficiency
during this time has been linked with impaired growth and cognition during
childhood (66, 292). Therefore, it is important that the iodine intakes of school-aged
children, particularly females, continue to be monitored using 24-hour urine
samples.
The major strength of the present study is the use of 24-hour urine samples
to objectively measure iodine intake in a relatively large number of Victorian
schoolchildren. A stringent 24-hour urine collection protocol, specifically tailored
to children was used to ensure the completeness of the samples. Limitations of this
study include the convenience sampling method, which resulted in the over-
representation of participants from a higher socioeconomic background.
Regardless of which SES definition was used, almost two-thirds of the participants
were from a high socioeconomic background, compared to 28% of 5–11 year olds
(based on parental education) in the AHS (293), and this limits applicability of the
findings to the general population. Finally, as the present study was limited to a
single 24-h urine collection, adjustments for the within person variation in 24-hour
Study 2: Iodine intakes of Victorian school-aged children measured using 24-hour urinary iodine
excretion
~ 103 ~
urinary iodine excretion could not be made, in order to obtain a measure of long-
term ‘usual’ iodine intake.
5.6 Conclusions
In conclusion, this is the first study to assess the iodine intakes of Australian
school-aged children post- fortification of bread with iodised salt using 24-hour
urine samples. Both daily UIE and UIC determined from 24-hour samples indicate
that the iodine intakes of this population are sufficient. These results confirm the
results of the AHS and indicate that the iodine intakes of Victorian schoolchildren
have increased to adequacy since mandatory fortification of bread with iodised salt
was introduced in 2009. However, continued monitoring of iodine intakes using 24-
hour urine samples is needed in order to ensure that the actual iodine intakes of
school children are sufficient.
~ 104 ~
~ 105 ~
Chapter Six:
Study 3: Food sources of iodine and association
with urinary iodine excretion
6.1 Introduction
Iodine is a trace element found in low concentrations in soil, air and the sea
(3-5). In the past, the most abundant food source of iodine was milk, both through
naturally occurring iodine as well as the contamination of milk by iodophor-
containing sanitisers used during milk processing (51, 130, 163, 164). Following the re-
emergence of iodine deficiency in Australia in the late 1990s (14, 34, 35, 52, 287, 294) a
number of fortification strategies were discussed by experts and government
bodies (154). From October 2009 mandatory fortification of all commercially
produced yeast leavened bread, excluding organic varieties, with iodised salt was
implemented nationally in Australia , due to the success of a similar voluntary
fortification strategy in Tasmania between 2001-2005 (32). Whilst the legislation
also stipulates that iodised salt may replace non-iodised salt in other baked
products, its addition during processing is at the discretion of the manufacturer (44).
Utilising dietary information obtained from 24-hour recalls, the 2011-13
Australian Health Survey (AHS) reported that bread and milk were the major food
sources of iodine in the Australian population (45). Furthermore, a recent analysis of
the AHS found that consumption of 100g of bread per day was associated with 12
times greater odds of achieving adequate dietary iodine intakes above the age
specific Estimated Average Requirement (EAR), amongst 2-18 year olds (46). The
iodine intakes determined in the AHS were based purely on dietary intake derived
from 24-hour dietary recalls, however 24-hour urine samples are able to provide
an objective measure of iodine intakes as approximately 90% of dietary iodine is
excreted in the urine (64, 94).To date no studies have examined the association
between food sources of iodine and urinary iodine excretion (UIE) over a 24-hour
period. Understanding the contribution of key food sources of iodine to urinary
iodine excretion, as an objective measure of total daily iodine intake, is important
Study 3: Food sources of iodine and association with urinary iodine excretion
~ 106 ~
when assessing the success of fortification strategies, as well determining how food
choices may influence iodine intake among Australian school-aged children.
6.2 Aims
i) To determine the dietary intake and food sources of iodine in a sample of
Victorian school-aged children.
ii) To assess the relationship between dietary intake of iodine and the major food
sources of iodine, including bread and milk, and urinary excretion of iodine over a
24-hour period.
6.3 Methods
The study design for this study has been described in Chapter Four
6.3.1 Participants and recruitment
See section 4.1 Participants and recruitment for details. Of the 780
participants in the Salt and Other Nutrient Intake in Children (SONIC) study, 454
had both a valid 24-hour food recall and a 24-hour urine sample analysed for iodine
and have been included in these analyses. Logistically it was not possible to
concurrently collect 24-hour dietary recalls alongside the 24-hour urine collection.
Instead 24-hour recalls were collected with children on the day of testing
procedures completed at the school site. As such, n=12 (3%) provided their dietary
recall and 24-hour urine collection on the same day, n=75 (17%) within two days,
n=29 (7%) collected within a 2-week period, and n=14 (3%) within a 6-week period)
(272).
6.3.2 Measures
See section 4.2 Testing procedures for details
6.3.3 24-hour food recall
See section 4.4 24-hour food recall for details.
Study 3: Food sources of iodine and association with urinary iodine excretion
~ 107 ~
6.3.4 24-hour urine collection
See section 4.3 24-hour urine collection for details.
6.3.5 Urinalysis
See section 4.3.3 Biochemical analysis for details.
6.3.6 Statistical analysis
Analyses were completed with STATA/SE 14.0 software (StataCorp LP), and
a P value <0·05 was considered statistically significant. Descriptive statistics (mean
values and standard deviations or proportions and numbers) were used to describe
participant characteristics, stratified by gender. Normality of continuous variables
was assessed and confirmed using box plots, histograms and the Shapiro-Wilk test.
Differences in the proportion of participants by gender across sociodemographic
characteristics was determined using 2 tests. Multiple linear regression, which
allows for the adjustment for clustering of students within schools, was used to
examine the differences in energy intake, dietary iodine intake and UIE between
genders. Pearsons correlation and multiple linear regression were used to assess
the association between the two methods of estimating iodine intake (dietary
assessment vs. urinary excretion). The unstandardised beta coefficient (β) and
standard error (SE) have been presented for all regression analyses. To assess the
adequacy of UIE and dietary iodine compared to dietary recommendations, the
proportion of the population with a UIE or Dietary iodine intake below the age and
gender specific estimated average requirement (EAR) (i.e. 65 μg/day for 4–8 year
olds and 75 μg/day for 9–12 year olds) (2) was determined using the EAR cut-point
method (5) and expressed as n (%), and chi-square (χ2) test used to assess the
difference in proportions between bread and milk consumption groups exceeding
the EAR.
Previous analyses in this sample determined that salt intakes were
significantly higher on non-school days compared to school days (295). Therefore,
we examined the differences in iodine intakes (dietary assessment and urinary
excretion) and food sources between school days and non-school days using
Study 3: Food sources of iodine and association with urinary iodine excretion
~ 108 ~
multiple linear regression (adjusted for age, gender, energy intake and school
clustering). Contribution of food groups to total iodine intake was expressed as
mean %. A ‘consumer’ was defined as any participant who consumed >0g of the
specified food on the day of the recall. Pearsons correlation and multiple regression
(adjusted for age, gender, energy intake and school cluster) were used to assess
the association between intake of food sources which contributed >1% of total
iodine (g/day) and UIE.
As the primary vehicle for iodine fortification in Australia is iodised salt
added to bread , we further examined the relationship between known iodine
fortified bread products and UIE specifically. For the purpose of these analyses,
‘Bread’ (g/day) includes all food items eaten within the 3-digit food group “122:
Regular breads, and bread rolls (plain/unfilled/untopped varieties)” and “123:
English-style muffins, flat breads, and savoury and sweet breads” food groups,
excluding any homemade and organic varieties in accordance with the foods which
are required to have iodised salt added to them under the 2009 mandatory
fortification legislation (44). This definition does not include bread which may have
been consumed as a commercially produced sandwich/hamburger which would fall
within the “135: Mixed dishes where cereal is the main ingredient category” and
would encompass the contribution of iodine from all components of the dish, as
opposed to the bread alone. In addition, as recent analyses of the AHS revealed
that milk is still a major contributor to iodine intakes (46), we also examined the
relationship between milk intake and UIE. ‘Milk’ g/d) includes all items consumed
within the 3-digit sub-major food group “191: Dairy milk (cow, sheep and goat)”
(158). The association between consumption of >100g bread or milk per day and UIE
was assessed using multiple linear regression, adjusted for age, gender, energy
intake and school cluster.
To further examine the relationship between bread and/or milk
consumption and UIE, multiple linear regression, adjusted for age, gender, energy
intake and school clustering, was used to compare differences in UIE and iodine
intake as assessed by 24-hour recall between consumers and non-consumers of
bread or milk. We also conducted a second analysis whereby consumers were
Study 3: Food sources of iodine and association with urinary iodine excretion
~ 109 ~
further broken down into consumers of neither (i.e. consumed neither bread nor
milk on the day of the survey), either (i.e. reported consuming either bread or milk
on the day of the recall) or both (i.e. consumed both bread and milk on the day of
the recall). In this model which included multiple comparisons between the
different consumption groups, non-consumers (i.e. did not report consuming both
bread and milk on the day of the recall) were used as the reference group and the
Bonferroni correction for P-values was used.
6.4 Results
6.4.1 Demographic characteristics
Of the 454 participants who provided valid urinary and dietary data, 55%
were male with an average age of 10 years (Table 6.1). Most (81%) participants
completed the 24-hour recall on a school day, whereas just under half (49%)
completed the 24-hour urine collection on a school day. The number of days
between dietary recall and urine collection ranged between 0 and 10 (median 8)
days: 49% of participants (n=224) completed the urine and dietary recall on the
same type of day (i.e. school day/non-school day), with a further 84% (n=380)
completing dietary assessment and urine collections within a week of each other
and 17% (n=75) completing the two components within two days of one another.
Mean energy intake was 8561 (2660) kJ/day, with males having a significantly
higher energy intake than females (Table 6.1).
6.4.2 Iodine intakes
Mean (SD) UIE and dietary iodine were 108 (54) µg/24-hour and 172 (74)
µg/day, respectively (Table 6.1.) There was a significant, weak, positive relationship
between iodine intake determined using the food recall and UIE (r=0.23 P<0.001).
Regression analysis revealed that a 10 µg/day increase in dietary iodine was
associated with a 3.2 µg/24hour increase in UIE (R2=0.054, =3.22 (0.63)(SE),
P<0.001). In participants who completed the recall and urine components on the
same day (n=12, 3%), a 10 µg/day increase in dietary iodine was associated with a
6.3 µg/24-hour increase in UIE (R2=0.26, =6.32 (1.81)(SE), P=0.04).
Study 3: Food sources of iodine and association with urinary iodine excretion
~ 110 ~
Males had significantly higher intakes of dietary iodine and UIE (both
P<0.001, Table 6.1). Whilst UIE was 10% higher on non-school days compared to
school days (Table 6.1), there was no difference in dietary iodine intake assessed
by 24-hour food recall between the different day types.
Table 6.1: Descriptive characteristics of SONIC participants with both a valid food recall and urine sample (n=454)
All Boys Girls
Participants, n (%) 454 249 (55%) 205 (45%) Age (mean (SD), years) 10.1 (1.25) 10.3 (1.3) 9.9 (1.2) SES1 Lowest tertile, n (%) 82 (18%) 36 (14%) 46 (22%) Mid tertile, n (%) 88 (19%) 42 (17%) 46 (22%) High tertile, n (%) 284 (63%) 171 (69%)a 113 (56%) BMI category Underweight, n (%) 33 (7%) 14 (6%) 19 (9%) Healthy, n (%) 330 (73%) 191 (77%) 139 (68%) Overweight, n (%) 76 (17%) 36 (14%) 40 (20%) Obese, n (%) 15 (3%) 8 (3%) 7 (3%) Day type of recall School day, n (%) 369 (81%) 206 (83%) 163 (80%) Non-school day, n (%) 58 (19%) 43 (17%) 42 (20%) Energy intake (kj/day) 8561 (2660) 8897 (2815)b 8152 (2402) Iodine intake (µg/day) 172 (74) 183 (80)b 159 (64) School day (µg/day) 172 (75) 182 (81)b 160 (65) Non-school day (µg/day) 169 (70) 185 (77)b 154 (60) Day type of urine School day 221 (49%) 124 (50%) 97 (47%) Non-school day 233 (51%) 125 (50%) 108 (53%) UIE (µg/24-hour) 108 (54) 118 (57)b 95 (47) School day (µg/24-hour) 102 (50)c 111 (52)b,c 89.9 (45)c
Non-school day (µg/24-hour) 113 (57)c 125 (61) b,c 99.5 (48)c
SONIC: Salt and Other Nutrient Intakes in Children study (Victoria); SES: socioeconomic status;
BMI: body mass index; UIE: Urinary Iodine Excretion 1 SES based on state-based socioeconomic indexes for areas, index of relative socioeconomic
disadvantage (296) a 2 p-value <0.01; b Multiple regression adjusted for age and school cluster P<0.05 for
difference between genders; c Multiple regression adjusted for age, gender and school cluster
P<0.05 for difference between school day and non-school day
Study 3: Food sources of iodine and association with urinary iodine excretion
~ 111 ~
6.4.3 Food sources of iodine
Table 6.2 presents the food groups which contributed 1% of total dietary
iodine. The two major sources of dietary iodine were ‘Cereals and cereal products’
(35%) and ‘milk products and dishes’ (35%). Ninety-eight percent of participants
(n=445) reported consuming a food from the ‘cereals and cereal products’ major
food category on the day of the recall and 89% (n=402) consumed an item from
the ‘milk products and dishes’ major food category. ‘Regular breads and bread rolls’
contributed 27% of total dietary iodine intake, with 78% of participants consuming
an item from this category (Table 6.2). Similarly, ‘Dairy milk (cow sheep and goat)’
contributed 25% of total dietary iodine, with 69% of participants consuming dairy
milk on the day of the recall.
When intake of iodine fortified bread products (i.e. based on the previously
defined ‘bread’ definition) was examined, bread contributed 31% of total dietary
iodine intake. Whilst consumption of an iodine fortified bread product was
significantly higher on school days compared to non-school days (93 (67) vs. 70 (66)
g/day, P=0.02), there was no difference in milk intake between school days and
non-school days (196 (205) vs. 171 (182) g/day, P=0.2).
Table 6.2: Food sources of iodine in SONIC participants >8y/o with both a valid food recall and urine sample (n=454)
Food Group Name (158) %
Consuming %
Contribution
Non-alcoholic beverages (total %) 94 5.5
Fruit and vegetable juices, and drinks 37 1.4
Fruit juices, commercially prepared 32 1.2
Waters, municipal and bottled, unflavoured 77 1.9
Domestic water (including tap, tank/rain water) 77 1.9
Cereals and cereal products (total %) 98 35.4 Regular breads, and bread rolls (plain/unfilled/untopped varieties)a
78 26.7
Breads, and bread rolls, white, mandatorily fortified 18 5.8 Breads, and bread rolls, white, not stated as to
fortification 35 9.1
Breads, and bread rolls, mixed grain, mandatorily fortified
5 1.2
Breads, and bread rolls, mixed grain, not stated as to fortification
8 2.2
Breads, and bread rolls, wholemeal and brown, mandatorily fortified
8 2.5
Study 3: Food sources of iodine and association with urinary iodine excretion
~ 112 ~
Table 6.2: Food sources of iodine in SONIC participants >8y/o with both a valid food recall and urine sample (n=454)
Food Group Name (158) %
Consuming %
Contribution Breads, and bread rolls, wholemeal, not stated as to
fortification 11 3.7
English-style muffins, flat breads, and savoury and sweet breads a
21 5.0
Flat breads (e.g. Pita bread), wheat based 6 1.3
Savoury filled or topped breads and bread rolls 5 1.2
Breakfast cereals, hot porridge style 7 1.7
Porridge style, oat based 7 1.7
Cereal based products and dishes (total %) 86 11.7
Cakes, muffins, scones, cake-type desserts 28 2.7
Mixed dishes where cereal is the major ingredient 31 6.5
Pizza, saturated fat ≤5 g/100 g 7 1.7 Savoury pasta/noodle and sauce dishes, saturated fat ≤5 g/100 g
9 1.1
Fish and seafood products and dishes (total %) 14 2.2
Fish and seafood products (homemade and takeaway) 4 1.0
Egg products and dishes (total %) 9 2.0
Eggs 7 1.3
Eggs, chicken 7 1.3
Meat, poultry and game products and dishes (total %) 75 2.5 Mixed dishes where poultry or feathered game is the major component
11 1.1
Milk products and dishes (total %) 89 35.3
Dairy milk (cow, sheep and goat) 69 24.9
Milk, cow, fluid, regular whole, full fat 32 11.9
Milk, cow, fluid, reduced fat, <2 g/100g 21 7.6
Milk, fluid, unspecified 14 4.0
Yoghurt 15 2.6
Yoghurt, flavoured or added fruit, full fat 9 1.7
Cheese 40 2.0
Cheese, hard cheese ripened styles 29 1.6
Frozen milk products 22 2.9
Ice cream, tub varieties, fat content >10 g/100 g 13 1.9
Flavoured milks and milkshakes 6 2.0
Milk, coffee/chocolate flavoured and milk-based drinks, full fat
4 1.5
Vegetable products and dishes (total %) 69 1.7
Other* - 3.7
SONIC: Salt and Other Nutrient Intakes in Children study (Victoria) *Other includes foods contributing less than 1% iodine - fats and oils; fruit products and dishes; dairy & meat substitutes; soup; seed and nut products and dishes; savoury sauces and condiments; legume and pulse products and dishes; snack foods; sugar products and dishes; alcoholic beverages; special dietary foods; miscellaneous; and infant formulae and foods a Included in “bread” definition as included in mandatory fortification legislation
Study 3: Food sources of iodine and association with urinary iodine excretion
~ 113 ~
6.4.4 Relationship between food sources of iodine and UIE
The total amount of bread consumed (g/day) was not associated with UIE
(Figure 6.1), however there was a significant, weak correlation between the
amount of milk consumed (g/day) and UIE (r=0.15, P=0.001, (Figure 6.2)).
Regression analysis indicated that a 100 g/day increase in milk intake was
associated with a 4 µg/24-hour higher UIE and accounted for 2% of the variance in
UIE (R2=0.02, β=4.03 (0.90)(SE), P<0.001). The combined weight of bread and milk
(g/day) consumed was also associated with UIE (r=0.67, P<0.001, (Figure 6.3)), with
a 100g increased intake of bread and milk combined associated with a 4 µg/24-
hour higher UIE and accounted for 3% of the variance in UIE (R2=0.03, β=4.21
(0.90)(SE), P<0.001). Both associations remained significant after adjustment for
age, gender and energy intake. There was no difference in the association between
UIE and bread, milk and combined bread and milk intake in consumers whose
dietary recall and urine were completed within one week of each other compared
to those whose recall and urine were completed >1 week apart. (Appendix G)
Thirty-seven percent of participants consumed >100 g bread/day however
consumption of >100 g/day was not significantly associated with UIE (P=0.26).
Comparatively, 62% of participants reported consuming >100 g milk/day and
regression analyses indicated that consumption of >100 g milk/day was associated
with a 10.8 µg/24-hour increase in UIE after adjustment for age, gender, energy
intake and school cluster (R2=0.09, β=10.79 (4.60)(SE), P=0.02).
Study 3: Food sources of iodine and association with urinary iodine excretion
~ 114 ~
Figure 6.1: Relationship between grams of bread consumed and 24-hour urinary iodine
excretion among SONIC participants with both a valid food recall and urine sample
(n=454)
Figure 6.2: Relationship between grams of milk consumed and 24-hour urinary iodine
excretion among SONIC participants with both a valid food recall and urine sample
(n=454)
Study 3: Food sources of iodine and association with urinary iodine excretion
~ 115 ~
Figure 6.3: Relationship between grams of bread and milk consumed and 24-hour
urinary iodine excretion among SONIC participants with both a valid food recall and
urine sample (n=454)
Tabl
e 6.
3: U
rina
ry Io
din
e Ex
cret
ion
an
d d
ieta
ry io
din
e in
take
by
con
sum
ptio
n o
f b
read
an
d m
ilk (
n=4
54)
B
read
1 M
ilk1
Bre
ad &
Milk
2
No
n-c
ons
umer
s C
on
sum
ers
No
n-c
on
sum
ers
Co
nsu
mer
s N
eith
er
Eith
er
Bo
th
n (
%)
68
(15
%)
38
6 (
85
%)
14
1 (
31
%)
31
3 (
69
%)
11
(3
%)
18
7 (
41
%)
25
6 (
56
%)
Die
tary
iod
ine
(mea
n (
SD),
µg/
24-h
ou
r)
138
(64
) 1
78
(7
4)a
14
0 (
55
) 1
86
(7
7)a
10
1 (
53
) 1
44
(5
7)b
19
5 (
77
)c,d
<E
AR
*, n
(%
) 8
(1
2%)
13
(3
%)e
15
(1
1%
) 6
(2
%)e
4 (
36
%)
15
(8
%)
2 (
1%
)
≥
EAR
*, n
(%
) 6
0 (
88%
) 3
73
(9
7%
)e 1
26
(8
9%
) 3
07
(9
8%
)e 7
(6
4%
) 1
72
(9
2%
) 2
54
(9
9%
)
UIE
(m
ean
(SD
), µ
g/24
-ho
ur)
1
02 (
59)
10
9 (
53
) 9
8 (
51
) 1
12
(5
5)a
70
(3
7)
10
3 (
54
)b 1
13
(5
3)c
<E
AR
*, n
(%
) 2
3 (
34%
) 9
1 (
24
%)
41
(2
9%
) 7
3 (
23
%)
6 (
56
%)
52
(2
8%
) 5
6 (
22
%)
≥
EAR
*, n
(%
) 4
5 (
66%
) 2
95
(7
6%
) 1
00
(7
1%
) 2
40
(7
7%
) 5
(4
4%
) 1
35
(7
2%
) 2
00
(8
8%
) 1 L
inea
r re
gres
sio
n w
ith
ad
just
men
t fo
r ag
e, g
en
der
, en
ergy
inta
ke a
nd
sch
oo
l clu
ster
a C
on
sum
ers
vs. n
on
-co
nsu
me
rs P
<0.0
5
2 B
on
ferr
on
i ad
just
me
nt
for
mu
ltip
le c
om
par
iso
ns
use
d t
o e
xam
ine
dif
fere
nce
s b
etw
een
su
bgr
ou
ps.
Su
b-g
rou
p d
iffe
ren
ces
ind
icat
ed b
y:
b
Eith
er v
s. n
eith
er P
<0.0
5
c B
oth
vs.
ne
ith
er P
<0.0
5
d B
oth
vs.
eit
her
P<0
.05
e χ
2 P<0
.05
fo
r d
iffe
ren
ce b
etw
een
co
nsu
mer
su
bgr
ou
ps
* EA
R f
or
4–8
yea
r o
lds:
65
μg/
day
, 9–1
3 y
ear
old
s: 7
5 μ
g/d
ay (2
)
~ 116 ~
Study 3: Food sources of iodine and association with urinary iodine excretion
Study 3: Food sources of iodine and association with urinary iodine excretion
~ 117 ~
6.4.5 Differences in dietary iodine intake and UIE between
consumers and non-consumers of bread and milk.
Eighty-five percent of participants reported consuming a known iodine
fortified bread product on the day of the recall (Table 6.3). Consumers of these
products had 22% higher dietary iodine intake compared to non-consumers
(P<0.001 Table 6.3), however there was no difference in UIE. In contrast,
consumers of milk (n=313, 69% of participants) had 55% higher dietary iodine
intake which was reflected by a 12% greater UIE, compared to non-consumers
(P<0.001 Table 6.3). Consumers of bread and milk were significantly more likely to
have dietary iodine intakes exceeding the age and gender specific EAR compared
to non-consumers (P<0.001 Table 6.3). There was, however, no difference in the
proportion of participants with a UIE excceding the age and gender specific EAR
between consumers and non-consumers of either bread or milk.
Participants who consumed either bread or milk on the day of the survey
had 32% higher UIE and 30% higher total dietary iodine intake than participants
who consumed neither (both P<0.001, Table 6.3). Participants who reported
consuming both bread and milk on the day of the recall had 38% higher UIE and
48% higher total dietary iodine intake than participants who consumed neither
bread nor milk on the day of the recall (both P<0.001 Table 6.3). Although total
dietary iodine intake was 26% higher in participants who consumed both bread and
milk compared to those who only consumed either bread or milk (P<0.001 Table
6.3), there was no difference in UIE.
Study 3: Food sources of iodine and association with urinary iodine excretion
~ 118 ~
6.5 Discussion
In a sample of Victorian schoolchildren following the mandatory
fortification of bread with iodised salt, the mean daily intakes of iodine estimated
from both 24-hour dietary recalls and 24-hour urine samples for 4-8 and 9-13 year
olds were in excess of the age-specific EARs of 65µg/day and 75µg/day, respectively
(2). In this population consuming adequate dietary iodine, the major contributors to
dietary iodine intakes, determined using 24-hour food recalls, were bread and
bread products (31%) and milk (25%). These results are similar to the findings of
the 2011-13 AHS, whereby bread and milk were the major sources of iodine (25%
and 26%, respectively) (45). Although milk intake was significantly associated with
UIE, the present study did not determine an association between total bread
intake, a major source of dietary iodine due to the mandatory use of iodised salt in
bread, and UIE.
Whilst mandatory fortification of bread with iodised salt appears to have
been successful in improving iodine intakes, with bread being a significant
contributor to iodine intakes in this study as well as the 2011-13 AHS (46, 163), the
present study found no association between bread consumption and UIE. In
addition, the present study was unable to confirm the findings of a previous
analysis of the 2011-13 AHS which found that consumption of >100g of bread/day
was associated with twelve times greater odds of achieving an adequate dietary
iodine intake in 2-18 year olds (46). This study, conducted by Charlton et. al. (2016),
utilised data from two 24-hour recalls, which may have reduced the variability in
bread intake (46). Within the present study we determined that 37% of participants
consumed >100 g of bread per day using a single 24-hour food recall, however
there was no association between consumption of greater than 100 g and UIE. The
use of only one 24-hour recall in the present study compared to two in the AHS
analysis may explain the differences in the findings as two 24-hour recalls are more
likely to capture usual intake (5, 157). Although the present study was unable to
determine an association between UIE and bread intake, this study does provide
evidence that bread and bread products contribute a significant proportion of
dietary iodine amongst schoolchildren in Australia.
Study 3: Food sources of iodine and association with urinary iodine excretion
~ 119 ~
Although it has been hypothesised that a reduction in the use of iodophores
by the dairy industry was the reason for the re-emergence of iodine deficiency in
Australia in the late 1990’s (52), the present study found that milk contributed 25%
of total iodine intake and was significantly associated with UIE, even after
adjustment for age, gender and energy intake. The proportion of dietary iodine
from milk products observed in Australian schoolchildren is comparable to that
observed in New Zealand (162), the United Kingdom (169), Germany (160) and the
United States (161), and indicates that milk is still a valuable source of iodine amongst
Australian schoolchildren. Similar to the present study, the studies in the U.K.,
Germany and the U.S. found that higher milk intakes were associated with an
increase in iodine excretion (160, 161, 169).
The iodine content of milk is dependent mainly on contamination from
iodophores (165), however there is some naturally occurring iodine present (166). This
naturally occurring iodine is, however, highly variable and is largely dependent on
the iodine intake of the cow itself (165-167). Factors such as the supplementation of
cow feed and salt licks, the cow species and farm location can impact the level of
naturally occurring iodine in milk (165, 166, 168). Currently within Australia iodophores
are still permitted for use in the dairy industry, however their use is not monitored,
and the proportion of farmers currently using them is not known, nor is the
concentration at which they are used (Kathryn Davis, Dairy Australia, Personal
Communication, January 2017). As such, it is difficult to determine the level of
contamination of milk by iodophores, and this in combination with the variation in
the naturally occurring iodine content of milk, means that the iodine content of
Australian milk could vary considerably both within and between producers.
However, the association between dietary iodine and UIE observed in the present
study provides evidence that milk remains a major contributor to daily iodine
excretion, and accordingly dietary intake among Australian schoolchildren. It is also
important to note that although there was a significant relationship between both
milk and combined bread and milk intake and UIE, consumption of these foods only
explained 2% and 3% of the variance in UIE, respectively. This indicates that there
may be a number of other factors influencing UIE aside from diet alone.
Study 3: Food sources of iodine and association with urinary iodine excretion
~ 120 ~
The major strength of the present study is the use of both 24-hour recalls
and 24-hour urine samples for the assessment of daily iodine intake. A stringent
24-hour urine collection protocol, specifically tailored to children was used to
ensure the completeness of the samples. However, as the present study was
limited to a single 24-h urine collection, adjustments for within and between
person variations in 24-hour urinary iodine excretion(18, 27, 297) could not be made,
in order to obtain a measure of long-term ‘usual’ iodine intake. In addition, the
present study only collected a single 24-hour recall further impacting our ability to
determine ‘usual’ intake. Whilst a single 24-hour recall is able to provide an
indication of the mean intake of a group, the use of only one 24-hour recall may
have impacted our ability to measure consumption of foods which are consumed
less frquently, such as fish (298). Fish and fish products contributed less than 1% of
total dietary iodine, compared to 3% in the Australian Health Survey (45). This study
does, provide a snapshot of current dietary patterns and provides evidence that
bread and milk are major food sources of iodine in this group of school children.
There are some limitations to this study, namely that the 24-hour recalls
over the same time period and 24-hour urine collection were not collected
concurrently. As such, some children completed the urine samples over a week
after the original 24-hour recall (i.e. n=29, 7% collected within a 2-week period)
(272). The variation in the number of days between the urine collection may have
contributed to the inability to detect an association between bread intake and UIE.
Furthermore, the observation that there was a significant difference in bread, but
not milk intake, between school days and non-school days indicates that bread
intake may be more variable than milk intake. This should be interpreted with
caution, however, due to the small number of participants (19%) who completed
the recall on a non-school day.
In addition, there are some inaccuracies inherent with the dietary
assessment methodologies used to assess the iodine content of food (299). A recent
review by Ershow et. Al. (2018) describes the wide variation in the iodine content
of food, and highlights the importance of maintaining accurate food databases for
determining the iodine intake of populations (299). This review also highlights the
Study 3: Food sources of iodine and association with urinary iodine excretion
~ 121 ~
difficulties associated with developing such a database due to the wide variations
in iodine content of food both within and between food types (299). Errors in the
database used to determine the food sources of iodine in the present study may
have limited our ability to capture associations between foods consumed (such as
bread) and UIE.
In Australia, the main source of iodine in bread is the iodised salt added
during production and the current level of iodine in salt added to bread in Australia
varies more than two fold: between 25-65 mg iodine per kilogram of salt (56).
Furthermore, the sodium content of bread ranges between 200-800 mg/100g (55)
and the iodine content of iodised salt may differ from the reported iodine content
due to losses related to storage and humidity (299). AUSNUT 2011-13, the food
database used in the present study, utilises the mean sodium and iodine content
of each of the bread products and does not account for the variation in either
sodium or iodine contents of breads , which may result in the inaccurate estimation
of the iodine content of foods, particularly bread and bread products which contain
iodised salt. Finally, the convenience sampling method used to recruit the
participants for this study may have resulted in the over-representation of
participants from higher socioeconomic areas (293).
6.6 Conclusion
This is the first Australian study to assess the contribution of food sources
of iodine to 24-hour urinary iodine excretion, as an objective measure of daily
iodine intake. In this sample of Victorian school-aged children, the major food
sources of dietary iodine were bread and milk. These results are comparable to the
results from the 2011-13 Australian Health Survey. The present study also found
that milk, but not bread intake, was associated with 24-hour urinary iodine
excretion. Future longitudinal research whereby 24-hour recalls and 24-hour urine
samples are collected concurrently, preferably on more than one day, is needed to
confirm these findings and to further elucidate the association between food
sources of iodine and urinary iodine excretion. Such studies are important for
evaluating the success of iodine fortification programs, as well as the potential
Study 3: Food sources of iodine and association with urinary iodine excretion
~ 122 ~
impact which the reformulation of major food sources of iodine, particularly
sodium reduction strategies, might have on the iodine intakes of Australian
schoolchildren.
~ 123 ~
Chapter Seven:
Study 4: Association between urinary excretion
of sodium and iodine in 24-hour urine samples
and association with discretionary salt use
7.1 Introduction
Due to the adverse health effects known to be associated with high salt
intakes (57, 180, 181, 189), the World Health Organization (WHO) recommends a
reduction in salt intake to <5g (2 g sodium) /day among adults by 2025 worldwide
with further reduction to <2g (0.8g sodium) /day recommended for children (190).
In Australia specifically, the establishment of salt reduction targets for nine food
categories, including bread, by the Federal Government’s Food and Health
Dialogue (FHD) in 2009 (194) resulted in a 10% reduction in the sodium content of
commercially available breads over 4 years (59). In addition the number of bread
products with a sodium content below the maximum recommended level of 400mg
sodium/100g tripled from 28% in 2009 to 86% in 2015 (59). During this same period
(2009-2015) Food Standards Australia New Zealand (FSANZ) reported an increase
in the iodine content of bread products from <2 µg/100g in 2006 to 60 µg/100g in
2015, as a result of mandatory fortification (196). However, it should be noted that
FSANZ also reported a subsequent reduction in the iodine contents of white and
wholemeal bread products by 11% and 25%, respectively, between 2010 and 2013
(196).
This reduction in the iodine content of bread products could be a result of
the successful implementation of sodium reduction targets. This raises the concern
that a further reduction in the sodium content of bread products could result in a
subsequent reduction in the iodine content of bread. As the 2011-13 Australian
Health Survey reported that bread and bread products contributed approximately
25% of total dietary iodine intake amongst 5-11 year olds (46), due to the iodised
salt added during processing, a reduction in the iodine content of bread as result
Study 4: Association between urinary excretion of sodium and iodine in 24-hour urine
samples and association with discretionary salt use
~ 124 ~
of sodium reduction strategies could have a subsequent negative impact on the
iodine intakes of Australians.
Therefore, it is important to establish the association between intakes of
iodine and sodium, in order to understand the role which iodised salt, added either
during processing or as discretionary salt (added during cooking and/or at the
table), plays in the iodine intakes of Australians. Studies in Germany (160) and Korea
(177) have observed modest correlations between urinary excretion of iodine and
sodium, however to date there have been no studies utilising 24-hour urine
samples, the most objective measure of both sodium and iodine intakes (64, 94), to
assess the relationship between iodine and sodium intake in a sample of Australian
schoolchildren.
7.2 Aims
i) To examine the relationship between excretion of iodine and sodium in a sample
of Victorian school-aged children, using 24-hour urine samples
ii) To assess differences in iodine intakes, determined using urinary iodine
excretion, across reported categories of discretionary salt use.
7.3 Methods
The study design for this study has been described in Chapter Four
7.3.1 Participants and recruitment
See section 4.1 Participant recruitment for details. In these analyses which
involved urinary sodium excretion, one extreme outlier for sodium excretion
(mean(SD) 531(9) mmol/24-hour) was excluded, leaving a final sample size of 649
participants with a valid 24-hour urine sample analysed for both sodium and iodine.
7.3.2 Measures
See section 4.2 Testing procedures for details
Study 4: Association between urinary excretion of sodium and iodine in 24-hour urine
samples and association with discretionary salt use
~ 125 ~
7.3.3 Discretionary salt use characteristics
This has been described in section 4.2.2 Discretionary salt use
characteristics. For the purpose of this analysis the responses for the questions
relating to discretionary salt use were dichotomised into “Yes”, encompassing “Yes,
usually” and “Yes, sometimes”, and “No”. Missing (n=7) and “Don’t know” (n=4)
responses were excluded from analysis, leaving a total of 638 participants with
both valid urine and completed discretionary salt use data. No information on
whether the discretionary salt used was iodised was collected. A discretionary salt
user was defined based on parent reported addition of salt during cooking and child
reported salt use at the table. Participants were classified as consuming “neither’
(i.e. salt was not added during cooking or at the table), “either” (reported adding
salt either during cooking or at the table), or “both” (reported adding salt during
cooking and at the table).
7.3.4 24-hour urine collection
See section 4.3 24-hour urine collection for details.
7.3.5 Urinalysis
See section 4.3.3 Biochemical analysis for details.
7.3.6 Statistical analysis
All analyses were completed with STATA/SE 14.0 software (StataCorp LP),
and a P value <0·05 was considered statistically significant. Normality of continuous
variables was assessed and confirmed using box plots, histograms and the Shapiro-
Wilk test and have been presented as mean (SEM). The underlying assumptions of
linear regression (i.e. homoscedasticity, normality) were confirmed using
regression plots of residuals. Pearson’s correlation and multiple regression
(adjusted for age, gender and school cluster) were used to assess the relationship
between urinary iodine excretion (UIE) and urinary sodium (UrNa).
Paired t-tests were used to assess differences in UIE between those who
did and did not report engaging in each of the three dichotomous discretionary salt
Study 4: Association between urinary excretion of sodium and iodine in 24-hour urine
samples and association with discretionary salt use
~ 126 ~
use behaviours. Linear regression, adjusted for age, gender and school cluster, was
used to further assess differences in UIE across the different levels of discretionary
salt use, whereby discretionary salt use category was entered as the indicator
variable with “neither” used as the reference group. As this model included
multiple comparisons between sub-groups, the Bonferroni correction for P-values
was also reported. Both the adjusted and unadjusted models have been presented.
As previous analyses have determined that sodium excretion was significantly
higher on non-school days, compared to school days (295), all regression analyses
have also been adjusted for urine day type. The unstandardised beta co-efficient
(β) and standard error (SE) have been presented for all regression models.
7.4 Results
7.4.1 Demographic characteristics
Overall 55% of children were male, the average age was 9 years and 4
months and 62% were of from a high socioeconomic area (Table 7.1). In total, 17%
of children were either overweight or obese and 53% completed the 24-hour urine
collection on a non-school day.
Study 4: Association between urinary excretion of sodium and iodine in 24-hour urine
samples and association with discretionary salt use
~ 127 ~
Table 7.1: Demographic characteristics of SONIC participants included in sodium analysis (n=649)1
All Boys Girls
Number of participants, n(%) 649 358 (55%) 291 (45%) Age (mean (SD), years) 9.3 (1.8) 9.3 (1.9) 9.2 (1.7) Age group
4-8 years, n(%) 280 (43%) 157 (44%) 123 (42%) 9-12 years, n(%) 368 (57%) 201 (56%) 167 (58%)
SES2 Low tertile, n(%) 105 (16%) 45 (12%)a 60 (21%)a
Mid tertile, n(%) 144 (22%) 77 (22%) 67 (23%) Top tertile, n(%) 399 (62%) 236 (66%)a 163 (56%)a
BMI category Underweight, n(%) 67 (10%) 34 (10%) 33 (11%) Healthy, n(%) 471 (73%) 270 (75%) 201 (69%) Overweight, n(%) 91 (14%) 45 (13%) 46 (16%) Obese, n(%) 19 (3%) 9 (2%) 10 (4%)
Day of urine collection School day, n(%) 303 (47%) 168 (47%) 135 (47%) Non-school day, n(%) 345 (53%) 190 (53%) 155 (53%)
Urvol (mean (SD), ml/24-hour) 870 (16.4) 892 (23.5) 844 (22.5) UrCr (mean (SD), mmol/24-hour) 5.5 (0.1) 5.8 (0.1)b 5.3 (0.1)b
UIE (mean (SD), µg/24-hour) 104 (2.1) 112 (3.0)b 93 (2.8)b
UrNa (mean (SD), mmol/24-hour) 104 (1.8) 109 (2.5)b 97 (2.5)b
>Na UL2, n(%) 468 (72%) 196 (67%)a 272 (76%)a Salt equivalent (mean (SD), g/24-hour) 6.1 (0.1) 6.4 (1.5)b 5.7 (0.1)b
SONIC: Salt and Other Nutrient Intakes in Children study (Victoria); SES: socioeconomic status; BMI: body mass index; UrVol: Urine volume; UrCr: Urinary creatinine; UIE: urinary iodine excretion; UrNa: Urinary sodium; UL: Upper Level of intake 1 One extreme outlier for sodium excretion (mean(SD) 531(9) mmol/24-hour) excluded; 2 SES based on state-based socioeconomic indexes for areas, index of relative socioeconomic disadvantage 2 Upper Level of intake for children aged 4-8 years: 60 mmol Na/24-hour and 9-13 years: 86 mmol Na/24-hour a 2 Test P<0.05 for differences between genders; b Multiple regression adjusted for age, urine day type and school cluster P<0.05 for difference between genders
7.4.2 Relationship between urinary sodium and urinary iodine
excretion
The mean (SEM) UIE and UrNa for all participants were 104 (2.1) μg/24-
hour and 104 (1.8) mmol/24-hour, respectively (Table 7.1). Seventy-two percent of
participants exceeded the upper level of intake for sodium (Table 7.1). Children
who exceeded the UL for sodium had a 28% higher UIE compared to those whose
urinary sodium was equal to or below the recommendation (mean (SD) 81 (38) vs.
112 (56) mmol/24-hour, P<0.001). There was a moderate, positive correlation
between UIE and UrNa (r=0.37, P<0.001; Figure 7.1). Regression analysis revealed
Study 4: Association between urinary excretion of sodium and iodine in 24-hour urine
samples and association with discretionary salt use
~ 128 ~
that one milligram/24-hour (0.003mg salt) of UrNa was associated with a 7.1
g/24-hour higher UIE and accounted for 14% of the variance in UIE (R2=0.14,
β(SE)=7.12(0.80), P<0.001). When adjusted for age, gender and day type of urine
collection, this association remained significant (R2=0.19, β(SE)=5.87(0.90),
P<0.001).
7.4.3 Differences in urinary iodine excretion across discretionary
salt use categories
Sixty-five percent of participant’s parents reported using salt during cooking
and 29% reported that their child added salt at the table (Table 7.2). Conversely,
significantly more children, 40%, reported that they added salt at the table (Table
7.2, P<0.001). Seventy-seven percent (n=493) of participants were classified as a
discretionary salt user, with 28% (n=177) of participants adding salt both at the
table and during cooking (Table 7.2).
Figure 7.1: Relationship between urinary excretion of iodine and sodium in the SONIC
paticipants included in sodium analyses (n=649)
Study 4: Association between urinary excretion of sodium and iodine in 24-hour urine
samples and association with discretionary salt use
~ 129 ~
Urinary sodium excretion was significantly higher in participants whose
parents reported not using salt during cooking (110.3 (46) vs. 101.6(49) mmol/24-
hour, P<0.05). There was, however, no significant difference in UIE across any of
the discretionary salt use categories (Table 7.2 & 7.3).
Table 7.2: Urinary excretion of iodine and sodium across discretionary salt use categories (n=638), mean (SEM) or n (%)
n (%)
UIE (µg/24-hour)
UrNa (mmol/24-hour)
salt added at the table (child defined) yes (yes, usually/yes, sometimes) 253 (40%) 104 (4.8) 107.2 (3.2) no 385 (60%) 103 (4.7) 102.2 (2.4)
salt added at the table (parent defined) yes (yes, usually/yes, sometimes) 184 (29%) 105 (4.4) 106.5 (3.9) no 454 (71%) 103 (4.4) 103.2 (2.3)
salt added during cooking (parent defined) yes (yes, usually/yes, sometimes) 417 (65%) 102 (4.1) 100.7 (2.3) no 221 (35%) 107 (5.5) 110.7 (3.4)a
discretionary salt user 1 salt not used either at the table or during cooking
145 (23%) 108 (6.1)b 110.9 (4.1)b
salt used either at the table or during cooking
316 (50%) 101 (4.4) 100.2 (2.5)
salt used both at the table and during cooking
177 (27%) 104 (5.1) 105.7 (3.2)
UIE: urinary iodine excretion; UrNa: urinary sodium excretion a Paired T-test used to examine difference between ‘yes’ and ‘no’, P<0.05; b Linear regression with adjustment for age, gender, urine day type and school cluster used to assess differences between subgroups, with Bonferroni correction for multiple comparisons P>0.05
1 Defined using parent reported use of salt during cooking and child reported use of salt at the table
Table 7.3: Relationship between urinary iodine excretion (μg/24-hour) and discretionary salt use (n=638)1
β (SE) P-value Adjusted P-Value2
Model 1 used neither (reference)
used either -7.0 (5.4) 0.2 0.4 used both -4.6 (5.7) 0.4 0.9
Model 2 used neither (reference)
used either -4.8 (5.4) 0.4 0.8
used both -4.6 (5.9) 0.4 0.9
Model 1: Unadjusted; Model 2: Adjusted for age, gender, and urine day type 1 Multiple linear regression used to assess differences in urinary electrolyte excretion by discretionary salt use, as defined using parent reported salt use during cooking and child reported salt use at the table;2 P-value adjusted for multiple comparisons between sub-groups using Bonferroni correction.
Study 4: Association between urinary excretion of sodium and iodine in 24-hour urine
samples and association with discretionary salt use
~ 130 ~
7.5 Discussion
In this sample of Victorian school-aged children post fortification of bread
with iodised salt there was a moderate, positive association between UIE and UrNa
but no association between UIE and reported discretionary salt use. The positive
association between urinary excretion of iodine and sodium is consistent with that
previously reported using 24-hour urine collections in a sample of mildly iodine
deficient German children aged 3-6 years (r=0.43, P<0.05) (160). In both Germany
and Australia, iodised salt added to foods during processing is a significant
contributor to iodine intake (45, 300), and this might explain the relationship between
UIE and UrNa observed in these studies. Conversely, however, a study conducted
in a sample of mildly iodine deficient Australian women prior to the introduction of
mandatory fortification of bread with iodised salt, was unable to detect an
association between UIE and UrNa (178). This may have been due to the fact that
bread, a food which is a major contributor to daily sodium intake, was at the time
not a source of iodine. Similarly, a study conducted in South African adults was also
unable to establish a relationship between the two nutrients as assessed by 24-
hour urinary excretion (179). Although universal salt iodisation (USI) has been
implemented in South Africa since 1995, salt added to food during processing is
exempt from mandatory iodisation (301). Therefore despite bread and bread
products being major contributors to sodium intake they may not be a source of
iodine in South Africa. The findings from these studies indicate that iodine and
sodium intake are more likely to track together in populations where foods that are
major sources of sodium are produced using iodised salt.
It has been estimated that discretionary salt use contributes 10-15% of total
dietary sodium and it has been found that adults who report adding salt at the
table and in cooking have higher total salt intakes compared to those not using
discretionary salt (174). Sixty-five percent of participants in the present study
reported that salt was added during cooking (parent reported) and 40% added it to
their food at the table (child reported). These results are slightly higher than that
observed in the 2011-13 AHS, whereby 50% of 4-8 year olds and 57% of 9-13 year
Study 4: Association between urinary excretion of sodium and iodine in 24-hour urine
samples and association with discretionary salt use
~ 131 ~
olds reported using salt in cooking rarely/occasionally/very often with 17% of 4-8
year olds and 36% of 9-13 year olds adding salt at the table (45).
Whilst reported discretionary salt use was high in the present study,
children whose parents reported adding salt during cooking had 10% lower urinary
sodium excretion compared to those children whose parents reported not adding
salt during cooking. In addition, the present study found that both UIE and UrNa
were significantly higher in participants who did not report adding salt at the table
or during cooking, compared to those participants who engaged in one or both of
these behaviours. It is possible that that those who added salt in cooking might be
doing more cooking at home and, although they added salt in cooking, the amount
added would be less than that found in pre-prepared/take-away meals. The
discrepancy could also be related to the use of one 24-hour urine collection for
assessment of daily sodium excretion compared with questions relating to general
use of discretionary salt. Furthermore, assessment of discretionary salt use can be
challenging due to recall and self-reporting biases (175).
Although discretionary salt use among Australian schoolchildren is still
relatively high, the present study did not find an an association between reported
discretionary salt use behaviours and UIE. This finding is similar to that observed in
a 2016 multi-center study of 8-10 year old iodine sufficient children (n=132) in the
United Kingdom (169). Compared to the study in the U.K. however, the present study
did not ask participants whether the salt used during cooking or at the table was
iodised. Furthermore, neither the present study nor the study in the U.K. included
a direct measure of iodised salt intake, and this may be the reason for the lack of
association between iodine excretion and discretionary salt use in both studies.
Further studies whereby discretionary use of iodised salt is directly measured
alongside a 24-hour urine sample are needed to further elucidate whether
discretionary use of iodised salt contributes to the daily iodine intake of Australian
schoolchildren
The main strength of the present study is the use of 24-hour urine samples
to estimate iodine and sodium intakes, as this is the most robust way to accurately
capture total daily intakes of both nutrients (20, 58). A stringent 24-hour urine
Study 4: Association between urinary excretion of sodium and iodine in 24-hour urine
samples and association with discretionary salt use
~ 132 ~
collection protocol, specifically tailored to children was used to ensure the
completeness of the samples. Limitations of this study include the convenience
sampling method, which resulted in some over-representation of participants from
higher socioeconomic areas (293). In addition, the study did not include a direct
measure of discretionary salt use, nor did it collect information regarding the use
of iodised salt specifically, which may have limited the ability to determine a
relationship between UIE and discretionary salt use. Finally, as the present study
was limited to a single 24-hour urine collection, adjustment for the within person
variation in 24-hour urinary iodine and sodium excretion could not be made in
order to obtain a measure of long-term ‘usual’ iodine intake.
7.6 Conclusion
In summary, this study found that in a sample of iodine sufficient Victorian
schoolchildren there was a moderate, positive association between urinary sodium
and urinary iodine excretion, but no association between urinary iodine and
reported discretionary salt use. Therefore, it is important to implement an ongoing
program to monitor population sodium and iodine intakes, in order to ensure that
a reduction in sodium intakes to decrease dietary related disease risk does not put
Australian schoolchildren at risk of iodine deficiency.
~ 133 ~
Chapter Eight: Discussion
8.1 Victorian children have sufficient iodine intakes – a
result of the successful implementation of mandatory
fortification?
Collectively the findings from this thesis build on the results of the 2011-13
Australian Health Survey (AHS), and confirm that Victorian school-aged children are
now iodine sufficient. The average iodine intakes in this sample of Victorian school-
aged children, assessed by 24-hour urine samples, were 94 and 111 µg/24-hours
for 4-8 and 9-13 year olds, respectively, exceeded the age-specific Estimated
Average Requirement (EAR) (2). Less than 30% of children having intakes below the
age-specific EAR. Furthermore, the median 24-hour urinary iodine concentration
(UIC) of 124µg/L observed in exceeded 100µg/L as recommended by the World
Health Organization (WHO) (38), indicating iodine sufficiency in the population.
The UIC determined using 24-hour urine samples was 41% higher than the
spot UIC observed in Victoria in the 2003-2004 National Iodine Nutrition (NINS)
study conducted prior to the introduction of mandatory fortification of bread with
iodised salt (34). This difference in UIC can be interpreted to indicate that
mandatory fortification of commercially produced bread, excluding organic and
homemade varieties, with iodised salt in 2009 has been effective in improving the
iodine status of Victorian school-aged children. Furthermore, it was found that
nearly 80% of participants consumed an iodine fortified bread product on the day
of the survey. This finding is important as it indicates that a large proportion of the
school-aged children in this sample were exposed to iodine fortification and that
iodine fortification is reaching the target audience identified when the strategy was
first proposed in 2004 (154). However, although it was observed that the main food
source of iodine was ‘regular breads and bread rolls’, contributing 27% of total
dietary iodine intake in these children, there was no association between the
amount of bread consumed and the amount of iodine excreted over 24-hours.
Discussion
~ 134 ~
Although we were unable to determine an association between bread
consumption and UIE, the finding that bread was the main food source of dietary
iodine in this sample of Victorian school-aged children is of significant importance
when considering the implementation of sodium reduction targets to processed
foods. As previously discussed, the application of sodium reduction targets to
bread as part of the Food and Health Dialogue (FHD), saw a 10% reduction in the
sodium content of bread between 2009-2015 (196). Whilst the successful
implementation of these targets is important for the reduction of excessive sodium
intakes, further reductions in the sodium content of bread may negatively impact
the iodine intakes of Australian school-aged children (44). A recent report by Food
Standards Australia New Zealand (FSANZ) observed that whilst the iodine content
of bread is considerably higher than compared to the period prior to fortification,
there has been a subsequent decline in bread iodine content since 2009 (196). This
decline is likely due to the application of sodium reduction targets to processed
foods, and a subsequent reduction in the amount of iodised salt added by bread
manufacturers. Furthermore, a 2016 report by FSANZ which evaluated the iodine
content of 95 commercially available breads in 2013, observed that the iodine
content ranged from 20-110 µg/100g (196). This range is very broad, and indicates
significant variation in the iodine content of breads currently available on the
Australian market. These variations are likely due to differences in both the amount
of salt added during bread production (range: 200-800mg/100g ) as well as the
level of salt iodisation specifically. Current salt iodisation legislation in Australia
state that iodised salt for use during bread manufacture should be iodised at a level
between 25-65 mg/kg of salt (56). It is therefore important to note that the exact
amount of iodine added to bread can vary substantially both within and between
bread varieties. Furthermore, in Australia there is currently no legislation ensuring
adequate monitoring of the amount of iodine in commercially produced bread and
bread products.
The wide variation in the iodine content of commercially available bread
and bread products makes it difficult to accurately estimate any potential impact
of sodium reduction targets on the iodine content of bread and the subsequent
impact on the iodine intakes of Australian school-aged children. Therefore, it is
Discussion
~ 135 ~
important that the iodine intakes of Australian school-aged children continue to be
monitored, using 24-hour urine samples, in order to monitor the potential impact
which the application of sodium reduction targets to bread might have and prevent
the re-emergence of iodine deficiency. Whilst mandatory fortification of bread with
iodised salt appears to have been effective in improving the iodine nutrition of
Victorian school-aged children it is perhaps not ideal to tag an essential nutrient,
being iodine, to sodium, a substance which is known to have long-term adverse
health effects when consumed in excess. Therefore, strategies to improve iodine
intakes through foods which are less reliant on iodised salt for their iodine content
need to be considered by government bodies and health experts.
One such strategy could be the promotion of milk and milk products as a
source of iodine, as it was observed that in this sample of Victorian school-aged
children ‘milk products and dishes’, including dairy milk, cheese and yoghurt,
contributed the same amount to total dietary iodine as ‘cereal products and
dishes’, 35%. Furthermore, whilst consumption of ‘cereal products and dishes’ was
not associated with daily iodine excretion, the consumption of ‘milk products and
dishes’ was significantly associated with an increase in excretion of iodine over 24-
hours. Similar findings have been observed in American (161), British (169), Portuguese
(302) and German (160) school-aged children. In all of these countries the major food
source of iodine was milk and an increase in milk and/or dairy consumption was
associated with a significant increase in urinary iodine levels. It should be noted,
however that only the German study assessed the relationship between observed
24-hour UIE and dairy consumption (160), with the remaining three studies utilising
spot urine samples to assess the association between dairy consumption and UIC
(161, 169, 302). Differences in methodologies aside, the results from these studies
indicate that consumption of dairy products can have a significant impact on the
iodine nutrition of school-aged children.
Although dairy products contributed a large proportion of total dietary
iodine in the present study, the recent Australian Health Survey determined that
children aged 4-13 years were not meeting the recommended daily serves of dairy.
Children aged 4-8, 9-11 and 12-13 years were consuming, on average, 1.6, 1.6 and
1.8 serves of dairy per day, respectively, considerably less than the 2, 2.5 and 3.5
Discussion
~ 136 ~
serves recommended for each (303). As the iodine content of milk is not dependent
on iodised salt, increasing population consumption of milk and/or dairy products
could present a viable alternative for maintaining the iodine intakes of the
population whilst also reducing population sodium intakes through a reduction in
the sodium content of processed foods, including bread. The consumption of an
additional 1 serve of full fat dairy milk per day would increase daily iodine intake by
approximately 57µg, equivalent to two slices of regular fortified white bread(54). If
dairy consumption was increased to meet recommendations, children would be
more likely to meet their daily iodine intake requirements, without the reliance on
foods fortified with iodised salt.
The present study is the first Australian study to evaluate the iodine intakes
of a sample of Australian schoolchildren using 24-hour urine samples. In addition,
the collection of 24-hour food recalls alongside these urine samples provides
valuable insight into the current state of iodine nutrition in Australia. It should be
acknowledged that the SONIC study was carried out between 2010-2013, relatively
soon after the introduction of mandatory fortification in 2009. Since the
introduction of mandatory fortification in 2009, the number of commercially
available iodine fortified products has increased substantially, particularly amongst
commercially produced bread and bread products (196). As such, the current
analysis may not be representative of iodine nutrition in Australia in 2018. It should
also be acknowledged that due to the convenience nature of participant
recruitment and the low response rate, the findings from the studies in this thesis
can not be extrapolated to the wider population. It is possible that participants
were from families that were more health conscious than non-respondents.
Despite efforts to reach all socioeconomic backgrounds, close to two-thirds of
children were from a high socioeconomic background. In addition, compared with
national estimates, our sample had fewer children who were overweight or obese,
which may reflect different dietary patterns among our study participants.
Discussion
~ 137 ~
8.2 Current methods for assessing the iodine nutrition of
populations – is it time for a change?
Current recommendations for assessing the iodine nutrition of populations
are based on the measurement of UIC in spot urine samples, collected from school-
aged children (37). As discussed in Chapter Three these recommendations were
established over a number of years, however the initial cut-offs were based on a
study conducted in Spanish children and adults in the 1970s (117). Whilst this study
observed that goiter prevalence was <10% in areas where daily iodine intakes,
estimated using the iodine/creatinine ratio (I/Cr) measured in spot urine samples,
were greater than 100µg/day the results from this study were for the population
as a whole and there was no separation of the findings based on age (117).
Irrespective of this, the World Health Organization (WHO) subsequently used the
estimated intakes determined in this study to inform their recommendations for
assessing the severity of iodine deficiency within a population using spot urine
samples in school-aged children in 1986 (101). Additionally, although these
recommendations were initially based on estimated daily iodine intake determined
from spot urine samples through extrapolation based on creatinine excretion, later
iterations extrapolated these cutoffs to represent a concentration, reported as
µg/L (37).
There are a number of issues with the establishment of these
recommendations, as well as their current use in population monitoring. Firstly, as
discussed in Study 1, only in cases where the mean daily urine volume equals one
liter would spot UIC be indicative of daily iodine intake. As the average urine
volume of school-aged children determined in Study 1 was closer to 0.75L, the
application of the current cutoffs as a surrogate index of the iodine intakes of this
population of school-aged children might result in the misclassification of iodine
deficient children within the population as iodine sufficient. Furthermore, Study 4
determined that the average urine volume of 4-12 year olds in the SONIC study was
873 mL/day. As such, the iodine concentration determined from 24-hour samples
in this study cannot be used as a surrogate measure of iodine intake in this group
of children as it would overestimate true intakes. If a daily urine volume of 1L was
Discussion
~ 138 ~
assumed, and the iodine concentration measured in the 24-hour urine sample (133
µg/L) used as a surrogate indicator of the daily iodine intake of this group of
schoolchildren, it would overestimate the iodine intakes by 22% when compared
to the iodine intake calculated using the true urine volume of the 24-hour urine
samples (104 µg/24-hours). Although the daily iodine intake of this group of
children was still in excess of the iodine intake of 100 µg/day originally associated
with reduced goiter prevalence (101, 117), such extrapolations in populations with a
UIC closer to 100 might result in the misclassification of a population with
inadequate iodine intakes as being iodine sufficient. For example, a population of
children with a UIC of 100 µg/L and a urine volume of 873 mL, true intakes would
lie closer to 87 µg/day which is 13% lower than the 100 µg/day originally associated
with reduced goiter prevalence(101, 117). As a result, such a population would not be
identified as at risk of developing the adverse health outcomes associated with
iodine deficiency, preventing the implementation of strategies to improve iodine
intakes. It may be worthwhile for future studies to consider collecting 24-hour urine
samples in a subset of the population under investigation, as a means of
determining the average urine volume of that population. This would allow for
studies to account for the average urine volume in their interpretation of the
results and the overall assessment of the iodine status of the population.
Secondly, the current recommendations were based on estimates from a
population of adults and children “of all ages” from Central America in the 1970s
(117). However, this study did not examine whether the association between
estimated daily iodine intakes and goiter prevalence was different in adults
compared to children. As such, the WHO recommendations state that whilst
school-aged children are the preferable target group for iodine monitoring studies,
they “appl[y] to adults, but not to pregnant and lactating women” (38). This implies
that the iodine requirements for adults (excluding pregnant and lactating women)
are the same as those for children, which is incorrect. The Nutrient Reference
Values for Australia New Zealand (NRVs) provide separate EAR recommendations
for different age groups (Table 8.1), and indicate that adults (excluding pregnant
and lactating women) have a 40% higher iodine requirement compared to 4-8 year
olds and a 20% higher requirement compared to 9-13 year olds (2). This presents
Discussion
~ 139 ~
challenges when the same spot UIC cut-offs are used to determine the iodine status
of both adults and children. Although deficiency during adulthood may not impact
growth and cognition as it would in childhood, iodine deficiency during adulthood
could still have significant effects on thyroid function (100). Furthermore, iodine
deficiency among women of child-bearing age could lead to females entering
pregnancy with suboptimal iodine status. Iodine is an important nutrient during
pregnancy, and deficiency during this time has been linked with impaired growth
and cognition (66, 292). As such, it is important that monitoring of iodine nutrition is
not limited only to children and pregnant women and appropriate
recommendations are needed for assessing the iodine nutrition of adult
populations.
Table 8.1: Iodine Nutrient Reference Values for children and adults (2)
Age group (years) EAR (µg/day)
1-3 65 4-8 65
9-13 75 14-18 95 19+* 100
EAR: Estimated Average Requirement *does not apply to pregnant/lactating women
A recent review by Zimmerman and Andersson raised the concern that the
application of the current spot UIC recommendations to assess the iodine status of
a population of adults, could result in the misclassification of the intakes of
individuals within adult populations (15). It has been estimated that the daily urinary
output of adults is approximately 1.5L (269), based on a water balance study
conducted in a sample of 1528 German adults aged 18-88 years, almost 30 years
ago (269). More recently however, a study in a sample of New Zealand adults
observed a mean daily urine output of 2L (266). In this sample of adults, a daily iodine
intake of 100µg/day (equivalent to the EAR for adults aged 19 years and over)
would correspond to a UIC of 50µg/L. As such, the application of the 100µg/L cut-
off as the indicator of iodine deficiency in this population could result in the
misclassification of iodine sufficient adults as iodine deficient. Whilst this may not
be as detrimental to health as the misclassification of iodine deficient populations
Discussion
~ 140 ~
as iodine sufficient, it could still have an impact on ID prevalence estimates. This
could result in the implementation of ID control programs in countries where they
are not needed, and potentially expose individuals to excessive iodine intakes and
subsequent adverse health outcomes. Therefore, it might be appropriate for the
current recommendations for assessing the iodine status of populations using spot
urine sample to be revised to account for the higher iodine requirements of adults.
Furthermore, more research into the daily urine volume of adults is needed in
order to inform the development of these recommendations.
Finally, it is important to note that the current spot UIC cut-offs were based
primarily on goiter prevalence estimates in an area of long-term moderate iodine
deficiency (117). Using goiter prevalence as a functional indicator of iodine deficiency
within a population comes with its own limitations, as both inter and intra observer
errors in the measurement of thyroid size can have a significant impact on goiter
prevalence estimates. This was demonstrated by a multi-centre study of the iodine
nutrition of 6-15 year old children from across Europe in 1995, using a combination
of thyroid ultrasound and the measurement of UIC in spot urine samples (107).
Whilst this study observed that a spot UIC >100µg/L was associated with reduced
goiter prevalence, thus providing support for the 1993 WHO recommendation for
assessing the iodine nutrition of populations based on a population median UIC of
100µg/L, it was later determined that the goiter prevalence estimates in the
European study had been overestimated (107). Whilst it was first suggested that this
may have been a result of the long standing history of iodine deficiency in Europe,
resulting in a slower response by the thyroid gland to iodine prophylaxis (141), it was
eventually established that systematic errors in the thyroid ultrasound
methodology used were the reason for the observed discrepancies in goiter
prevalence estimates (108). Furthermore, studies conducted in South Africa (143) and
Côte d’Ivoire (69) have demonstrated that goiter prevalence can remain elevated in
populations for up to 4 years after spot UIC returns to normal levels. As such, the
measurement of thyroid size, and subsequently goiter prevalence, may not be the
most sensitive functional outcome to use as the indicator of iodine deficiency when
forming recommendations for assessing the iodine nutrition of populations.
Alternatives to thyroid size assessment have been investigated by a number of
Discussion
~ 141 ~
researchers (136, 304-307). The most promising of these biomarkers is serum
thyroglobulin (Tg), which studies have demonstrated to be a sensitive index of
iodine nutrition in both children (136, 307) and adults (308-310).
8.3 Current lack of population iodine monitoring in
Australia
The findings from this thesis add to the limited pool of research assessing
the current state of iodine nutrition in Australia. Prior to the 2011-2013 AHS the
most recent national survey of iodine nutrition encompassing both children and
adults was conducted in 1995 (311). This survey utilised 24-hour food recall data to
determine total dietary iodine intake, however did not include urinary assessment
of iodine status (311). Eight years later, the 2003-2004 NINS utilised spot urine
samples and thyroid ultrasound to assess the prevalence of iodine deficiency
among 1,709 8-10 year old children from across the five mainland states of
Australia, in order to confirm the findings of iodine deficiency among school-aged
children by a number of smaller studies in various regions across Australia (14, 41-43).
Following on from this in 2007 the Australian Children’s National Nutrition and
Physical Activity Survey (CNPAS) utilised 24-hour food recalls to estimate the iodine
intakes of a representative sample of 4,487 2-16 year old children from across
Australia (281). Although mandatory fortification of bread with iodised salt was
introduced in 2009 as a means of combatting the iodine deficiency observed in
Australia between 1999-2007, few studies have been conducted post fortification
to evaluate the effectiveness of the strategy and monitor the iodine nutrition of
the population (29, 47, 312-317). Furthermore, only three of these studies were
conducted in children (29, 47, 315), with the majority of studies focusing on pregnant
or lactating women (312-314, 316, 317).
Whilst the 2011-13 AHS utilised spot urine samples to assess the iodine
status of the population, to date there have been no studies utilising 24-hour urine
samples to assess the iodine intakes of a nationally representative sample of
Australian children and adults as a means of evaluating the effectiveness of
mandatory fortification. Such a program is unlikely as the collection of 24-hour
Discussion
~ 142 ~
urine samples from populations is considered difficult, when compared to the
collection of spot urine samples. Globally, monitoring of the iodine nutrition of
populations is largely carried out using spot urine samples to determine iodine
status (318, 319), including the American National Health and Nutrition Examination
Survey (NHANES) (85), China’s National Iodine Deficiency Disorders Survey (320, 321)
and the United Kingdom’s National Diet and Nutrition Survey (NDNS) (322).
Additionally, these large-scale national surveys also collect dietary data to
determine dietary intakes and food sources of iodine within populations (85, 320-322).
Whilst spot urine samples and dietary methods are adequate for assessing
population risk of iodine deficiency, the inherent inaccuracies associated with
these methods mean that they are not able to provide an accurate estimate of daily
iodine intake. In order to accurately assess the iodine intakes of individuals and
populations 24-hour urine samples are needed (111). Globally, there are currently
no ongoing national surveys utilising 24-hour urine samples to monitor the iodine
intakes of a population. The findings from the present thesis demonstrate that with
appropriate instructions and resources, collection of 24-hour urine samples is
feasible among school-aged children. The use of 24-hour urine samples for the
assessment of the iodine intakes of a large sample has been successfully
demonstrated by the ongoing Dortmund Nutritional and Anthropometric
Longitudinally Designed (DONALD) Study which has effectively collected 24-hour
urine samples from German children and adolescents aged 2-18 years old at yearly
intervals since its establishment in 1985 (202).
The history of iodine deficiency in Australia in combination with the
evidence linking both iodine deficiency and excess to adverse health outcomes in
both children and adults provides sufficient rationale for the implementation of an
ongoing iodine monitoring program in Australia. There is currently no ongoing
monitoring of the iodine nutrition of both children and adults in Australia.
Furthermore, the use of 24-hour urine samples is needed to determine the iodine
intakes of the population as opposed to simply relying on spot urine samples for
assessing iodine status. Such a program would help monitor the impact of various
public health strategies, such as mandatory iodine fortification of bread and the
application of sodium reduction targets to processed foods, on the iodine nutrition
Discussion
~ 143 ~
of the population. Furthermore, as the use of 24-hour urine samples is
recommended as the most appropriate method for monitoring the sodium intakes
of the population, it might be worthwhile for future studies assessing the sodium
intakes of Australian to consider assessing iodine intakes concurrently, as this will
assist in monitoring the impact of sodium reduction strategies on both sodium and
iodine intakes of the population.
8.4 Concluding remarks
The findings from this thesis provide a unique contribution to nutrition
science and add important information to the limited available data regarding the
iodine nutrition of Victorian school-aged children post fortification of bread with
iodised salt. Furthermore, the studies included in this thesis have highlighted a
number of challenges to overcome with regards to the current methods used for
assessing the iodine nutrition of populations. Therefore, validation of current
recommendations is needed using a more sensitive biomarker of iodine nutrition,
such as thyroglobulin, to ensure that the iodine nutrition of populations is being
accurately assessed. Based on the findings from this thesis, it would appear that
the iodine intakes of Victorian school-aged children have improved to sufficient
levels since the introduction of mandatory iodine fortification in 2009, with bread
and milk being the main contributors to total iodine intake. The main source of
iodine within bread comes from the iodised salt added during processing, therefore
the implementation of sodium reduction targets as a means of reducing population
sodium intakes, may have a negative impact on the iodine status of Victorian
school-aged children. As sodium reduction should remain an important public
health initiative for reducing the risk of cardiovascular disease, such targets should
also take into account the potential impact which their implementation may have
on the iodine content of foods such as bread. In addition, alternative strategies for
improving iodine intakes through foods which are less reliant on iodised salt for
their iodine content, such as milk, need to be considered by health professionals
and government bodies. In summary, the evidence linking both iodine deficiency
and excess to adverse health outcomes in school-aged children provides
Discussion
~ 144 ~
substantial rationale for the implementation of an ongoing population iodine
monitoring program in Australia. Furthermore, such a program will help to further
elucidate the success of mandatory fortification and enable the monitoring of the
impact of various public health strategies, such as the application of sodium
reduction targets to bread, on the iodine nutrition of the population.
~ 145 ~
References
1. Centers for Disease Control and Prevention, National Center for Health Statistics. National Health and Nutrition Examination Survey: About the National Health and Nutrition Examination Survey 2017 [updated 15/9/2017; cited 7/11/2017]. Available from: https://www.cdc.gov/nchs/nhanes/about_nhanes.htm.
2. National Health and Medical Research Council, Australian Department of Health and Ageing, New Zealand Ministry of Health. Nutrient reference values for Australia and New Zealand : including recommended dietary intakes: [Canberra, A.C.T. : National Health and Medical Research Council], c2006.; 2006.
3. Stipanuk MH, Caudill MA. Biochemical, physiological, and molecular aspects of human nutrition / [edited by] Martha H. Stipanuk, Marie A. Caudill: St. Louis, Mo. : Elsevier/Saunders, c2013. 3rd ed.; 2013.
4. Sumar S, Ismail H. Iodine in food and health. Nutr Food Sci. 1997;97(5):175-83. 5. Gibson RS. Principles of nutritional assessment. Gibson RS, editor. Oxford; UK:
Oxford University Press; 2005. 6. Gordon RC, Rose MC, Skeaff SA, Gray AR, Morgan KM, Ruffman T. Iodine
supplementation improves cognition in mildly iodine-deficient children. Am J Clin Nutr. 2009;90(5):1264-71.
7. Zimmermann MB, Connolly K, Bozo M, Bridson J, Rohner F, Grimci L. Iodine supplementation improves cognition in iodine-deficient schoolchildren in Albania: a randomized, controlled, double-blind study. Am J Clin Nutr. 2006;83(1):108-14.
8. World Health Organization. Iodine status worldwide: WHO Global Database on Iodine Deficiency. Geneva: World Health Organization; 2004.
9. Hetzel BS. Iodine deficiency disorders (IDD) and their eradication. Lancet. 1983;2(8359):1126-9.
10. Whitehead DC. The distribution and transformations of iodine in the environment. Environ Int. 1984;10(4):321-39.
11. Tinggi U, Schoendorfer N, Davies PSW, Scheelings P, Olszowy H. Determination of iodine in selected foods and diets by inductively coupled plasma-mass spectrometry. Pure Appl Chem. 2012;84(2):291-9.
12. Connolly RJ. The changing iodine environment of Tasmania. Med J Aust. 1971;2(23):1191-3.
13. Eastman CJ. The Status of Iodine Nutrition in Australia. In: Delange F, Dunn JT, Glinoer D, editors. Iodine Deficiency in Europe: A Continuing Concern. Boston, MA: Springer US; 1993. p. 133-9.
14. Guttikonda K, Burgess JR, Hynes K, Boyages S, Byth K, Parameswaran V. Recurrent iodine deficiency in Tasmania, Australia: a salutary lesson in sustainable iodine prophylaxis and its monitoring. J Clin Endocrinol Metab. 2002;87(6):2809-15.
15. Zimmermann MB, Andersson M. Assessment of iodine nutrition in populations: past, present, and future. Nutr Rev. 2012;70(10):553-70.
16. Als C, Helbling A, Peter K, Haldimann M, Zimmerli B, Gerber H. Urinary iodine concentration follows a circadian rhythm: a study with 3023 spot urine samples in adults and children. J Clin Endocrinol Metab. 2000;85(4):1367-9.
17. Nicolau GY, Haus E, Dumitriu L, Plîngă L, Lakatua DJ, Ehresman D, et al. Circadian and seasonal variations in iodine excretion in children with and without endemic goiter. Endocrinologie. 1989;27(2):73-86.
18. Rasmussen LB, Ovesen L, Christiansen E. Day-to-day and within-day variation in urinary iodine excretion. Eur J Clin Nutr. 1999;53(5):401-7.
References
~ 146 ~
19. Vanacor R, Soares R, Manica D, Furlanetto TW. Urinary Iodine in 24 h Is Associated with Natriuresis and Is Better Reflected by an Afternoon Sample. Ann Nutr Metab. 2008;53(1):43-9.
20. Chen W, Wu Y, Lin L, Tan L, Shen J, Guo X, et al. 24-Hour Urine Samples Are More Reproducible Than Spot Urine Samples for Evaluation of Iodine Status in School-Age Children. J Nutr. 2016;146(1):142-6 5p.
21. Karmisholt J, Laurberg P, Andersen S. Recommended number of participants in iodine nutrition studies is similar before and after an iodine fortification programme. Eur J Nutr. 2014;53(2):487-92.
22. Als C, Keller A, Minder C, Haldimann M, Gerber H. Age- and gender-dependent urinary iodine concentrations in an area-covering population sample from the Bernese region in Switzerland. Eur J Endocrinol. 2000;143(5):629-37.
23. Konig F, Andersson M, Hotz K, Aeberli I, Zimmermann MB. Ten repeat collections for urinary iodine from spot samples or 24-hour samples are needed to reliably estimate individual iodine status in women. J Nutr. 2011;141(11):2049-54.
24. Milhoransa P, Vanacor R, Furlanetto TW. Intra- and Interindividual Iodine Excretion in 24 Hours in Individuals in Southern Brazil: A Cross-Sectional Study. Ann Nutr Metab. 2011;57(3/4):260-4.
25. Remer T, Fonteyn N, Alexy U, Berkemeyer S. Longitudinal examination of 24-h urinary iodine excretion in schoolchildren as a sensitive, hydration status-independent research tool for studying iodine status. Am J Clin Nutr. 2006;83(3):639-46.
26. Soldin OP. Controversies in urinary iodine determinations. Clin Biochem. 2002;35(8):575-9.
27. Ji C, Lu T, Dary O, Legetic B, Campbell NR, Cappuccio FP, et al. Systematic review of studies evaluating urinary iodine concentration as a predictor of 24-hour urinary iodine excretion for estimating population iodine intake. Rev Panam Salud Publica. 2015;38(1):73-81 9p.
28. Andersen S, Karmisholt J, Pedersen KM, Laurberg P. Reliability of studies of iodine intake and recommendations for number of samples in groups and in individuals. Br J Nutr. 2008;99(4):813-8 6p.
29. DePaoli KM, Seal JA, Burgess JR, Taylor R. Improved iodine status in Tasmanian schoolchildren after fortification of bread: a recipe for national success. Med J Aust. 2013;198(9):492-4.
30. Samidurai AJ, Ware RS, Davies PSW, Samidurai AJ, Ware RS, Davies PSW. Advantages of collecting multiple urinary iodine concentrations when assessing iodine status of a population. Acta Paediatr. 2015;104(11):e524-e9 6p.
31. Samidurai AJ, Ware RS, Davies PSW. The Iodine Status of Queensland Preschool Children After the Introduction of Mandatory Iodine Fortification in Bread: An Exploratory Study Using a Convenience Sample. Matern Child Health J. 2016:1-7.
32. Seal JA, Doyle Z, Burgess JR, Taylor R, Cameron AR. Iodine status of Tasmanians following voluntary fortification of bread with iodine. Med J Aust. 2007;186(2):69-71.
33. Gunton JE, Hams G, Fiegert M, McElduff A. Iodine deficiency in ambulatory participants at a Sydney teaching hospital: is Australia truly iodine replete? Med J Aust. 1999;171(9):467-70.
34. Li M, Eastman CJ, Waite KV, Ma G, Zacharin MR, Topliss DJ, et al. Are Australian children iodine deficient? Results of the Australian National Iodine Nutrition Study. Med J Aust. 2006;184(4):165-9.
References
~ 147 ~
35. Skeaff S, Zhao Y, Gibson R, Makrides M, Zhou SJ. Iodine status in pre-school children prior to mandatory iodine fortification in Australia. Matern Child Nutr. 2014;10(2):304-12.
36. He FJ, Ma Y, Feng X, Zhang W, Lin L, Guo X, et al. Effect of salt reduction on iodine status assessed by 24 hour urinary iodine excretion in children and their families in northern China: a substudy of a cluster randomised controlled trial. BMJ Open. 2016;6(9):e011168.
37. World Health Organization, United Nations Children's Fund, International Council for the Control of Iodine Deficiency Disorders. Assessment of Iodine Deficiency Disorders and Monitoring their Elimination: A Guide for Programme Managers. 3rd ed. Geneva: World Health Organisation; 2007.
38. World Health Organization. Urinary iodine concentrations for determining iodine status in populations Geneva: World Health Organistion; 2013 [26 March 2014]. Available from: http://www.who.int/vmnis/indicators/urinaryiodine/en/.
39. Hales I, Reeve T, Myhill J, Dowda K. Goitre: seasonal fluctuations in New South Wales. Med J Aust. 1969;1(8):378-80.
40. Stewart JC, Vidor GI, Buttifield IH, Hetzel BS. Epidemic thyrotoxicosis in northern Tasmania: studies of clinical features and iodine nutrition. Aust N Z J Med. 1971;1(3):203-11.
41. Li M, Ma G, Boyages SC, Eastman CJ. Re-emergence of iodine deficiency in Australia. Asia Pac J Clin Nutr. 2001;10(3):200-3.
42. Guttikonda K, Travers CA, Lewis PR, Boyages S. Iodine deficiency in urban primary school children: a cross-sectional analysis. Med J Aust. 2003;179(7):346-8.
43. McDonnell CM, Harris M, Zacharin MR. Iodine deficiency and goitre in schoolchildren in Melbourne, 2001. Med J Aust. 2003;178(4):159-62.
44. Food Standards Australia New Zealand. Iodine fortification 2012 [26/10/2013]. Available from: http://www.foodstandards.gov.au/consumer/nutrition/iodinefort/Pages/default.aspx.
45. Australian Bureau of Statistics. Australian Health Survey: Nutrition First Results - Foods and Nutrients, 2011-12 2014 [updated 31 July 201412/12/2014]. Available from: http://www.abs.gov.au/AUSSTATS/[email protected]/DetailsPage/4364.0.55.0072011-12?OpenDocument.
46. Charlton K, Probst Y, Kiene G. Dietary Iodine Intake of the Australian Population after Introduction of a Mandatory Iodine Fortification Programme. Nutrients. 2016;8(11).
47. Samidurai AJ, Ware RS, Davies PS. The Iodine Status of Queensland Preschool Children After the Introduction of Mandatory Iodine Fortification in Bread: An Exploratory Study Using a Convenience Sample. Matern Child Health J. 2017;21(1):215-21.
48. Australian Bureau of Statistics. 4364.0.55.003 - Australian Health Survey: Updated Results, 2011-2012: Overweight and Obesity 2013 [updated 2 October 201324 May 2017]. Available from: http://www.abs.gov.au/ausstats/[email protected]/lookup/33C64022ABB5ECD5CA257B8200179437?opendocument.
49. Ohlhorst SD, Slavin M, Bhide JM, Bugusu B. Use of iodized salt in processed foods in select countries around the world and the role of food processors. Compr Rev Food Sci Food Saf. 2012;11(2):233-84.
50. Zimmermann MB. Assessing iodine status and monitoring progress of iodized salt programs. J Nutr. 2004;134(7):1673-7.
References
~ 148 ~
51. Commonwealth Scientific and Industrial Research Organisation. The 2007 Australian National Children's Nutrition and Physical Activity Survey Volume Two: Nutrient Intakes. Canberra: Department of Health and Ageing, 2012.
52. Li M, Waite KV, Ma G, Eastman CJ. Declining iodine content of milk and re-emergence of iodine deficiency in Australia. Med J Aust. 2006;184(6):307.
53. Stewart JC, Vidor GI. Thyrotoxicosis induced by iodine contamination of food--a common unrecognised condition? Br Med J. 1976;1(6006):372-5.
54. Food Standards Australia New Zealand. Iodine in food and iodine requirements 2016 [25/8/2016]. Available from: http://www.foodstandards.gov.au/consumer/nutrition/iodinefood/Pages/default.aspx.
55. Webster JL, Dunford EK, Neal BC. A systematic survey of the sodium contents of processed foods. Am J Clin Nutr. 2010;91(2):413-20.
56. Food Standards Australia New Zealand. Australia New Zealand Food Standards Code - Standard 2.10.2 - Salt and Salt Products. Canberra: Commonwealth of Australia, 2013.
57. Aburto NJ, Ziolkovska A, Hooper L, Elliott P, Cappuccio FP, Meerpohl JJ. Effect of lower sodium intake on health: systematic review and meta-analyses. BMJ (Clinical Research Ed). 2013;346:f1326-f.
58. World Health Organization. WHO issues new guidance on dietary salt and potassium 2013 [27/10/2016]. Available from: http://www.who.int/mediacentre/news/notes/2013/salt_potassium_20130131/en/.
59. National Heart Foundation of Australia. Report on the Evaluation of the nine Food Categories for which reformulation targets were set under the Food and Health Dialogue 2016.
60. Karl H, Münkner W, Krause S, Bagge I. Determination, spatial variation and distribution of iodine in fish. Deutsche Lebensmittel-Rundschau. 2001;97(3):89-96.
61. Julshamn K, Dahl L, Eckhoff K. Determination of iodine in seafood by inductively coupled plasma/mass spectrometry. J AOAC Int. 2001;84(6):1976-83.
62. Laurberg P, Cerqueira C, Ovesen L, Rasmussen LB, Perrild H, Andersen S, et al. Iodine intake as a determinant of thyroid disorders in populations. Best Pract Res Clin Endocrinol Metab. 2010;24(1):13-27.
63. Fisher DA, Oddie TH. Thyroid iodine content and turnover in euthyroid subjects: validity of estimation of thyroid iodine accumulation from short-term clearance studies. J Clin Endocrinol Metab. 1969;29(5):721-7.
64. Nath SK, Moinier B, Thuillier F, Rongier M, Desjeux JF. Urinary excretion of iodide and fluoride from supplemented food grade salt. Int J Vitam Nutr Res. 1992;62(1):66-72.
65. Boyages SC. Clinical review 49: Iodine deficiency disorders. J Clin Endocrinol Metab. 1993;77(3):587-91.
66. Delange F. Iodine deficiency as a cause of brain damage. Postgrad Med J. 2001;77(906):217-20.
67. Zimmermann MB, Jooste PL, Mabapa NS, Mbhenyane X, Schoeman S, Biebinger R, et al. Treatment of iodine deficiency in school-age children increases insulin-like growth factor (IGF)-I and IGF binding protein-3 concentrations and improves somatic growth. J Clin Endocrinol Metab. 2007;92(2):437-42.
68. Pharoah POD, Buttfield IH, Hetzel BS. Neurological damage to the fetus resulting from severe iodine deficiency during pregnancy. Int J Epidemiol. 2012;41(3):589-92.
References
~ 149 ~
69. Zimmermann MB, Hess SY, Adou P, Toresanni T, Wegmüller R, Hurrell RF. Thyroid size and goiter prevalence after introduction of iodized salt: a 5-y prospective study in schoolchildren in Côte d'Ivoire. Am J Clin Nutr. 2003;77(3):663-7 5p.
70. Bleichrodt N, Born MP. A meta-analysis of research on iodine and its relationship to cognitive development. In: Stanbury JB, editor. The damaged brain of iodine deficiency. New York: Cognizant Communication; 1994. p. 195-200.
71. Pharoah PO, Connolly KJ. A controlled trial of iodinated oil for the prevention of endemic cretinism: a long-term follow-up. Int J Epidemiol. 1987;16(1):68-73.
72. Zhou SJ, Anderson AJ, Gibson RA, Makrides M. Effect of iodine supplementation in pregnancy on child development and other clinical outcomes: a systematic review of randomized controlled trials. Am J Clin Nutr. 2013;98(5):1241-54.
73. Taylor PN, Okosieme OE, Dayan CM, Lazarus JH. Impact of iodine supplementation in mild-to-moderate iodine deficiency: Systematic review and meta-analysis. Eur J Endocrinol. 2014;170(1):R1-R15.
74. van den Briel T, West CE, Bleichrodt N, van de Vijver FJR, Ategbo EA, Hautvast JGAJ. Improved iodine status is associated with improved mental performance of schoolchildren in Benin. Am J Clin Nutr. 2000;72(5):1179-85.
75. Bautista A, Barker PA, Dunn JT, Sanchez M, Kaiser DL. The effects of oral iodized oil on intelligence, thyroid status, and somatic growth in school-age children from an area of endemic goiter. Am J Clin Nutr. 1982;35(1):127-34.
76. Isa ZM, Alias IZ, Kadir KA, Ali O. Effect of iodized oil supplementation on thyroid hormone levels and mental performance among Orang Asli schoolchildren and pregnant mothers in an endemic goitre area in Peninsular Malaysia. Asia Pacific Journal Of Clinical Nutrition. 2000;9(4):274-81.
77. Bougma K, Aboud FE, Harding KB, Marquis GS. Iodine and mental development of children 5 years old and under: a systematic review and meta-analysis. Nutrients. 2013;5(4):1384-416.
78. Santiago-Fernandez P, Torres-Barahona R, Muela-Martinez JA, Rojo-Martinez G, Garcia-Fuentes E, Garriga MJ, et al. Intelligence quotient and iodine intake: a cross-sectional study in children. J Clin Endocrinol Metab. 2004;89(8):3851-7.
79. Vermiglio F, Sidoti M, Finocchiaro MD, Battiato S, Lo Presti VP, Benvenga S, et al. Defective neuromotor and cognitive ability in iodine-deficient schoolchildren of an endemic goiter region in Sicily. J Clin Endocrinol Metab. 1990;70(2):379-84.
80. Tiwari BD, Godbole MM, Chattopadhyay N, Mandal A, Mithal A. Learning disabilities and poor motivation to achieve due to prolonged iodine deficiency. Am J Clin Nutr. 1996;63(5):782-6.
81. Zhao W, Han C, Shi X, Xiong C, Sun J, Shan Z, et al. Prevalence of Goiter and Thyroid Nodules before and after Implementation of the Universal Salt Iodization Program in Mainland China from 1985 to 2014: A Systematic Review and Meta-Analysis. PLoS One. 2014;9(10):1-14.
82. Li M, Liu D, et al., Qu CG, Hetzel BS. Endemic goitre in central China caused by excessive iodine intake. Lancet. 1987;ii(Aug. 1):257-9.
83. Pearce EN, Gerber AR, Gootnick DB, Khan LK, Li R, Pino S, et al. Effects of chronic iodine excess in a cohort of long-term American workers in West Africa. J Clin Endocrinol Metab. 2002;87(12):5499-502.
84. Zimmermann MB, Ito Y, Hess SY, Fujieda K, Molinari L. High thyroid volume in children with excess dietary iodine intakes. Am J Clin Nutr. 2005;81(4):840-4.
85. Caldwell KL, Makhmudov A, Ely E, Jones RL, Wang RY. Iodine status of the U.S. population, National Health and Nutrition Examination Survey, 2005-2006 and 2007-2008. Thyroid. 2011;21(4):419-27.
References
~ 150 ~
86. Carvalho AL, Meirelles CJ, Oliveira LA, Costa TM, Navarro AM. Excessive iodine intake in schoolchildren. Eur J Nutr. 2012;51(5):557-62.
87. Stanbury JB, Ermans AE, Bourdoux P, Todd C, Oken E, Tonglet R, et al. Iodine-induced hyperthyroidism: occurrence and epidemiology. Thyroid. 1998;8(1):83-100.
88. Fisher DA, Oddie TH. Thyroidal Radioiodine Clearance and Thyroid Iodine Accumulation: Contrast Between Random Daily Variation and Population Data. J Clin Endocrinol Metab. 1969;29(1):111-5.
89. Institute of Medicine, Panel on Micronutrients. DRI : dietary reference intakes for vitamin A, vitamin K, arsenic, boron, chromium, copper, iodine, iron, manganese, molybdenum, nickel, silicon, vanadium, and zinc : a report of the Panel on Micronutrients ... and the Standing Committee on the Scientific Evaluation of Dietary Reference Intakes, Food and Nutrition Board, Institute of Medicine: Washington, D.C. : National Academy Press, c2001.; 2002.
90. Gardner DF, Centor RM, Utiger RD. Effects of low dose oral iodide supplementation on thyroid function in normal men. Clin Endocrinol (Oxf). 1988;28(3):283-8.
91. Paul T, Meyers B, Witorsch RJ, Pino S, Chipkin S, Ingbar SH, et al. The effect of small increases in dietary iodine on thyroid function in euthyroid subjects. Metabolism. 1988;37(2):121-4.
92. Ingenbleek Y, Malvaux P. Iodine balance studies in protein-calorie malnutrition. Arch Dis Child. 1974;49(4):305-9.
93. Malvaux P, Beckers C, De Visscher M. Iodine balance studies in nongoitrous children and in adolescents on low iodine intake. J Clin Endocrinol Metab. 1969;29(1):79-84.
94. Bates CJ, Thurnham DI, Bingham SA, Margetts BM, Nelson M. Biochemical markers of nutrient intake. In: Margetts BM, Nelson M, editors. Design Concepts in Nutritional Epidemiology. Oxford: Oxford University Press; 1997. p. 170-240.
95. Dunn JT, Crutchfield HE, Gutekunst R, Dunn D. Methods for Measuring Iodine in Urine. The Netherlands: International Council for Control of Iodine Deficiency Disorders, The World Health Organisation; 1993.
96. Zimmermann MB. The influence of iron status on iodine utilization and thyroid function. Annu Rev Nutr. 2006;26(1):367-89 23p.
97. Zimmermann MB, Hess SY, Molinari L, De Benoist B, Delange F, Braverman LE, et al. New reference values for thyroid volume by ultrasound in iodine-sufficient schoolchildren: a World Health Organization/Nutrition for Health and Development Iodine Deficiency Study Group Report. Am J Clin Nutr. 2004;79(2):231-7.
98. Zimmermann MB. Methods to assess iron and iodine status. Br J Nutr. 2008;99 Suppl 3:S2-9.
99. Lamberg BA. Iodine deficiency disorders and endemic goitre. J Am Diet Assoc. 1993;93(7):834.
100. Hetzel BS, Potter BJ, Dulberg EM. The iodine deficiency disorders: nature, pathogenesis and epidemiology. World Rev Nutr Diet. 1990;62:59-119.
101. Pan American Health Organization (PAHO)/World Health Organization (WHO) Technical Group on Endemic Goiter C, and Iodine Deficiency, . Towards the Eradication of Endemic Goiter, Cretinism, and Iodine Deficiency: Proceedings of the Fifth Meeting of the PAHO/WHO Technical Group on Endemic Goiter, Cretinism, and Iodine Deficiency, Lima, Peru, November 1983. In: Dunn JT, Pretell EA, Daza CH, Viteri FE, editors. Washington, DC: Pan American Health Organization; 1986.
References
~ 151 ~
102. World Health Organization, United Nations Children's Fund, International Council for the Control of Iodine Deficiency Disorders. Indicators for assessing iodine deficiency disorders and their control programmes. Report of a Joint WHO/ UNICEF/ICCIDD consultation, Geneva, Switzerland, 3–5 November 1992. Geneva: World Health Organisation, 1993.
103. World Health Organization. Goitre as a determinant of the prevalence and severity of iodine deficiency disorders in populations. Geneva: World Health Organization, 2014.
104. Aghini-Lombardi F, Antonangeli L, Pinchera A, Leoli F, Rago T, Bartolomei AM, et al. Effect of iodized salt on thyroid volume of children living in an area previously characterized by moderate iodine deficiency. J Clin Endocrinol Metab. 1997;82(4):1136-9.
105. Jooste PL, Weight MJ, Lombard CJ. Short-term effectiveness of mandatory iodization of table salt, at an elevated iodine concentration, on the iodine and goiter status of schoolchildren with endemic goiter. Am J Clin Nutr. 2000;71(1):75-80.
106. Zimmermann MB, Adou P, Torresani T, Zeder C, Hurrell RF. Effect of oral iodized oil on thyroid size and thyroid hormone metabolism in children with concurrent selenium and iodine deficiency. Eur J Clin Nutr. 2000;54(3):209-13.
107. Delange F, Benker G, Caron P, Eber O, Ott W, Peter F, et al. Thyroid volume and urinary iodine in European schoolchildren: standardization of values for assessment of iodine deficiency. Eur J Endocrinol. 1997;136(2):180-7.
108. Zimmermann MB, Molinari L, Spehl M, Weidinger-Toth J, Podoba J, Hess S, et al. Toward a consensus on reference values for thyroid volume in iodine-replete schoolchildren: results of a workshop on inter-observer and inter-equipment variation in sonographic measurement of thyroid volume. Eur J Endocrinol. 2001;144(3):213-20.
109. Hetzel BS, Dunn JT. The iodine deficiency disorders: their nature and prevention. Annu Rev Nutr. 1989;9:21-38.
110. Vejbjerg P, Knudsen N, Perrild H, Laurberg P, Andersen S, Rasmussen LB, et al. Estimation of iodine intake from various urinary iodine measurements in population studies. Thyroid. 2009;19(11):1281-6.
111. Perrine CG, Cogswell ME, Swanson CA, Sullivan KM, Chen TC, Carriquiry AL, et al. Comparison of Population Iodine Estimates from 24-Hour Urine and Timed-Spot Urine Samples. Thyroid. 2014.
112. World Health Organization, United Nations Children's Fund, International Council for the Control of Iodine Deficiency Disorders. A practical guide to the correction of iodine deficiency. Wageningen: International Council for the Control of Iodine Deficiency Disorders, 1990.
113. Knudsen N, Christiansen E, Brandt-Christensen M, Nygaard B, Perrild H. Age- and sex-adjusted iodine/creatinine ratio. A new standard in epidemiological surveys? Evaluation of three different estimates of iodine excretion based on casual urine samples and comparison to 24 h values. Eur J Clin Nutr. 2000;54(4):361-3.
114. Konno N, Yuri K, Miura K, Kumagai M, Murakami S. Clinical evaluation of the iodide/creatinine ratio of casual urine samples as an index of daily iodide excretion in a population study. Endocr J. 1993;40(1):163-9.
115. Montenegro-Bethancourt G, Johner SA, Stehle P, Neubert A, Remer T. Iodine status assessment in children: spot urine iodine concentration reasonably reflects true twenty-four-hour iodine excretion only when scaled to creatinine. Thyroid. 2015;25(6):688-97.
References
~ 152 ~
116. Remer T, Neubert A, Maser-Gluth C. Anthropometry-based reference values for 24-h urinary creatinine excretion during growth and their use in endocrine and nutritional research. Am J Clin Nutr. 2002;75(3):561-9.
117. Ascoli W, Arroyave G. Epidemiologia el bocio endémico en Centro América. Relación entre prevalencia y excreción urinaria de yodo [Epidemiology of endemic goiter in Central America. Association between prevalence and urinary iodine excretion]. Arch Latinoam Nutr. 1970;20:309-20.
118. Bourdoux P. Measurement of iodine in the assessment of iodine deficiency. IDD Newsletter. 1988;4(1):8-12.
119. Mage DT, Allen RH, Kodali A. Creatinine corrections for estimating children's and adult's pesticide intake doses in equilibrium with urinary pesticide and creatinine concentrations. J Expo Sci Environ Epidemiol. 2008;18(4):360-8.
120. Kesteloot H, Joossens JV. On the determinants of the creatinine clearance: a population study. J Hum Hypertens. 1996;10(4):245-9.
121. Bingham SA, Cummings JH. The use of creatinine output as a check on the completeness of 24-hour urine collections. Hum Nutr Clin Nutr. 1985;39(5):343-53.
122. Edwards OM, Bayliss RIS, Millen S. Urinary Creatinine Excretion as an Index of the Completeness of 24-Hour Urine Collections. The Lancet. 1969;294(7631):1165-6.
123. Johner SA, Boeing H, Thamm M, Remer T. Urinary 24-h creatinine excretion in adults and its use as a simple tool for the estimation of daily urinary analyte excretion from analyte/creatinine ratios in populations. Eur J Clin Nutr. 2015;69(12):1336-43.
124. Vought RL, London WT, Lutwak L, Dublin TD. Reliability of Estimates of Serum Inorganic Iodine and Daily Fecal and Urinary Iodine Excretion from Single Casual Specimens. J Clin Endocrinol Metab. 1963;23:1218-28.
125. Frey HM, Rosenlund B, Torgersen JP. Value of single urine specimens in estimation of 24 hour urine iodine excretion. Acta Endocrinol (Copenh). 1973;72(2):287-92.
126. Thomson CD, Smith TE, Butler KA, Packer MA. An evaluation of urinary measures of iodine and selenium status. J Trace Elem Med Biol. 1996;10(4):214-22.
127. Remer T, Fonteyn N, Alexy U, Berkemeyer S. Longitudinal examination of 24-h urinary iodine excretion in schoolchildren as a sensitive, hydration status–independent research tool for studying iodine status. Am J Clin Nutr. 2006;83(3):639-46.
128. Zimmermann MB, Hussein I, Al Ghannami S, El Badawi S, Al Hamad NM, Abbas Hajj B, et al. Estimation of the Prevalence of Inadequate and Excessive Iodine Intakes in School-Age Children from the Adjusted Distribution of Urinary Iodine Concentrations from Population Surveys. J Nutr. 2016;146(6):1204-11.
129. Bourdoux P. Evaluation of the iodine intake: problems of the iodine/creatinine ratio--comparison with iodine excretion and daily fluctuations of iodine concentration. Experimental And Clinical Endocrinology & Diabetes: Official Journal, German Society Of Endocrinology [And] German Diabetes Association. 1998;106 Suppl 3:S17-S20.
130. Hynes KL, Blizzard CL, Venn AJ, Dwyer T, Burgess JR. Persistent iodine deficiency in a cohort of Tasmanian school children: associations with socio-economic status, geographical location and dietary factors. Aust N Z J Public Health. 2004;28(5):476-81.
131. Samidurai AJ, Davies PSW, editors. The iodine status of preschool aged children after the introduction of mandatory iodine fortification of bread2013: The Nutrition Society of Australia.
132. Rose M, Gordon R, Skeaff S. Using bread as a vehicle to improve the iodine status of New Zealand children. N Z Med J. 2009;122(1290):14-23.
References
~ 153 ~
133. Skeaff SA, Lonsdale-Cooper E. Mandatory fortification of bread with iodised salt modestly improves iodine status in schoolchildren. Br J Nutr. 2013;109(6):1109-13.
134. Skeaff SA, Thomson CD, Gibson RS. Mild iodine deficiency in a sample of New Zealand schoolchildren. Eur J Clin Nutr. 2002;56(12):1169-75.
135. Skeaff SA, Thomson CD, Gibson RS. Iodine Deficiency Disorders (IDD) in the New Zealand population: another example of an outmoded IDD control programme. Asia Pac J Clin Nutr; Australia: HEC Press; 2003. p. S15.
136. Skeaff SA, Thomson CD, Wilson N, Parnell WR. A comprehensive assessment of urinary iodine concentration and thyroid hormones in New Zealand schoolchildren: a cross-sectional study. Nutrition Journal. 2012;11(1):31-7.
137. World Health Organization, Food and Agriculture Organization of the United Nations. Iodine: Recommended intakes for iodine. In: World Health Organisation, editor. Vitamin and Mineral Requirements in Human Nutrition: World Health Organization,; 2004. p. 306-10.
138. World Health Organization, International Council for the Control of Iodine Deficiency Disorders. Recommended normative values for thyroid volume in children aged 6 - 15 years. World Health Organization, 1997.
139. Foo LC, Zulfiqar A, Nafikudin M, Fadzil MT, Asmah AS. Local versus WHO/International Council for Control of Iodine Deficiency Disorders-recommended thyroid volume reference in the assessment of iodine deficiency disorders. European Journal Of Endocrinology / European Federation Of Endocrine Societies. 1999;140(6):491-7.
140. Hess SY, Zimmermann MB. Thyroid volumes in a national sample of iodine-sufficient swiss school children: comparison with the World Health Organization/International Council for the control of iodine deficiency disorders normative thyroid volume criteria. European Journal Of Endocrinology / European Federation Of Endocrine Societies. 2000;142(6):599-603.
141. Xu F, Sullivan K, Houston R, Zhao J, May W, Maberly G. Thyroid volumes in US and Bangladeshi schoolchildren: comparison with European schoolchildren. Eur J Endocrinol. 1999;140(6):498-504.
142. World Health Organization, United Nations Children's Fund, International Council for the Control of Iodine Deficiency Disorders. Assessment of iodine deficiency disorders and monitoring their elimination: a guide for programme managers, 2nd ed. Geneva: World Health Organisation, 2001.
143. Jooste PL, Weight MJ, Kriek JA, Louw AJ. Endemic goitre in the absence of iodine deficiency in schoolchildren of the Northern Cape Province of South Africa. Eur J Clin Nutr. 1999;53(1):8-12.
144. Andersson M, Takkouche B, Egli I, Allen HE, De Benoist B. Current global iodine status and progress over the last decade towards the elimination of iodine deficiency. Bull WHO. 2007;85(5):518-25.
145. Mattsson S, Lindström S. Diuresis and voiding pattern in healthy schoolchildren. Br J Urol. 1995;76(6):783-9.
146. de Benoist B, McLean E, Andersson M, Rogers L. Iodine deficiency in 2007: global progress since 2003. Food and nutrition bulletin. 2008;29(3):195-202.
147. Andersson M, Karumbunathan V, Zimmermann MB. Global iodine status in 2011 and trends over the past decade. J Nutr. 2012;142(4):744-50.
148. Zimmermann MB. Iodine deficiency and excess in children: worldwide status in 2013. Endocr Pract. 2013;19(5):839-46.
149. Pearce EN, Andersson M, Zimmermann MB. Global iodine nutrition: Where do we stand in 2013? Thyroid: Official Journal Of The American Thyroid Association. 2013;23(5):523-8.
References
~ 154 ~
150. Eastman CJ. Where has all our iodine gone? Med J Aust. 1999;171(9):455-6. 151. Cross C, Moriarty H, Coakley J. Prevalence of iodine deficiency in infants and young
children in Western Sydney, Australia: a cross-sectional analysis. Infant Child Adolesc Nutr. 2010;2(5):284-7.
152. World Health Organization, United Nations Children's Fund, International Council for the Control of Iodine Deficiency Disorders. Indicators for assessing Iodine Deficiency Disorders and their control through salt iodisation. Geneva: World Health Organisation, 1994
153. World Health Organization, United Nations Children's Fund, International Council for the Control of Iodine Deficiency Disorders. Recommended iodine levels in salt and guidelines for monitoring their adequacy and effectiveness. Geneva: World Health Organisation; 1996.
154. Food Standards Australia New Zealand. Initial Assessment Report: Proposal P230 - Iodine Fortification. Canberra: Food Standards Australia New Zealand, 2004.
155. Food Standards Australia New Zealand. Australia New Zealand Food Standards Code - Standard 2.1.1 - Cereals and Cereal Products. Canberra: Commonwealth of Australia, 2014.
156. Australian Bureau of Statistics. 4364.0.55.003 - Australian Health Survey: Updated Results, 2011-2012 2013 [cited 2016]. Available from: http://www.abs.gov.au/ausstats/[email protected]/Lookup/4364.0.55.003Chapter12011-2012.
157. Thompson FE, Subar AF. Dietary assessment methodology. Coulston AM, Rock CL, Monsen ER, editors. San Diego; USA: Academic Press; 2001.
158. Food Standards Australia New Zealand. AUSNUT 2011-13: Classification of foods and dietary supplements 2013 [9/01/2015]. Available from: http://www.foodstandards.gov.au/science/monitoringnutrients/ausnut/classificationofsupps/Pages/default.aspx.
159. Hennessy Á, Ní Chaoimh C, McCarthy EK, Kingston C, Irvine AD, Hourihane JOB, et al. Variation in iodine food composition data has a major impact on estimates of iodine intake in young children. Eur J Clin Nutr. 2017.
160. Johner SA, Thamm M, Nöthlings U, Remer T. Iodine status in preschool children and evaluation of major dietary iodine sources: a German experience. Eur J Nutr. 2013;52(7):1711-9.
161. Perrine CG, Sullivan KM, Flores R, Caldwell KL, Grummer-Strawn LM. Intakes of dairy products and dietary supplements are positively associated with iodine status among U.S. children. J Nutr. 2013;143(7):1155-60.
162. Jones E, McLean R, Davies B, Hawkins R, Meiklejohn E, Ma ZF, et al. Adequate Iodine Status in New Zealand School Children Post-Fortification of Bread with Iodised Salt. Nutrients. 2016;8(5).
163. Australian Bureau of Statistics. National Nutrition Survey: Foods Eaten Australia 1995. Canberra: Commonwealth of Australia, 1999.
164. New Zealand Ministry of Health. NZ Food NZ Children: Key results of the 2002 National Nutrition Survey. Wellington: Ministry of Health, 2003.
165. Flachowsky G, Franke K, Meyer U, Leiterer M, Schöne F. Influencing factors on iodine content of cow milk. Eur J Nutr. 2014;53(2):351-65.
166. Castro SI, Berthiaume R, Robichaud A, Lacasse P. Effects of iodine intake and teat-dipping practices on milk iodine concentrations in dairy cows. J Dairy Sci. 2012;95(1):213-20.
167. Van der Reijden O, Galetti V, Hulmann M, Haldimann M, Schlegel P, Kreuzer M, et al. IDENTIFYING SOURCES AND VARIABILITY OF IODINE IN COW’S MILK TO ENSURE
References
~ 155 ~
ADEQUATE DIETARY IODINE INTAKES BY THE SWISS POPULATION. Ann Nutr Metab. 2017;71:315-6.
168. Grace ND, Waghorn GC. Impact of iodine supplementation of dairy cows on milk production and iodine concentrations in milk. N Z Vet J. 2005;53(1):10-3.
169. Bath SC, Combet E, Scully P, Zimmermann MB, Hampshire-Jones KHC, Rayman MP. A multi-centre pilot study of iodine status in UK schoolchildren, aged 8-10 years. Eur J Nutr. 2015.
170. Bath SC, Rayman MP. Trace element concentration in organic and conventional milk: what are the nutritional implications of the recently reported differences? Br J Nutr. 2016;116(1):3-6.
171. Aburto N, Abudou M, Candeias V, Wu T. Effect and safety of salt iodization to prevent iodine deficiency disorders: a systematic review with meta-analyses. Geneva: World Health Organisation; 2014.
172. Li M, Chapman S, Agho K, Eastman CJ. Can even minimal news coverage influence consumer health-related behaviour? A case study of iodized salt sales, Australia. Health Educ Res. 2008;23(3):543-8.
173. James WP, Ralph A, Sanchez-Castillo CP. The dominance of salt in manufactured food in the sodium intake of affluent societies. Lancet (London, England). 1987;1(8530):426-9.
174. Nowson C, Lim K, Grimes C, O'Halloran S, Land MA, Webster J, et al. Dietary Salt Intake and Discretionary Salt Use in Two General Population Samples in Australia: 2011 and 2014. Nutrients. 2015;7(12):10501-12.
175. Espeland MA, Kumanyika S, Wilson AC, Reboussin DM, Easter L, Self M, et al. Statistical Issues in Analyzing 24-Hour Dietary Recall and 24-Hour Urine Collection Data for Sodium and Potassium Intakes. Am J Epidemiol. 2001;153(10):996-1006.
176. Libuda L, Kersting M, Alexy U. Consumption of dietary salt measured by urinary sodium excretion and its association with body weight status in healthy children and adolescents. Public Health Nutr. 2012;15(3):433-41.
177. Choi J, Kim H, Hong D, Lim H, Kim J. Urinary iodine and sodium status of urban Korean subjects: a pilot study. Clin Biochem. 2012;45(7/8):596-8.
178. Charlton K, Land M-A, Ma G, Yeatman H, Houweling F. Iodine status similarly suboptimal in Australian women who have desirable salt intakes compared to those with excessive intakes. Nutrition. 2014;30(2):234-5.
179. Charlton KE, Jooste PL, Steyn K, Levitt NS, Ghosh A. A lowered salt intake does not compromise iodine status in Cape Town, South Africa, where salt iodization is mandatory. Nutrition. 2013;29(4):630-4.
180. Aaron KJ, Sanders PW. Role of dietary salt and potassium intake in cardiovascular health and disease: a review of the evidence. Mayo Clin Proc. 2013;88(9):987-95.
181. He FJ, MacGregor GA. Importance of salt in determining blood pressure in children: meta-analysis of controlled trials. Hypertension. 2006;48(5):861-9.
182. He FJ, Marrero NM, MacGregor GA. Salt and blood pressure in children and adolescents. J Hum Hypertens. 2007;22(1):4-11.
183. Simons-Morton DG, Obarzanek E. Diet and blood pressure in children and adolescents. Pediatr Nephrol. 1997;11(2):244-9.
184. He FJ, Marrero NM, MacGregor GA. Salt Intake Is Related to Soft Drink Consumption in Children and Adolescents. A Link to Obesity? 2008;51(3):629-34.
185. Grimes CA, Wright JD, Liu K, Nowson CA, Loria CM. Dietary sodium intake is associated with total fluid and sugar-sweetened beverage consumption in US children and adolescents aged 2–18 y: NHANES 2005–2008. Am J Clin Nutr. 2013;98(1):189-96.
References
~ 156 ~
186. Grimes CA, Riddell LJ, Campbell KJ, Nowson CA. Dietary Salt Intake, Sugar-Sweetened Beverage Consumption, and Obesity Risk. Pediatrics. 2013;131(1):14-21.
187. Stachenfeld NS. Acute effects of sodium ingestion on thirst and cardiovascular function. Curr Sports Med Rep. 2008;7(4 Suppl):S7-13.
188. Grimes CA, Riddell LJ, Campbell KJ, He FJ, Nowson CA. 24-h urinary sodium excretion is associated with obesity in a cross-sectional sample of Australian schoolchildren. Br J Nutr. 2016;115(6):1071-9.
189. Strazzullo P, D’Elia L, Kandala N-B, Cappuccio FP. Salt intake, stroke, and cardiovascular disease: meta-analysis of prospective studies. BMJ. 2009;339.
190. World Health Organization. Guideline: sodium intake for adults and children. Geneva: World Health Organisation, 2012.
191. Trieu K, Neal B, Hawkes C, Dunford E, Campbell N, Rodriguez-Fernandez R, et al. Salt Reduction Initiatives around the World – A Systematic Review of Progress towards the Global Target. PLoS One. 2015;10(7):e0130247.
192. He FJ, Brinsden HC, MacGregor GA. Salt reduction in the United Kingdom: a successful experiment in public health. J Hum Hypertens. 2014;28(6):345-52.
193. National Institute for Health Care and Excellence. Cardiovascular disease prevention 2010 [updated June 2010; cited 10/10/2015]. Available from: https://www.nice.org.uk/guidance/ph25.
194. Webster J, Dunford E, Kennington S, Neal B, Chapman S. Drop the Salt! Assessing the impact of a public health advocacy strategy on Australian government policy on salt. Public Health Nutr. 2014;17(1):212-8.
195. Webster J, Dunford E, Huxley R, Li N, Nowson CA, Neal B. The development of a national salt reduction strategy for Australia. Asia Pacific Journal of Clinical Nutrition. 2009;18(3):303-9.
196. Food Standards Australia New Zealand. Monitoring the Australian population’s intake of dietary iodine before and after mandatory fortification. 2016.
197. Webster J, Land MA, Christoforou A, Eastman CJ, Zimmerman M, Campbell NR, et al. Reducing dietary salt intake and preventing iodine deficiency: towards a common public health agenda. Med J Aust. 2014;201(9):507-8.
198. Jones A, Magnusson R, Swinburn B, Webster J, Wood A, Sacks G, et al. Designing a Healthy Food Partnership: lessons from the Australian Food and Health Dialogue. BMC Public Health. 2016;16:651.
199. World Health Organisation. 2008-2013 Action Plan for the Global Strategy for the Prevention and Control of Noncommunicable Diseases. Geneva, Switzerland: World Health Organization, 2009.
200. Moher D, Shamseer L, Clarke M, Ghersi D, Liberati A, Petticrew M, et al. Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement. Systematic Reviews. 2015;4:1-.
201. Moher D, Liberati A, Tetzlaff J, Altman DG, Group P. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. BMJ. 2009;339:b2535.
202. Kroke A, Manz F, Kersting M, Remer T, Sichert-Hellert W, Alexy U, et al. The DONALD Study. History, current status and future perspectives. Eur J Nutr. 2004;43(1):45-54.
203. Bokhof B, Günther ALB, Berg-Beckhoff G, Kroke A, Buyken AE. Validation of protein intake assessed from weighed dietary records against protein estimated from 24 h urine samples in children, adolescents and young adults participating in the Dortmund Nutritional and Longitudinally Designed (DONALD) Study. Public Health Nutr. 2010;13(6):826-34.
References
~ 157 ~
204. Dimitriou T, Huesemann S, Neubert A, Remer T. Measurements of urinary leptin and capillary leptin: alternative tools for the assessment of the leptin status? Hormone Res. 2001;56(3-4):93-7.
205. Ebner A, Manz F. Sex difference of urinary osmolality in German children. Am J Nephrol. 2002;22(4):352-5.
206. Esche J, Johner S, Shi L, Schonau E, Remer T. Urinary Citrate, an Index of Acid-Base Status, Predicts Bone Strength in Youths and Fracture Risk in Adult Females. J Clin Endocrinol Metab. 2016;101(12):4914-21.
207. Penczynski KJ, Krupp D, Bring A, Bolzenius K, Remer T, Buyken AE. Relative validation of 24-h urinary hippuric acid excretion as a biomarker for dietary flavonoid intake from fruit and vegetables in healthy adolescents. Eur J Nutr. 2015.
208. Krupp D, Doberstein N, Shi L, Remer T. Hippuric acid in 24-hour urine collections is a potential biomarker for fruit and vegetable consumption in healthy children and adolescents. The Journal Of Nutrition. 2012;142(7):1314-20.
209. Remer T, Shi L, Buyken AE, Maser-Gluth C, Hartmann MF, Wudy SA. Prepubertal adrenarchal androgens and animal protein intake independently and differentially influence pubertal timing. J Clin Endocrinol Metab. 2010;95(6):3002-9.
210. Degen GH, Blaszkewicz M, Shi L, Buyken AE, Remer T. Urinary isoflavone phytoestrogens in German children and adolescents--a longitudinal examination in the DONALD cohort. Mol Nutr Food Res. 2011;55(3):359-67.
211. Manz F, van't Hof MA, Haschke F. Iodine supply in children from different european areas: the Euro-growth study. Committee for the Study of Iodine Supply in European Children. J Pediatr Gastroenterol Nutr. 2000;31 Suppl 1:S72-S5.
212. Montenegro-Bethancourt G, Johner SA, Remer T. Contribution of fruit and vegetable intake to hydration status in schoolchildren. Am J Clin Nutr. 2013;98(4):1103-12.
213. Montenegro-Bethancourt G, Johner SA, Stehle P, Remer T. Dietary ratio of animal:plant protein is associated with 24-h urinary iodine excretion in healthy school children. Br J Nutr. 2015;114(1):24-33 10p.
214. Cogswell ME, Maalouf J, Elliott P, Loria CM, Patel S, Bowman BA. Use of Urine Biomarkers to Assess Sodium Intake: Challenges and Opportunities. Annu Rev Nutr. 2015;35:349-87 33p.
215. John KA, Cogswell ME, Campbell NR, Nowson CA, Legetic B, Hennis AJM, et al. Accuracy and Usefulness of Select Methods for Assessing Complete Collection of 24-Hour Urine: A Systematic Review. The Journal of Clinical Hypertension. 2016;18(5):456-67.
216. G.A. Wells, B. Shea, D. O'Connell, J. Peterson, V. Welch, M. Losos, et al. The Newcastle-Ottawa Scale (NOS) for assessing the quality of nonrandomised studies in meta-analyses 1999 [2/8/2016]. Available from: http://www.ohri.ca/programs/clinical_epidemiology/oxford.asp.
217. Marrero NM, He FJ, Whincup P, Macgregor GA. Salt intake of children and adolescents in South London: consumption levels and dietary sources. Hypertension. 2014;63(5):1026-32.
218. Borawski KM, Sur RL, Miller OF, Pak CYC, Preminger GM, Kolon TF. Urinary reference values for stone risk factors in children. The Journal Of Urology. 2008;179(1):290-4.
219. Ajayi OA, Adeyemi IA, Osifo BOA. The urinary excretion of riboflavin among Nigerian teenagers. Ecol Food Nutr. 1977;6(1):49-52.
220. M'Buyamba-Kabangu JR, Fagard R, Lijnen P, Mbuy wa Mbuy R, Staessen J, Amery A. Blood pressure and urinary cations in urban Bantu of Zaire. Am J Epidemiol. 1986;124(6):957-68.
References
~ 158 ~
221. Omid N, Maguire A, O'Hare WT, Zohoori FV. Total daily fluoride intake and fractional urinary fluoride excretion in 4- to 6-year-old children living in a fluoridated area: weekly variation? Community Dent Oral Epidemiol. 2017;45(1):12-9.
222. Vanderas AP, Papagiannoulis L. Urinary catecholamine levels in children with and without a history of dentofacial injuries. Endod Dent Traumatol. 1995;11(5):205-9.
223. Abuhaloob L, Maguire A, Moynihan P. Fractional Urinary Fluoride Excretion (FUFE) of 3-4 year children in the Gaza Strip. Community Dent Health. 2015;32(1):8-15.
224. Acevedo AM, Febres-Cordero C, Feldman S, Arasme MA, Pedauga DF, Gonzalez H, et al. Urinary fluoride excretion in children aged 3 to 5 years exposed to fluoridated salt at 60 to 90 mgF/Kg in two Venezuelan cities. A pilot study. Acta Odontol Latinoam. 2007;20(1):9-16.
225. Allevard-Burguburu AM, Geelen G, Sempore B, Louis F, Legros JJ, Gharib C. Urinary excretion of immunoreactive vasopressin in prepubertal children. Lack of correlation with urinary excretion of immunoreactive neurophysins. Eur J Pediatr. 1981;137(3):291-4.
226. Aparicio A, Rodriguez-Rodriguez E, Cuadrado-Soto E, Navia B, Lopez-Sobaler AM, Ortega RM. Estimation of salt intake assessed by urinary excretion of sodium over 24 h in Spanish subjects aged 7-11 years. Eur J Nutr. 2015;56(1):171-8.
227. Ballauff A, Kersting M, Manz F. Do children have an adequate fluid intake? Water balance studies carried out at home. Ann Nutr Metab. 1988;32(5-6):332-9.
228. Clark PM, Hindmarsh PC, Shiell AW, Law CM, Honour JW, Barker DJ. Size at birth and adrenocortical function in childhood. Clin Endocrinol (Oxf). 1996;45(6):721-6.
229. Fujishima S, Tochikubo O, Kaneko Y. Environmental and physiological characteristics in adolescents genetically predisposed to hypertension. Jpn Circ J. 1983;47(2):276-82.
230. Haftenberger M, Viergutz G, Neumeister V, Hetzer G. Total fluoride intake and urinary excretion in German children aged 3-6 years. Caries Res. 2001;35(6):451-7.
231. Haga M, Sakata T. Daily salt intake of healthy Japanese infants of 3-5 years based on sodium excretion in 24-hour urine. J Nutr Sci Vitaminol (Tokyo). 2010;56(5):305-10.
232. He FJ, Wu Y, Feng XX, Ma J, Ma Y, Wang H, et al. School based education programme to reduce salt intake in children and their families (School-EduSalt): cluster randomised controlled trial. BMJ. 2015;350:h770.
233. Hesse A, Classen A, Knoll M, Timmermann F, Vahlensieck W. Dependence of urine composition on the age and sex of healthy subjects. Clin Chim Acta. 1986;160(2):79-86.
234. Hollriegl V, Arogunjo AM, Giussani A, Michalke B, Oeh U. Daily urinary excretion of uranium in members of the public of Southwest Nigeria. Sci Total Environ. 2011;412-413:344-50.
235. Juárez López MLA, Hernández Guerrero JC, Adriano Anaya MP, Pruneda FM. Urinary fluoride excretion in 3-5-year-old children with and without malnutrition. Fluoride. 2016;49(2):178-84.
236. Ketley CE, Cochran JA, Holbrook WP, Sanches L, van Loveren C, Oila AM, et al. Urinary fluoride excretion by preschool children in six European countries. Community Dent Oral Epidemiol. 2004;32 Suppl 1:62-8.
237. Ketley CE, Lennon MA. Determination of fluoride intake from urinary fluoride excretion data in children drinking fluoridated school milk. Caries Res. 2001;35(4):252-7.
238. Khandare AL, Rao GS, Lakshmaiah N. Effect of tamarind ingestion on fluoride excretion in humans. Eur J Clin Nutr. 2002;56(1):82-5.
References
~ 159 ~
239. Kirdpon S, Kirdpon W, Airarat W, Thepsuthammarat K, Nanakorn S. Changes in urinary compositions among children after consuming prepared oral doses of aloe (Aloe vera Linn). J Med Assoc Thai. 2006;89(8):1199-205.
240. Kristbjornsdottir OK, Halldorsson TI, Thorsdottir I, Gunnarsdottir I. Association between 24-hour urine sodium and potassium excretion and diet quality in six-year-old children: a cross sectional study. Nutr J. 2012;11:94.
241. Maguire A, Walls R, Steen N, Teasdale L, Landes D, Omid N, et al. Urinary fluoride excretion in 6- to 7-year-olds ingesting milk containing 0.5 or 0.9 mg fluoride. Caries Res. 2013;47(4):291-8.
242. Martins CC, Paiva SM, Cury JA. Effect of discontinuation of fluoride intake from water and toothpaste on urinary excretion in young children. Int J Environ Res Public Health. 2011;8(6):2132-41.
243. Maruhama Y, Hikichi I, Hashimoto T, Saito F, Ninomiya K. Further evidence for insulin hypersecretion not as an initial event but as a consequence of body growth and maturation in juvenile-onset obesity. Diabetes Res Clin Pract. 1986;2(2):83-90.
244. Matkovic V, Ilich JZ, Andon MB, Hsieh LC, Tzagournis MA, Lagger BJ, et al. Urinary calcium, sodium, and bone mass of young females. Am J Clin Nutr. 1995;62(2):417-25.
245. Mori M, Mori H, Hamada A, Yamori Y. Taurine in morning spot urine for the useful assessment of dietary seafood intake in Japanese children and adolescents. J Biomed Sci. 2010;17 Suppl 1:S43.
246. Padrao P, Neto M, Pinto M, Oliveira AC, Moreira A, Moreira P. Urinary hydration biomarkers and dietary intake in children. Nutr Hosp. 2016;33(Suppl 3):314.
247. Rafie N, Mohammadifard N, Khosravi A, Feizi A, Safavi SM. Relationship of sodium intake with obesity among Iranian children and adolescents. ARYA Atherosclerosis. 2017;13(1):1-6.
248. Rugg-Gunn AJ, Nunn JH, Ekanayake L, Saparamadu KD, Wright WG. Urinary fluoride excretion in 4-year-old children in Sri Lanka and England. Caries Res. 1993;27(6):478-83.
249. Sinaiko AR, Gomez-Marin O, Smith CL, Prineas RJ. Comparison of serum calcium levels between junior high school children with high-normal and low-normal blood pressure. The child and adolescent blood pressure program. Am J Hypertens. 1994;7(12):1045-51.
250. Staessen J, Bulpitt C, Fagard R, Joossens JV, Lijnen P, Amery A. Four urinary cations and blood pressure. A population study in two Belgian towns. Am J Epidemiol. 1983;117(6):676-87.
251. Touitou Y, Auzeby A, Camus F, Djeridane Y. Twenty-four-hour profiles of urinary excretion of calcium, magnesium, phosphorus, urea, and creatinine in healthy prepubertal boys. Clin Biochem. 2010;43(1-2):102-5.
252. Villa A, Anabalón M, Cabezas L. The fractional urinary fluoride excretion in young children under stable fluoride intake conditions. Community Dent Oral Epidemiol. 2000;28(5):344-55.
253. Zhang L, Zhao F, Zhang P, Gao J, Liu C, He FJ, et al. A pilot study to validate a standardized one-week salt estimation method evaluating salt intake and its sources for family members in China. Nutrients. 2015;7(2):751-63.
254. Zohouri FV, Rugg-Gunn AJ. Total fluoride intake and urinary excretion in 4-year-old Iranian children residing in low-fluoride areas. The British Journal Of Nutrition. 2000;83(1):15-25.
255. Zohouri FV, Swinbank CM, Maguire A, Moynihan PJ. Is the fluoride/creatinine ratio of a spot urine sample indicative of 24-h urinary fluoride? Community Dent Oral Epidemiol. 2006;34(2):130-8.
References
~ 160 ~
256. Melse-Boonstra A, Rozendaal M, Rexwinkel H, Gerichhausen MJ, van den Briel T, Bulux J, et al. Determination of discretionary salt intake in rural Guatemala and Benin to determine the iodine fortification of salt required to control iodine deficiency disorders: studies using lithium-labeled salt. Am J Clin Nutr. 1998;68(3):636-41.
257. Allison ME, Walker V. The sodium and potassium intake of 3 to 5 year olds. Arch Dis Child. 1986;61(2):159-63.
258. Baker BA, Alexander BH, Mandel JS, Acquavella JF, Honeycutt R, Chapman P. Farm Family Exposure Study: methods and recruitment practices for a biomonitoring study of pesticide exposure. J Expo Anal Environ Epidemiol. 2005;15(6):491-9.
259. Soto-Mendez MJ, Aguilera CM, Campana-Martin L, Martin-Laguna V, Schumann K, Solomons NW, et al. Variation in hydration status within the normative range is associated with urinary biomarkers of systemic oxidative stress in Guatemalan preschool children. Am J Clin Nutr. 2015;102(4):865-72.
260. Campanozzi A, Avallone S, Barbato A, Iacone R, Russo O, De Filippo G, et al. High Sodium and Low Potassium Intake among Italian Children: Relationship with Age, Body Mass and Blood Pressure. PLoS One. 2015;10(4):e0121183-e.
261. Grases F, Rodriguez A, Costa-Bauza A, Saez-Torres C, Rodrigo D, Gomez C, et al. Factors Associated With the Lower Prevalence of Nephrolithiasis in Children Compared With Adults. Urology. 2015;86(3):587-92.
262. Manz F, Wentz A, Sichert-Hellert W. The most essential nutrient: defining the adequate intake of water. The Journal Of Pediatrics. 2002;141(4):587-92.
263. Higgins JPTG, S. Cochrane Handbook for Systematic Reviews of Interventions The Cochrane Collaboration; 2011. Available from: http://handbook.cochrane.org.
264. Goldstein SL. Oliguria in Children. In: Vincent J-L, Hall JB, editors. Encyclopedia of Intensive Care Medicine. Berlin, Heidelberg: Springer Berlin Heidelberg; 2012. p. 1616-.
265. Xu C, Guo X, Tang J, Guo X, Lu Z, Zhang J, et al. Iodine nutritional status in the adult population of Shandong Province (China) prior to salt reduction program. Eur J Nutr. 2016;55(5):1933-41.
266. Edmonds JC, McLean RM, Williams SM, Skeaff SA. Urinary iodine concentration of New Zealand adults improves with mandatory fortification of bread with iodised salt but not to predicted levels. Eur J Nutr. 2016;55(3):1201-12.
267. Shan Z, Chen L, Lian X, Liu C, Shi B, Shi L, et al. Iodine Status and Prevalence of Thyroid Disorders After Introduction of Mandatory Universal Salt Iodization for 16 Years in China: A Cross-Sectional Study in 10 Cities. Thyroid: Official Journal Of The American Thyroid Association. 2016;26(8):1125-30.
268. Johner S, Thamm M, Schmitz R, Remer T. Examination of iodine status in the German population: an example for methodological pitfalls of the current approach of iodine status assessment. Eur J Nutr. 2016;55(3):1275-82 8p.
269. Manz F, Johner SA, Wentz A, Boeing H, Remer T. Water balance throughout the adult life span in a German population. The British Journal Of Nutrition. 2012;107(11):1673-81.
270. Larsson G, Victor A. Micturition patterns in a healthy female population, studied with a frequency/volume chart. Scand J Urol Nephrol Suppl. 1988;114:53-7.
271. Wang CY, Cogswell ME, Loria CM, Chen TC, Pfeiffer CM, Swanson CA, et al. Urinary excretion of sodium, potassium, and chloride, but not iodine, varies by timing of collection in a 24-hour calibration study. J Nutr. 2013;143(8):1276-82.
272. Grimes CA, Baxter JR, Campbell KJ, Riddell LJ, Rigo M, Liem DG, et al. Cross-Sectional Study of 24-Hour Urinary Electrolyte Excretion and Associated Health Outcomes in a Convenience Sample of Australian Primary Schoolchildren: The Salt
References
~ 161 ~
and Other Nutrients in Children (SONIC) Study Protocol. JMIR Res Protoc. 2015;4(1):e7.
273. Cameron AJ, Ball K, Pearson N, Lioret S, Crawford DA, Campbell K, et al. Socioeconomic variation in diet and activity-related behaviours of Australian children and adolescents aged 2-16 years. Pediatr Obes. 2012;7(4):329-42.
274. Golley RK, Hendrie GA, McNaughton SA. Scores on the dietary guideline index for children and adolescents are associated with nutrient intake and socio-economic position but not adiposity. J Nutr. 2011;141(7):1340-7.
275. Grimes CA, Campbell KJ, Riddell LJ, Nowson CA. Is socioeconomic status associated with dietary sodium intake in Australian children? A cross-sectional study. BMJ Open. 2013;3(2):e002106.
276. Marfell-Jones M, Olds T, Stewart A, de Ridder H. International Standards for Anthropometric Assessment. Potchefstroom: International Society for the Advancement of Kinanthropometry (ISAK); 2006.
277. Cole TJ, Bellizzi MC, Flegal KM, Dietz WH. Establishing a standard definition for child overweight and obesity worldwide: international survey. BMJ (Clinical Research Ed). 2000;320(7244):1240-3.
278. Cole TJ, Flegal KM, Nicholls D, Jackson AA. Body mass index cut offs to define thinness in children and adolescents: international survey. BMJ (Clinical Research Ed). 2007;335(7612):194-.
279. Pino S, Fang SL, Braverman LE. Ammonium persulfate: a new and safe method for measuring urinary iodine by ammonium persulfate oxidation. Exp Clin Endocrinol Diabetes. 1998;106 Suppl 3:S22-7.
280. Sandell EB, Kolthoff IM. Micro determination of iodine by a catalytic method. Microchimica Acta. 1937;1(1):9-25.
281. Department of Health and Ageing, Department of Agriculture Fisheries and Forestry, Australian Food and Grocery Council. 2007 Australian National Children’s Nutrition and Physical Activity Survey User Guide. Canberra, Australia: Commonwealth Government, 2010.
282. Livingstone MBE, Robson PJ, Wallace JMW. Issues in dietary intake assessment of children and adolescents. Br J Nutr. 2004;92:S213-S22.
283. Grimes CA, Campbell KJ, Riddell LJ, Nowson CA. Sources of sodium in Australian children's diets and the effect of the application of sodium targets to food products to reduce sodium intake. Br J Nutr. 2011;105(3):468-77.
284. Mackerras DEM, Singh GR, Eastman CJ. Iodine status of Aboriginal teenagers in the Darwin region before mandatory iodine fortification of bread. Med J Aust. 2011;194(3):126-30.
285. Rahman A, Savige GS, Deacon NJ, Francis I, Chesters JE. Increased iodine deficiency in Victoria, Australia: analysis of neonatal thyroid-stimulating hormone data, 2001 to 2006. Med J Aust. 2010;193(9):503-5.
286. Uren LJ, McKenzie G, Moriarty H. Evaluation of iodine levels in the Riverina population. Aust J Rural Health. 2008;16(2):109-14 6p.
287. Charlton KE, Yeatman HR, Houweling F. Poor iodine status and knowledge related to iodine on the eve of mandatory iodine fortification in Australia. Asia Pac J Clin Nutr. 2010;19(2):250-5.
288. Yeatman H, Player C, Charlton K. Women's perceptions relating to the introduction of mandatory iodine fortification in Australia. Nutr Diet. 2010;67(1):13-7 5p.
289. Baxter JR, Riddell L, Huggins CE, Brinkman M, Giles GG, English D, et al. Iodine status in Melbourne adults in the early 1990s and 2007-08. Aust N Z J Public Health. 2011;35(5):408-11.
References
~ 162 ~
290. Zimmermann MB. Symposium on 'Geographical and geological influences on nutrition': iodine deficiency in industrialised countries. Proc Nutr Soc. 2010;69(1):133-43.
291. Australian Bureau of Statistics. 4363.0.55.001 - Australian Health Survey: Users' Guide, 2011-13 2013 [24/8/2016]. Available from: http://www.abs.gov.au/AUSSTATS/[email protected]/Lookup/4363.0.55.001Main+Features12011-13?OpenDocument.
292. Delange F. The role of iodine in brain development. Proc Nutr Soc. 2000;59(1):75-9.
293. Australian Bureau of Statistics. 6227.0 - Education and Work, Australia, May 2016 2016. Available from: http://www.abs.gov.au/AUSSTATS/[email protected]/DetailsPage/6227.0May%202016?OpenDocument.
294. Thomson CD. Selenium and iodine intakes and status in New Zealand and Australia. Br J Nutr. 2004;91(5):661-72.
295. Grimes CA, Riddell LJ, Campbell KJ, Beckford K, Baxter JR, He FJ, et al. Dietary intake and sources of sodium and potassium among Australian schoolchildren: results from the cross-sectional Salt and Other Nutrients in Children (SONIC) study. BMJ Open. 2017;7(10).
296. Australian Bureau of Statistics. Socioeconomic Indexes for Areas 2013 [12/2014]. Available from: http://www.abs.gov.au/websitedbs/censushome.nsf/home/seifa.
297. Ji X, Liu P, Sun Z, Su X, Wang W, Gao Y, et al. Intra-individual variation in urinary iodine concentration: effect of statistical correction on population distribution using seasonal three-consecutive-day spot urine in children. BMJ Open. 2016;6(2):e010217-e.
298. Rasmussen LB, Ovesen L, Bulow I, Jorgensen T, Knudsen N, Laurberg P, et al. Dietary iodine intake and urinary iodine excretion in a Danish population: effect of geography, supplements and food choice. Br J Nutr. 2002;87(1):61-9.
299. Ershow A, Skeaff S, Merkel J, Pehrsson P. Development of Databases on Iodine in Foods and Dietary Supplements. Nutrients. 2018;10(1):100.
300. Johner SA, Gunther AL, Remer T. Current trends of 24-h urinary iodine excretion in German schoolchildren and the importance of iodised salt in processed foods. Br J Nutr. 2011;106(11):1749-56.
301. Jooste PL, Weight MJ, Lombard CJ. Iodine concentration in household salt in South Africa. Bull World Health Organ. 2001;79(6):534-40.
302. Costa Leite J, Keating E, Pestana D, Cruz Fernandes V, Maia ML, Norberto S, et al. Iodine Status and Iodised Salt Consumption in Portuguese School-Aged Children: The Iogeneration Study. Nutrients. 2017;9(5).
303. Australian Bureau of Statistics. 4364.0.55.012 - Australian Health Survey: Consumption of Food Groups from the Australian Dietary Guidelines, 2011-12 2016 [updated 13/12/201727/05/2018]. Available from: http://www.abs.gov.au/AUSSTATS/[email protected]/DetailsPage/4364.0.55.0122011-12?OpenDocument.
304. Ma ZF, Skeaff SA. Thyroglobulin as a biomarker of iodine deficiency: a review. Thyroid: Official Journal Of The American Thyroid Association. 2014;24(8):1195-209.
305. Zimmermann MB, de Benoist B, Corigliano S, Jooste PL, Molinari L, Moosa K, et al. Assessment of iodine status using dried blood spot thyroglobulin: development of reference material and establishment of an international reference range in iodine-sufficient children. J Clin Endocrinol Metab. 2006;91(12):4881-7.
References
~ 163 ~
306. Simsek E, Safak A, Yavuz O, Aras S, Dogan S, Kocabay K. Sensitivity of iodinedeficiency indicators and iodine status in Turkey. Journal Of PediatricEndocrinology & Metabolism: JPEM. 2003;16(2):197-202.
307. Zimmermann MB, Aeberli I, Andersson M, Assey V, Yorg JAJ, Jooste P, et al.Thyroglobulin is a sensitive measure of both deficient and excess iodine intakes inchildren and indicates no adverse effects on thyroid function in the UIC range of100-299 μg/L: a UNICEF/ICCIDD study group report. J Clin Endocrinol Metab.2013;98(3):1271-80.
308. Vejbjerg P, Knudsen N, Perrild H, Laurberg P, Carlé A, Pedersen IB, et al.Thyroglobulin as a marker of iodine nutrition status in the general population.European Journal Of Endocrinology / European Federation Of Endocrine Societies.2009;161(3):475-81.
309. Knudsen N, Bülow I, Jørgensen T, Perrild H, Ovesen L, Laurberg P. Serum Tg--asensitive marker of thyroid abnormalities and iodine deficiency in epidemiologicalstudies. J Clin Endocrinol Metab. 2001;86(8):3599-603.
310. Rasmussen LB, Ovesen L, Bulow I, Jorgensen T, Knudsen N, Laurberg P, et al.Relations between various measures of iodine intake and thyroid volume, thyroidnodularity, and serum thyroglobulin. Am J Clin Nutr. 2002;76(5):1069-76.
311. Australian Bureau of Statistics. 1995 National Nutrition Survey Users' Guide.Canberra: Australian Bureau of Statistics, 1998.
312. Axford S, Charlton K, Yeatman H, Ma G. Poor knowledge and dietary practicesrelated to iodine in breastfeeding mothers a year after introduction of mandatoryfortification. Nutr Diet. 2012;69(2):91-4 4p.
313. Charlton KE, Yeatman H, Brock E, Lucas C, Gemming L, Goodfellow A, et al.Improvement in iodine status of pregnant Australian women 3 years afterintroduction of a mandatory iodine fortification programme. Preventive medicine.2013;57(1):26-30.
314. Condo D, Huyhn D, Anderson AJ, Skeaff S, Ryan P, Makrides M, et al. Iodine statusof pregnant women in South Australia after mandatory iodine fortification of breadand the recommendation for iodine supplementation. Matern Child Nutr.2016:e12410-n/a.
315. Samidurai AJ, Ware RS, Davies PSW, Davies PS. The influence of mandatory iodinefortification on the iodine status of Australian school children residing in an iodinesufficient region. Asia Pacific Journal of Clinical Nutrition. 2017;26(4):680-5.
316. Clifton VL, Hodyl NA, Fogarty PA, Torpy DJ, Roberts R, Nettelbeck T, et al. Theimpact of iodine supplementation and bread fortification on urinary iodineconcentrations in a mildly iodine deficient population of pregnant women in SouthAustralia. Nutrition Journal. 2013;12:32-.
317. Huynh D, Condo D, Gibson R, Muhlhausler B, Ryan P, Skeaff S, et al. Iodine status ofpostpartum women and their infants in Australia after the introduction ofmandatory iodine fortification. Br J Nutr. 2017;117(12):1656-62.
318. Iodine Global Network. Global iodine scorecard and map 2017 [updated30/5/2017; cited 9/10/2017]. Available from: http://www.ign.org/scorecard.htm.
319. World Health Organization. Salt reduction and iodine fortification strategies inpublic health: report of a joint technical meeting convened by the World HealthOrganization and The George Institute for Global Health in collaboration with theInternational Council for the Control of Iodine Deficiency Disorders GlobalNetwork, Sydney, Australia, March 2013. Geneva: World Health Organisation,2014.
~ 164 ~
320. Codling K, Chen Z, Hongmei S, Li M, Gu Y, Lu Z. China: leading the way in sustainedIDD elimination: the international council for control of iodine deficiency disorders(ICCIDD) global network. IDD Newsl. 2014;42(2):1-5.
321. Sun D, Codling K, Chang S, Zhang S, Shen H, Su X, et al. Eliminating IodineDeficiency in China: Achievements, Challenges and Global Implications. Nutrients.2017;9(4):361.
322. Public Health England. National Diet and Nutrition Survey 2016 [updated16/03/201827/05/2018]. Available from:https://www.gov.uk/government/collections/national-diet-and-nutrition-survey#history.
323. Australian Government Department of Health. Summary of Food CategoriesEngaged under the Food and Health Dialogue to date Commonwealth of Australia2013 [15/01/2015]. Available from:http://www.foodhealthdialogue.gov.au/internet/foodandhealth/publishing.nsf/Content/summary_food_categories.
324. Alexy U, Drossard C, Kersting M, Remer T. Iodine intake in the youngest: impact ofcommercial complementary food. Eur J Clin Nutr. 2009;63(11):1368-70.
325. Buyken AE, Kellerhoff Y, Hahn S, Kroke A, Remer T. Urinary C-peptide excretion infree-living healthy children is related to dietary carbohydrate intake but not to thedietary glycemic index. The Journal Of Nutrition. 2006;136(7):1828-33.
326. Griefahn B, Remer T, Blaszkewicz M, Bröde P. Long-Term stability of 6-hydroxymelatonin sulfate in 24-h urine samples stored at -20 degrees C.Endocrine. 2001;15(2):199-202.
327. Johner SA, Libuda L, Shi L, Retzlaff A, Joslowski G, Remer T. Urinary fructose: apotential biomarker for dietary fructose intake in children. Eur J Clin Nutr.2010;64(11):1365-70.
328. Johner SA, Shi L, Remer T. Higher urine volume results in additional renal iodineloss. Thyroid: Official Journal Of The American Thyroid Association.2010;20(12):1391-7.
329. Remer T, Manz F, Alexy U, Schoenau E, Wudy SA, Shi L. Long-term high urinarypotential renal acid load and low nitrogen excretion predict reduced diaphysealbone mass and bone size in children. J Clin Endocrinol Metab. 2011;96(9):2861-8.
330. Shi L, Maser-Gluth C, Remer T. Daily urinary free cortisol and cortisone excretion isassociated with urine volume in healthy children. Steroids. 2008;73(14):1446-51.
331. Shi L, Wudy SA, Buyken AE, Hartmann MF, Remer T. Body fat and animal proteinintakes are associated with adrenal androgen secretion in children. Am J Clin Nutr.2009;90(5):1321-8.
332. Shi L, Berkemeyer S, Buyken AE, Maser-Gluth C, Remer T. Glucocorticoids and bodyfat associated with renal uric acid and oxalate, but not calcium excretion, inhealthy children. Metabolism. 2010;59(1):134-9.
333. Shi L, Wudy SA, Buyken AE, Maser-Gluth C, Hartmann MF, Remer T. Prepubertalglucocorticoid status and pubertal timing. J Clin Endocrinol Metab.2011;96(6):E891-E8.
334. Shi L, Wudy SA, Maser-Gluth C, Hartmann MF, Remer T. Urine volume dependencyof specific dehydroepiandrosterone (DHEA) and cortisol metabolites in healthychildren. Steroids. 2011;76(1-2):140-4.
335. Shi L, Sánchez-Guijo A, Hartmann MF, Schönau E, Esche J, Wudy SA, et al. Higherglucocorticoid secretion in the physiological range is associated with lower bonestrength at the proximal radius in healthy children: importance of protein intakeadjustment. Journal Of Bone And Mineral Research: The Official Journal Of TheAmerican Society For Bone And Mineral Research. 2015;30(2):240-8.
References
~ 165 ~
Appendices
Appendix A: Summary of Food and Health Dialogue food reformulation targets (323)
Food Category Subcategory Reformulation Targets Timeframe for Action
Breads n/a Maximum sodium target of 400mg/100g
May 2010 - December 2013
Ready-to-eat Breakfast Cereals
n/a 15% reduction in sodium across those products with sodium levels exceeding 400mg/100g
May 2010 - December 2013
Simmer Sauces
Asian style sauces 15% reduction in sodium across simmer sauces with sodium levels exceeding 680mg/100g
January 2011 - December 2014
Indian style sauces Pasta Sauces Other (simmer-type) sauces
15% reduction in sodium across simmer sauces with sodium levels exceeding 420mg/100g
Processed meats
Bacon Ham and other cured meat products
Maximum sodium target of 1090mg/100g
January 2011 - December 2013
Emulsified luncheon meats
Maximum sodium target of 830mg/100g
Soups
Dry soup products Maximum sodium target of 290mg/100g
December 2011 - December 2014
Wet/condensed soup products
Average sodium target of 290mg/100g AND a maximum target of 300mg/100g
Savoury Pies
Wet savoury pies and pastries
10% reduction in sodium across those with sodium levels exceeding 400mg/100g March 2012 -
March 2014
Dry savoury pies and pastries
10% reduction in sodium across those with sodium levels exceeding 500mg/100g
Appendices
~ 166 ~
Food Category Subcategory Reformulation Targets Timeframe for Action
Potato/Corn/ Extruded Snacks
Cereal-based snacks
Average sodium target of 550mg/100g AND maximum target of 700mg/100g
December 2012 - December 2015
Potato chips Average sodium target of 550mg/100g AND max. target 800mg/100
Extruded snacks Average sodium target of 950mg/100g AND maximum target of 1250mg/100g
Salt and vinegar based snacks
Average sodium target of 850mg/100g AND maximum target of 1100mg/100g
Savoury crackers
Flavoured crackers (flour-based)
Maximum sodium target of 1000mg/100g OR 15% reduction in sodium towards the maximum target for products with sodium levels significantly above the agreed maximum targets
December 2012 - December 2015
Plain crackers (flour based) Flavoured rice crackers/cakes/ corncakes
Maximum sodium target of 850mg/100g OR 15% reduction in sodium towards the maximum targets for products with sodium levels significantly above the agreed maximum targets
Cheese
Cheddar and cheddar style cheeses
Maximum sodium target of 710mg/100g
March 2013 - March 2017
Low moisture mozarella cheeses
Maximum sodium target of 550mg/100g
Chilled processed cheeses
Maximum sodium target of 1270mg/100mg OR 10-15% reduction in sodium towards the maximum target for those products with sodium levels significantly above the agreed maximum target of 1270mg/100g.
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ten
egro
-B
eth
anco
urt
_20
15b
- 2
00
2
No
~ 169 ~
Stu
dy
ID
Appendices
Stu
dy
ID
Aim
(s)
Stu
dy
year
(s)
Age
ra
nge
N
N
um
ber
of
uri
ne
sam
ple
s
Par
tici
pan
t o
verl
ap w
ith
oth
er
stu
die
s
Incl
ud
ed in
fi
nal
dat
a sy
nth
esis
?
Gri
efah
n_2
001
(326
)
To d
eter
min
e w
het
her
th
e co
nce
ntr
atio
n o
f 6
-hyd
roxy
- m
elat
on
in s
ulf
ate
(6-O
HM
S)
rem
ain
s st
able
in u
rin
e sa
mp
les
sto
red
ove
r at
leas
t 1
5 y
r.
19
85
-19
87
1
99
1-1
99
3
19
97
-19
99
8
-9 y
/o
11
7
11
7
Man
z_2
002
- 1
98
5-1
98
9, 1
99
1-
19
93
M
on
ten
egro
-B
eth
anco
urt
_20
15b
- 1
99
7-1
99
9
No
To v
erif
y w
het
her
th
e p
ote
nti
al
bio
mar
ker
fru
cto
se e
xcre
tio
n a
lso
p
rovi
des
an
ad
equ
ate
esti
mat
e o
f d
ieta
ry s
uga
r in
take
in f
ree
-liv
ing
child
ren
.(327
)
19
96
-20
03
7
-10
y/o
3
76
1
14
M
on
ten
egro
-Bet
han
cou
rt_2
015
Mo
nte
neg
ro-
Bet
han
cou
rt_2
015
b
No
Joh
ner
_20
10b
(328
)
To e
xam
ine
the
imp
act
of
U-V
ol
(an
ind
ex o
f fl
uid
inta
ke)
on
th
e u
rin
ary
excr
etio
n o
f io
din
e in
24
-h
ou
r u
rin
e sa
mp
les
in a
co
ntr
olle
d
die
t ex
per
imen
t an
d in
a
lon
gitu
din
al s
amp
le o
f h
ealt
hy
free
-liv
ing
ado
lesc
ents
.
20
03
-20
08
1
3-1
8 y
/o
21
5
20
4
Mo
nte
neg
ro-B
eth
anco
urt
_201
5 A
lexy
_20
12
N
o
Joh
ner
_20
11 (3
00)
To e
xam
ine
wh
eth
er a
red
uct
ion
in
th
e u
se o
f io
dis
ed s
alt
du
rin
g fo
od
pro
cess
ing
has
aff
ecte
d t
he
iod
ine
stat
us
of
Ger
man
sc
ho
olc
hild
ren
fro
m 2
00
4-2
00
9
20
04
-9
6-1
2 y
/o
28
7
70
7
Mo
nte
neg
ro-
Bet
han
cou
rt_2
015
b
No
~ 170 ~
Joh
ner
_20
10 (3
13)
Appendices
A
im(s
) St
ud
y ye
ar(s
) A
ge
ran
ge
N
Nu
mb
er o
f u
rin
e sa
mp
les
Par
tici
pan
t o
verl
ap w
ith
oth
er
stu
die
s
Incl
ud
ed in
fi
nal
dat
a sy
nth
esis
?
Joh
ner
_20
13 (1
60)
To c
har
acte
rize
th
e cu
rren
t io
din
e su
pp
ly o
f G
erm
an p
resc
ho
ol
child
ren
in d
etai
l, in
vest
igat
e it
s d
evel
op
men
t d
uri
ng
the
last
yea
rs
and
qu
anti
fy t
he
imp
act
of
dif
fere
nt
foo
d g
rou
ps
on
iod
ine
nu
trit
ion
in t
his
age
gro
up
.
20
03
-20
10
3
-<6
y/o
2
22
3
78
Li
bu
da_
201
2 N
o
Rem
er_2
006
(25
)
To s
pe
cifi
cally
exa
min
e th
e lo
ng-
term
tre
nd
s in
iod
ine
stat
us
fro
m
19
96
to
19
99
an
d f
rom
20
00
to
2
00
3, w
e st
ud
ied
th
e 2
4-h
uri
nar
y io
din
e ex
cre
tio
n (
24
-h U
I) in
a
sam
ple
of
Ger
man
sch
oo
lch
ildre
n
wh
o w
ere
follo
wed
lon
gitu
din
ally
o
ver
the
resp
ect
ive
8-y
per
iod
.
19
96
-20
03
6
-12
y/o
4
26
1
04
6
Mo
nte
neg
ro-B
eth
anco
urt
_201
5 M
on
ten
egro
-B
eth
anco
urt
_20
15b
- 1
99
6-
20
03
No
Rem
er_2
011
(329
)
To e
xam
ine
wh
eth
er t
he
asso
ciat
ion
of
lon
g-te
rm d
ieta
ry
acid
load
an
d p
rote
in in
take
wit
h
child
ren
’s b
on
e st
atu
s ca
n b
e co
nfi
rmed
usi
ng
app
rove
d u
rin
ary
bio
mar
kers
an
d w
het
her
th
ese
die
t in
flu
ence
s m
ay b
e in
dep
end
ent
of
po
ten
tial
bo
ne
-an
abo
lic s
ex
ster
oid
s.
July
19
98
-
Jun
e19
99
6
-18
y/o
1
97
7
89
M
on
ten
egro
-Bet
han
cou
rt_2
015
Mo
nte
neg
ro-
Bet
han
cou
rt_2
015
b
No
~ 171 ~
Stu
dy
ID
Appendices
Stu
dy
ID
Aim
(s)
Stu
dy
year
(s)
Age
ra
nge
N
N
um
ber
of
uri
ne
sam
ple
s
Par
tici
pan
t o
verl
ap w
ith
oth
er
stu
die
s
Incl
ud
ed in
fi
nal
dat
a sy
nth
esis
?
To e
xam
ine
wh
eth
er u
rin
ary
free
co
rtis
ol (
UFF
), c
ort
iso
ne
(UFE
),
and
glu
coco
rtic
oid
sec
reti
on
m
arke
r ar
e af
fect
ed b
y u
rin
e vo
lum
e in
hea
lth
y ch
ildre
n (3
30)
19
90
-20
02
8
-9, 1
2-
14
y/o
2
00
2
00
M
anz_
200
2 -
19
90
-19
97
M
on
ten
egro
-B
eth
anco
urt
_20
15b
- 1
99
3-2
00
2
No
Shi_
2009
(331
)
To in
vest
igat
e w
het
her
a r
elev
ant
par
t o
f th
e va
riat
ion
in 2
4-h
AA
se
cret
ion
may
als
o b
e ex
pla
ined
b
y b
od
y co
mp
osi
tio
n a
nd
die
tary
in
take
s in
he
alth
y ch
ildre
n
19
96
-20
03
3
-12
y/o
3
82
1
87
Mo
nte
neg
ro-B
eth
anco
urt
_201
5
- 6
-12
y/o
M
on
ten
egro
-B
eth
anco
urt
_20
15b
- 6
-12
y/o
No
Shi_
2010
(332
)
To e
xam
ine
the
exte
nt
to w
hic
h
24
-ho
ur
uri
nar
y ex
cret
ion
of
calc
ium
, oxa
late
, an
d u
ric
acid
is
asso
ciat
ed w
ith
bo
dy
fat
as w
ell
as e
nd
oge
no
us
glu
coco
rtic
oid
s in
fr
ee-l
ivin
g ch
ildre
n, t
akin
g re
leva
nt
nu
trit
ion
al a
nd
aci
d-b
ase
fact
ors
into
acc
ou
nt.
19
96
-20
03
4
-5, 8
-9,
12
-14
y/o
3
00
3
00
Mo
nte
neg
ro-B
eth
anco
urt
_201
5
- 8
-9y/
o, 1
2-1
4y/
o
Mo
nte
neg
ro-
Bet
han
cou
rt_2
015
b -
8-9
y/o
M
on
ten
egro
-Bet
han
cou
rt_2
013
-
4-6
y/o
No
~ 172 ~
Shi_
2008
(316
)
Appendices
Aim
(s)
Stu
dy
year
(s)
Age
ra
nge
N
N
um
ber
of
uri
ne
sam
ple
s
Par
tici
pan
t o
verl
ap w
ith
oth
er
stu
die
s
Incl
ud
ed in
fi
nal
dat
a sy
nth
esis
?
Shi_
2011
(333
)
To e
xam
ine
the
rela
tio
nsh
ip
bet
wee
n p
rep
ub
erta
l gl
uco
cort
ico
id s
tatu
s an
d e
arly
or
late
pu
ber
tal m
arke
rs,
ind
epen
de
nt
of
adre
nar
chal
an
d
nu
trit
ion
al s
tatu
s.
19
96
-20
03
7
-10
y/o
3
76
1
11
M
on
ten
egro
-Bet
han
cou
rt_2
015
Mo
nte
neg
ro-
Bet
han
cou
rt_2
015
b
No
Shi_
2011
b (3
34)
To e
xam
ine
wh
eth
er a
dre
nal
an
dro
gen
(A
A)
met
abo
lites
may
b
e al
so a
ffec
ted
by
uri
ne
volu
me
in h
ealt
hy
child
ren
19
96
-20
03
4
-10
y/o
1
69
1
20
Mo
nte
neg
ro-B
eth
anco
urt
_201
5
- 6
-10
y/o
M
on
ten
egro
-B
eth
anco
urt
_20
15b
- 6
-10
y/o
No
Shi_
2015
(335
)
To e
xam
ine
the
asso
ciat
ion
of
uri
nar
y m
easu
res
of
glu
coco
rtic
oid
sta
tus
and
co
rtic
al
bo
ne
in h
ealt
hy
no
n-o
be
se
child
ren
, aft
er p
arti
cula
rly
con
tro
llin
g fo
r p
rote
in in
take
.
July
19
98
-
Jun
e19
99
6
-18
y/o
1
75
1
75
M
on
ten
egro
-Bet
han
cou
rt_2
015
Mo
nte
neg
ro-
Bet
han
cou
rt_2
015
b
No
~ 173 ~
Stu
dy
ID
Appendices
A
im(s
) St
ud
y ye
ar(s
) A
ge
ran
ge
N
Nu
mb
er o
f u
rin
e sa
mp
les
Par
tici
pan
t o
verl
ap w
ith
oth
er
stu
die
s
Incl
ud
ed in
fi
nal
dat
a sy
nth
esis
?
Bo
kho
f_2
010
(203
)
To a
sse
ss t
he
valid
ity
of
die
tary
p
rote
in in
take
rec
ord
ed o
n t
he
thir
d 2
4h
of
a 3
d w
eig
he
d d
ieta
ry
reco
rd a
gain
st t
he
pro
tein
inta
ke
esti
mat
ed f
rom
sim
ult
ane
ou
sly
colle
cted
24
h u
rin
e sa
mp
les.
no
t p
rovi
ded
3
-4, 7
-8,
11
-13
y/o
4
39
3
36
u
ncl
ear
No
Dim
itri
ou
_20
01 (2
04)
To in
vest
igat
e w
het
her
uri
nar
y le
pti
n m
easu
rem
ents
co
uld
be
u
sed
as
a n
on
inva
sive
bio
che
mic
al
mar
ker
to a
sses
s th
e le
pti
n s
tatu
s in
ch
ildre
n.
no
t p
rovi
ded
4
-18
y/o
1
55
1
55
u
ncl
ear
No
Ebn
er_2
002
(205
) To
an
alys
e th
e o
rigi
n o
f th
e se
x d
iffe
ren
ce in
uri
ne
osm
ola
lity
usi
ng
the
DO
NA
LD c
oh
ort
n
ot
pro
vid
ed
4-1
4.9
y/
o
49
5
49
5
un
clea
r N
o
Esch
e_20
16
(206
)
To e
xam
ine
the
asso
ciat
ion
b
etw
een
uri
nar
y ci
trat
e ex
cret
ion
an
d b
on
e st
ren
gth
as
wel
l as
lon
g-te
rm f
ract
ure
ris
k.
no
t p
rovi
ded
6
-18
y/o
2
31
8
57
u
ncl
ear
No
~ 174 ~
Stu
dy
ID
Appendices
Aim
(s)
Stu
dy
year
(s)
Age
ra
nge
N
N
um
ber
of
uri
ne
sam
ple
s
Par
tici
pan
t o
verl
ap w
ith
oth
er
stu
die
s
Incl
ud
ed in
fi
nal
dat
a sy
nth
esis
?
Kru
pp
_201
2 (2
08)
To in
vest
igat
e w
het
her
Hip
pu
ric
Aci
d m
ay a
ctu
ally
rep
rese
nt
an
app
rop
riat
e b
iom
arke
r fo
r Fr
uit
an
d V
ege
tab
le c
on
sum
pti
on
in
hea
lth
y ch
ildre
n a
nd
ad
ole
sce
nts
.
no
t p
rovi
ded
9
-10
&
13
-15
y/o
2
40
2
40
u
ncl
ear
No
Pen
czyn
ski_
2015
(207
)
To in
vest
igat
e th
e re
lati
ve v
alid
ity
of
24
-h u
rin
ary
Hip
pu
ric
A
excr
etio
n a
s a
bio
mar
ker
for
hab
itu
al f
lavo
no
id f
rom
Fru
it a
nd
V
eget
able
co
nsu
mp
tio
n b
y co
mp
aris
on
wit
h it
s in
take
es
tim
ated
fro
m m
ult
iple
3-2
4h
w
eigh
ed
die
tary
rec
ord
s in
h
ealt
hy
ado
lesc
ents
.
no
t p
rovi
ded
9
-16
y/o
2
87
1
09
8
un
clea
r N
o
Rem
er_2
010
(209
)
To c
hec
k w
he
ther
th
e b
iom
arke
r-va
lidat
ed d
iet
effe
cts
on
bo
ne
are
ind
epen
de
nt
of
the
infl
ue
nce
of
adre
nar
chal
sex
ste
roid
s, w
e al
so
exam
ined
an
d c
on
tro
lled
fo
r u
rin
ary
24
-h D
HEA
met
abo
lite
excr
etio
n r
ate
s.
no
t p
rovi
ded
6
-10
y/o
1
09
1
09
u
ncl
ear
No
~ 175 ~
Stu
dy
ID
Appendices
Appendices
~ 176 ~
Appendix C: Modified Newcastle – Ottawa Quality Assessment Scale
TOTAL OUT OF 10 STARS
Selection (maximum 2 stars)
1) Representativeness of the study sample (maximum 2 stars) a. truly representative of the source population b. somewhat representative of the source population c. selected group of users eg. small age range, single gender, small sample
size d. no description of the derivation of the cohort
Comparability (maximum 1 star)
1) Normalisation of urine collection time a. collection normalised to 24-hour period b. some other normalization applied to results c. results not normalised d. unclear as to whether results were normalised
Assessment of Outcome: 24-hour urine collection (maximum 7 stars)
1) Instructions given to participants (maximum 2 stars) a. clear instructions given to both the parents and the child participant b. instructions only given to either the parent or the participant c. unclear as to the level of instruction given
2) Start/stop time of urine collection (maximum 1 star)
a. parent or researcher recorded the start and stop time b. child reported start and stop time c. no information provided
3) Sample inclusion/exclusion criteria (maximum 4 stars)
a. time of collection b. volume of collection c. number of missed samples/spillages d. creatinine cutoff e. no description of urine exclusion/inclusion criteria
~ 177 ~
Appendices
Ap
pen
dix
D:
Fore
st p
lot
of
stu
dies
ass
essi
ng
24-h
ou
r u
rin
e vo
lum
es o
f 2
-6 y
ear
old
s
~ 178 ~
Appendices
Ap
pen
dix
E: F
ore
st p
lot
of
stu
dies
ass
essi
ng
24-h
ou
r u
rin
e vo
lum
es o
f 7
-11
year
old
s
~ 179 ~
Appendices
Ap
pen
dix
F: F
ore
st p
lot
of
stu
dies
ass
essi
ng
24-h
ou
r u
rin
e vo
lum
es o
f 12
-19
year
old
s
Appendices
~ 180 ~
Figure G.1: Correlation between UIE and bread intake in bread
consumers whose recall and urine were collected within one week of
each other (n=325)
Figure G.2: Correlation between UIE and bread intake in bread
consumers whose recall and urine were collected >1 week apart (n=61)
Appendix G: Subgroup analysis of relationship between food sources of iodine and UIE
Appendices
~ 181 ~
Figure G.3: Correlation between UIE and milk intake in milk consumers
whose recall and urine were collected within one week of each other
(n=262)
Figure G.4: Correlation between UIE and milk intake in milk consumers
whose recall and urine were collected >1 week apart (n=51)
Appendices
~ 182 ~
Figure G.5: Correlation between UIE and combined bread and milk intake
in bread and milk consumers whose recall and urine were collected
within one week of each other (n=372)
Figure G.6: Correlation between UIE and combined bread and milk intake
in bread and milk consumers whose recall and urine were collected >1
week apart (n=71)
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