DISEASE, DISABILITY, SERVICE USE AND SOCIAL SUPPORT

AMONGST COMMUNITY-DWELLING PEOPLE AGED 75 YEARS

AND OVER: THE SYDNEY OLDER PERSONS STUDY

Dorothy Marcia Edelbrock Bachelor of Arts, The University of Newcastle, 1982. Graduate Diploma in Education, The University of Newcastle, 1983. Bachelor of Arts (Hons – Class 1) The University of Newcastle, 1990. Centre for Social Change Research School of Humanities and Human Services Queensland University of Technology Brisbane, Australia.

A thesis submitted for the degree of Doctor of Philosophy of the Queensland University of Technology, 2004.

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ABSTRACT

This study investigates the characteristics of and the interrelationships between disease, disability, service use and social support in a random sample of 647 community dwellers aged 75 years and over. The two broad objectives of the study are: to examine the physical aspects and manifestations of health by investigating disease and disability and the interrelationships between these two factors, and; to examine the social aspects of health by investigating service use and social support and the interrelationships between these two factors. Given the dramatic population ageing in Australia, particularly in the very old age groups, the health, well-being and quality of life of older Australians are of paramount importance and will be well into the future. The proportion of the population with diseases and disabilities increases significantly with age. As the physical aspects of health are manifested with increasing age the social aspects of health also become increasingly important. Older adults, particularly those in advanced old age, are disproportionately high users of health and community services. Despite the high use of services in this age group, far more older adults living in the community rely on their families, friends and neighbours for social support and many older adults use a combination of formal services and informal social support. Little is known about people aged 75 years and over living in the community in Australia. In particular, significant knowledge gaps exist with regard to the relationship between disease and disability and that between service use and social support. The characteristics of social support in this group of older adults are also largely unknown.

The papers presented in this thesis are based on data collected in The Sydney

Older Persons Study (SOPS). This is a large longitudinal multidisciplinary project which began in 1991 in order to investigate the health and service use patterns of people aged 75 years and over living in the community in the Central Sydney Health Area. The initial sample consisted of two groups: first, the Australian Bureau of Statistics (ABS) selected census districts with probability proportional to size and 9271 households were door-knocked to obtain a random sub-sample of the general community (n=320, response rate 73%); second, community-living veterans and war widows residing in the Central Sydney Health Area were selected at random from a list provided by the Department of Veterans Affairs to obtain a veteran/war widow sub-sample (n=327, response rate 82%). Respondents participated in both an interview conducted by a social scientist and a medical assessment performed by a medical practitioner with experience in geriatric medicine. An informant was sought for each respondent and this informant participated in a phone interview conducted by a social scientist.

The first paper in this thesis investigates the characteristics of diseases

(neurodegenerative, systemic and psychiatric) including their prevalence and association with age. The second paper extends the first by examining the nature of the relationship between disease and disability and in particular which individual diseases and groups of diseases have the greatest impact on disability. The third paper expands

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the analysis in the second paper by focusing in greater detail on the relationship between disease and disability. The contribution of clinically-diagnosed individual diseases and groups of diseases to three different measures of disability (clinician-rated, informant-rated or proxy and self-report) is investigated here. The fourth paper examines the possibility of disease and disability being the major predictors of service use and social support. It focuses on the determinants of service use and social support using Andersen’s behavioral model. The fifth paper investigates the characteristics of social support, in particular gender differences and the socio-demographic variables associated with social support. This is an important research area because lower levels of social support have been found to predict mortality, disease and lower levels of well-being. Finally, the sixth paper links the major themes of the fourth and fifth papers by investigating the relationship between service use and social support. This paper tests Cantor’s ‘hierarchical-compensatory’ mechanism, which predicts a negative association between service use and social support, and the ‘bridging’ mechanism which predicts a positive association between these two factors. Thus it assesses the extent to which demands for service use and for social support are made together or in a compensatory fashion for respondents of equal disease and disability.

The presented work demonstrates that neurodegenerative diseases [dementia,

cognitive impairment, parkinsonism, instability (gait ataxia), immobility (gait slowing) and motivation loss/behaviour change] have the largest and most significant increases with age of all disease groups. Therefore the hypothesis made in paper one that neurodegenerative diseases will come to dominate the health care needs of older adults, particularly when combined with population ageing, is supported. Further, results of papers two and three indicate that neurodegenerative diseases result in greater levels of disability, lending credence to the finding that it is these neurodegenerative diseases that are of central importance to the future of the health care needs of older adults of advanced age. While systemic diseases play an important role in disability, the neurodegenerative diseases are under-recognised by self-report and yet are most strongly associated with severe disability. A major recommendation of this study is that assessments and diagnosis of neurodegenerative diseases be included in disability assessments.

With regard to the social aspects of health, the fourth paper finds that disease

and disability are the main predictors of service use and social support. The fifth paper highlights important gender differences in social support and also finds that lower levels of social support are associated with increased age, male gender, single marital status and lower socioeconomic status. Because it is widely accepted that social support is protective against adverse health outcomes and low levels of wellbeing, these groups of older adults are at risk of poorer health and wellbeing. Finally the sixth paper fills some knowledge gaps with regard to the relationship between service use and social support. It shows that with regard to IADL (instrumental activities of daily living) services and IADL social support, Cantor’s ‘hierarchical-compensatory’ mechanism (negative correlation) applies but with regard to medical services and both ADL

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(activities of daily living) and IADL social support the ‘bridging’ mechanism (positive correlation) is supported.

These complex interrelationships between disease, disability, service use and

social support are summarised schematically in a model. In light of significant population ageing, substantial resources in the form of medical and community services and social support from carers, family, friends and neighbours will need to be devoted to older adults with diseases, in particular neurodegenerative diseases, and to those with disabilities. Given the increasing importance of disease, disability, service use and social support in very old age, it is crucial that knowledge and understanding of these factors and their interrelationships be advanced in order to better allocate and sustain resources and to ultimately improve the health, well-being and quality of life of very old adults.

KEYWORDS Disease, Disability, Service Use, Social Support, Sydney Older Persons Study, Community-dwelling, ‘old-old’, Older adults, Neurodegenerative diseases, The Medical Model, The Social Model, The Individual-society Model, Andersen’s Behavioral Model, Cantor’s ‘Hierarchical-compensatory’ Mechanism, The ‘Bridging’ Mechanism.

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PUBLICATIONS PAPER 1 Waite LM, Broe GA, Creasey H, Grayson DA, Cullen J, O’Toole BI, Edelbrock D, Dobson M. Neurodegenerative and Other Chronic Disorders Among People Aged 75 Years and Over in the Community. Medical Journal of Australia 1997; 167: 429-432. PAPER 2 Broe GA, Jorm AF, Creasey H, Grayson DA, Edelbrock D, Waite L, Bennett H, Cullen J, Casey B. Impact of Chronic Systemic and Neurological Disorders on Disability, Depression and Life Satisfaction. International Journal of Geriatric Psychiatry 1998; 13: 667-673. PAPER 3 Waite LM, Creasey H, Grayson DA, Edelbrock D, Cullen J, Brooks WS, Casey B, Bennett HP, Broe GA. Clinical Diagnosis and Disability Among Community Dwellers Aged 75 and Over: The Sydney Older Persons Study. Australasian Journal on Ageing 2001; 20 (2): 67-72. PAPER 4 Broe GA, Grayson DA, Waite LM, Creasey H, Edelbrock D, Bennett HP, Brooks WS. Determinants of Service Use Among the Elderly: The Sydney Older Persons Study. Australasian Journal on Ageing 2002; 21 (2): 61-66. PAPER 5 Edelbrock D, Buys LR, Waite LM, Grayson DA, Broe GA, Creasey H. Characteristics of Social Support in a Community-Living Sample of Older People: The Sydney Older Persons Study. Australasian Journal on Ageing 2001; 20 (4): 173-178. PAPER 6 Edelbrock D, Waite LM, Broe GA, Grayson DA, Creasey H. The Relation Between Unpaid Support and the Use of Formal Health Services: The Sydney Older Persons Study. Australasian Journal on Ageing 2003; 22 (1): 2-8.

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DECLARATION I, Dorothy Edelbrock, the candidate for the degree of Doctor of Philosophy, certify

that the work contained in this thesis has not been previously submitted for a

degree or diploma at any other higher education institution. To the best of my

knowledge and belief, the thesis contains no material previously published or

written by another person except where due reference is made.

Signed…………………………… Date……………………………...

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TABLE OF CONTENTS ABSTRACT 2 KEYWORDS 4 PUBLICATIONS 5 TABLE OF CONTENTS 7 ACKNOWLEDGMENTS 10 CHAPTER 1. INTRODUCTION 12 1.1 A DESCRIPTION OF THE SCIENTIFIC PROBLEM INVESTIGATED 12 1.2 THE OVERALL OBJECTIVES OF THE STUDY 14 1.3 THE SPECIFIC AIMS OF THE STUDY 14 1.4 AN ACCOUNT OF THE SCIENTIFIC PROGRESS LINKING THE SCIENTIFIC PAPERS 15 CHAPTER 2. LITERATURE REVIEW 22 2.1 INTRODUCTION 22 2.2 DISEASE 23

2.2.1 Introduction to Disease 23 2.2.2 Definition of Disease 24 2.2.3 Neurodegenerative Diseases 24 2.2.4 Systemic Diseases 26 2.2.5 Psychiatric Diseases 27 2.2.6 Multiple Pathology 29

2.3 DISABILITY 30

2.3.1 Introduction to Disability 30 2.3.2 Definition of Disability 30 2.3.3 Outcome of Disability (IADL, ADL, Mobility) 31 2.3.4 Measures of Disability used in SOPS 32 2.3.4.1 The Kilsyth Disability Scales 32 2.3.4.2 Assessment of Disability and Handicap Used by the ABS and in SOPS 33

2.4 THE RELATIONSHIP BETWEEN DISEASE AND DISABILITY 34

2.4.1 Introduction 34 2.4.2 The Medical Model of Disability 35 2.4.3 The Social Construction of Disability 38 2.4.4 The Individual-Society Model 39 2.4.5 Disability and Older Adults 41

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2.5 SERVICE USE 42 2.5.1 Introduction 42 2.5.2 Definition 42 2.5.3 Determinants of Service Usage 43 2.5.4 Determinants of Service Usage: Andersen’s Behavioral Model 44

2.6 SOCIAL SUPPORT 46

2.6.1 Introduction 46 2.6.2 Definition 47 2.6.3 Types of Social Support 48 2.6.4 Social Support as a Predictor of Disease, Mortality and Lower Levels of Well-being 50 2.6.5 Major Hypotheses on the Relationship Between Social Support and Health 51 2.6.5.1 The Existence of a Relationship 52 2.6.5.2 Main or Direct Effect Hypothesis 52 2.6.5.3 Stress Buffering Hypothesis 53 2.6.5.4 Minimum Threshold Hypothesis 53 2.6.5.5 Health as an Independent Variable 53 2.6.5.6 Combination of Hypotheses 54 2.6.6 Identification of Causal Mechanisms Between Social Support and Health 54 2.6.7 How Social Support was Measured in SOPS 55 2.6.7.1 Measurement of Instrumental Support in SOPS 56 2.6.7.2 Measurement of Emotional Support in SOPS 56 2.6.7.3 Measurement of Perceived Support in SOPS 57 2.6.7.4 Measurement of Social Involvement/Participation in SOPS 58 2.6.8 Social Support 59

2.7 THE RELATIONSHIP BETWEEN SERVICE USE AND SOCIAL SUPPORT 60

2.7.1 Introduction 60 2.7.2 Cantor’s “Hierarchical compensatory” Mechanism 62 2.7.3 The “Bridging” Mechanism 64

2.8 DISCUSSION, OBJECTIVES AND AIMS 65

2.8.1 Significance of the Project Aims 65 2.9 CONCLUSION 67 CHAPTER 3. PAPER 1 NEURODEGENERATIVE AND OTHER CHRONIC DISORDERS AMONG PEOPLE AGED 75 YEARS AND OVER IN THE COMMUNITY 83 CHAPTER 4. PAPER 2 IMPACT OF CHRONIC SYSTEMIC AND NEUROLOGICAL DISORDERS ON DISABILITY, DEPRESSION AND LIFE SATISFACTION 90

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CHAPTER 5. PAPER 3 CLINICAL DIAGNOSIS AND DISABILITY AMONG COMMUNITY DWELLERS AGED 75 AND OVER: THE SYDNEY OLDER PERSONS STUDY 100 CHAPTER 6. PAPER 4 DETERMINANTS OF SERVICE USE AMONG THE ELDERLY: THE SYDNEY OLDER PERSONS STUDY 109 CHAPTER 7. PAPER 5 CHARACTERISTICS OF SOCIAL SUPPORT IN A COMMUNITY-DWELLING SAMPLE OF OLDER PEOPLE: THE SYDNEY OLDER PERSONS STUDY 118 CHAPTER 8. PAPER 6 THE RELATION BETWEEN UNPAID SUPPORT AND THE USE OF FORMAL HEALTH SERVICES: THE SYDNEY OLDER PERSONS STUDY 126 CHAPTER 9. GENERAL DISCUSSION 135

9.1 THE PRINCIPAL SIGNIFICANCE OF FINDINGS 135 9.1.1 Introduction 135 9.1.2 Disease and Disability 135 9.1.3 Service Use and Social Support 137 9.1.4 Overall Findings 138 9.1.5 Implications for Public Health, Practice and Research 140

9.2 FUTURE RESEARCH 141 9.3 CONCLUSION 142 APPENDIX 146 A1 NEUROLOGICAL SIGNS, AGING, AND THE NEURODEGENERATIVE SYNDROMES 146

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ACKNOWLEDGMENTS

First I would like to thank my principal supervisor, Dr Laurie Buys, who has provided guidance, support and understanding throughout my candidature. I know I would not have made it to submission without her assistance. She was always available when I needed to discuss any problem or to read my work and I am extremely grateful for her patience and perseverance. Thank you also to my associate supervisor, Professor Clive Bean, for your constructive comments and positiveness.

This thesis would not have been possible without the contributions of my colleagues on the SOPS team. To my former employer, chief investigator and mentor, Professor Gerald Anthony (Tony) Broe I am truly grateful. Tony has been constantly supportive and even after I ceased to be employed on SOPS has always made himself available when I needed assistance. I am also extremely grateful to Dr Louise Waite for her work as Project Manager on the second phase of SOPS, for conducting numerous medical examinations, for her significant contribution to the preparation of manuscripts and for her understanding and support in so many ways. Dr David Grayson provided invaluable statistical advice and training and I thank him for those many long telephone conversations regarding data analysis issues. I would also like to thank Dr Helen Creasey, co-investigator of SOPS, for her advice and support during the project at Concord Hospital. To Sandra Forster, Administrative Manager, I wish to convey my gratitude for encouraging words on so many occasions, for being invariably pleasant to work with on SOPS and for your practical assistance during this time and whenever I have needed help afterwards. For assistance with fieldwork, particularly interviews, thanks to Enid Sawley, Sonia Danzo and Karen Eldridge, to Jan Koh for data entry and numerous other administrative tasks and to Jill Groth who also assisted with administrative support. I would very much like to thank all co-authors of the manuscripts contained in this thesis. Those not already mentioned are Professor Anthony Jorm, Dr John Cullen, Dr Brian O’Toole, Dr William Brooks, Dr Hayley Bennett, Dr Barney Casey and Dr Matthew Dobson. Thank you to everyone who assisted with SOPS, particularly geriatricians, medical practitioners and administrative staff. On such a large project it was a privilege to experience teamwork at its best and I am grateful to everyone, in particular I think of those lengthy weekly meetings on Friday afternoons and of numerous brainstorming sessions.

Thank you to the participants of SOPS. You gave so much of your time and provided the study with invaluable information and me in particular with amazing insights, stories, cups of tea and hospitality that I will never forget.

I would like to acknowledge the assistance of the Australian Association of Gerontology in the form of an RM Gibson Scientific Research Fund grant supporting this thesis. I would also like to thank my colleague Dr Brendan Goodger for sharing his expertise and bibliography on social support. Thank you so much to all the people who have not been named personally but have nevertheless been supportive of me during this thesis.

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Finally I wish to thank my family and friends. To my husband, best friend and confidante, Dr David Scott, I wish to express my love and undying gratitude. How do you say thankyou for such unconditional love and support? Thanks for providing and caring for me financially, emotionally, practically and in so many other ways. To my other best friend, my mother, Marianne Edelbrock, again words are inadequate. Thanks mum for always being there for me, for never giving up hope and for your constant encouragement. To my sister, Karen Alexander, and her family I wish to express my appreciation – thank you so much for agreeing not to see me last Christmas so that I could work on this thesis and also for bringing baby James to Brisbane so that I could meet him for the first time when I didn’t have time to fly down to Sydney. These and so many other things, like the video of the Christmas I missed, will be treasured as long as I live. Thank you also to my friends who are too numerous to mention individually - you know who you are! I am so grateful for your caring support and prayers. In particular, Marguerite Cameron was always there to listen to my worries, concerns and problems. I am also grateful for the friendship of Anthea Addison, Robyn Forbes, Judy Langton, Lynn Cameron, Joan Kendrick, Cheryl Smith, Allison Manser, Kelley Caswell and Dr Melissa Bull.

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CHAPTER 1. INTRODUCTION 1.1 A Description of the Scientific Problem Investigated Australia is experiencing an ageing population [1] The Australian Bureau of Statistics (ABS) states that population ageing is the most dramatic of all the changes that are projected to occur in Australia’s population [2]. The ABS does not calculate projections for the over 75 age group specifically. However, the ABS reports that the population aged 85 years and over “is projected to experience the highest growth rates of all groups within the population” [2, p12]. This group is expected to more than double within 25 years from 1999. The population of older adults is growing at a rate that is two to three times more than that of the remainder of the population [3]. A decrease in death rates at the older ages has resulted in significant increases in the life expectancy of older adults [4]. The other major cause of population ageing is low fertility rates over a significant period [2]. Despite official projections indicating that Australia’s population ageing will be dramatic, a recent study has concluded that the size of the future population of older adults, particularly women and those of advanced old age, is underestimated by these official projections [5]. Therefore it is likely that the proportion of people in the most senior age brackets will be even higher than previously estimated.

Taking into account the dramatic growth in the population of older adults in Australia, particularly in the very old age groups, the health, well-being and quality of life of older Australians is of paramount importance and will be for many decades to come. The incidence and prevalence of disease increases with age as does the proportion of the population with disabilities [6]. De Looper and Bhatia state that “age, particularly advanced age, is a significant predictor of poor health and disability. Chronic diseases and conditions such as arthritis, heart disease, cancer and dementia are highly prevalent in the older population” [3, p40]. As the physical aspects of health manifest themselves with increasing age, the social aspects of health become increasingly important. Health service usage also increases with age and as older adults begin to lose their independence through disease and disability, a significant proportion will rely on family and friends for social support. De Looper and Bhatia highlight the fact that “poor health and disability also entail dependency” [3, p40]. Therefore as the population ages, the issues of disease, disability, service use and social support and their interrelationships become increasingly important. By understanding more about the health needs of this growing population we can formulate policies to accommodate population ageing. The ABS states that “Growth of this magnitude has important implications for the provision of health services” [2, p13]. The World Health Organization (WHO) defines health as “a state of complete physical, mental and social well-being and not merely the absence of disease or infirmity” [4, p1]. The Australian Institute of Health and Welfare indicates that health can mean the absence of disease, impairment, disability or handicap in everyday usage. However, in order to encompass the breadth of the WHO definition, health also includes social well-being, economic well-being, environmental well-being, life satisfaction,

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spiritual or existential well-being and other characteristics valued by humans [4]. It is the aim of this thesis to examine the health of a representative sample of 647 people aged 75 years and over in this broad sense by focusing on their disease, disability, service use and social support with the overall objective of increasing knowledge and understanding of these factors in order to improve the health, well-being and quality of life of older Australians. This objective is an important one because the Commonwealth government of Australia states that sustainable improvements in well-being is the overarching objective of economic policy in its recent Intergenerational Report [1]. This thesis will focus on both the physical aspects and manifestations of health by examining disease and disability and their interrelationship, and on the social aspects of health by examining service use and social support and the interrelationships between them.

As people advance in age there is a marked increase in the development of health-related problems, in both chronic and acute illnesses and diseases. In fact, the impact of disease is the major factor that prevents old people from remaining independent [7]. Disease can impose limitations on a person’s everyday activities in the form of disability. The importance of disability in assessing health status has been recognised by the World Health Organization through its International Classification of Functioning, Disability and Health [8]. Disability is an important predictor of health and community service utilisation. Understanding its pathenogenesis has implications for the planning of future health services.

Because disease is the major factor that prevents older adults from remaining independent, older adults may rely on assistance from both formal and informal services or support sources in order to maintain independence. Most older adults prefer to remain in their own home in the community, and it is the use of formal services and informal support networks that allow those with diseases and disabilities to do so. In the Australian Bureau of Statistics Survey of Disability, Ageing and Carers, researchers found that 67% of people aged 75 years or over need some form of assistance with housework, home maintenance, meals preparation, personal affairs or transport [9]. The majority of this assistance is provided as social support by informal carers (i.e., family, friends and neighbours) in the older person’s home [10].

Disease and disability are the primary determinants of both formal service use and informal social support among older adults [11-15]. The interrelationship between formal service use and informal social support for people of equal disease and disability is at present unclear. In addition, analysing the characteristics and level of social support received by older people is an important research agenda because lower levels of social support have been associated with mortality, poor health and lower levels of well being [16-21]. Thus, there are complex interrelationships between disease, disability, service use and social support in people aged 75 years and over, and, examining the characteristics of these four factors and the interrelationships among them is an important research agenda with implications for the planning of aged care in Australia.

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There are several strengths of the present study. First, the Sydney Older Persons Study (SOPS) is a multidisciplinary project including a wide variety of data. Second, it is based on a random sample of 647 people aged 75 years and over living in the community. Third, response rates are very good for a sample of this age. Response rates reported in the papers vary depending on which subgroup of the sample is being investigated. Basically, however, for the entire sample (n=647) the response rate for the veteran/war widow sub-sample (n=327) was 82% and the response rate for the community sub-sample (n=320) was 73%. Fourth, in addition to an interview with a social scientist and an informant interview, there was a clinical assessment of most of the participants (n=537) and therefore disease and disability were assessed by qualified medical practitioners with experience in geriatric medicine. 1.2 The Overall Objectives of the Study

The overall aim of the present study is to investigate the characteristics of and the interrelationships between disease, disability, service use and social support in a random sample of 647 community dwellers aged 75 years and over. There are two broad objectives of this study. The first is to examine the physical aspects and manifestations of health by examining disease and disability and the interrelationships between these two factors. The second is to examine the social aspects of health by examining service use and social support and the interrelationships between these two factors. Thus, this thesis explores the physical and social well-being of a representative sample of 647 over 75 year olds in order to encompass some of the breadth of the WHO definition of health outlined earlier [see section 1.1] and to ultimately contribute towards the improvement of the health, well-being and quality of life of this group of older Australians. 1.3 The Specific Aims of the Study

Within the scope of one Ph.D. thesis, it would be impossible to investigate all the interrelationships among the four factors of disease, disability, service use and social support. Therefore, this study is limited to the investigation of the characteristics of and the interrelationships between some of these concepts. In relation to the first broad objective of examining the physical aspects and manifestations of health, the specific aims of this study are first to understand the characteristics of disease in this sample of people aged 75 and over. Second, to investigate the relationship between disease and disability in the sample, in particular, what diseases cause the greatest disability and are therefore likely to reduce independence. This second specific aim is examined in papers two and three.

In relation to the social aspects of health, the third specific aim is to examine the relationship between service use and disease and between service use and disability by finding the major determinants of service use. The fourth aim is to explore the characteristics and level of social support received by those aged 75 years or over living

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in the community. The final specific aim is to investigate the interrelationship between formal service use and informal social support in this age group. 1.4 An Account of the Scientific Progress Linking the Scientific Papers

The first paper [22] investigates the prevalence of various clinically diagnosed diseases. It examines the disease patterns in an “old-old” population and the impact of age on disease prevalence. Particular emphasis was placed on the prevalence of neurodegenerative disorders (i.e. gait ataxia, visual impairment, cognitive impairment, gait slowing, dementia and Parkinson’s disease) and their association with systemic (i.e. arthritis, heart disease, obesity, stroke, chronic lung disease, other systemic diseases) and vascular diseases. The hypothesis that the neurodegenerative disorders will come to dominate the health care needs of old people was accepted. This paper ascertained that the increase in comorbidities in the older population arises from an age-related increase in neurodegenerative disorders.

The second paper [23] extends the first paper by asking the question: if disease imposes limitations on an old person’s everyday activities then what is the nature of the relationship between disease and disability? In particular, which individual diseases and which groups of diseases have the greatest effect on disability (as well as depression and life satisfaction)? In addition, this paper investigates whether or not the effects of diseases on depression and life satisfaction are mediated by disability. That is, do chronic disorders cause disability that in turn leads to increased depression and reduced life satisfaction? This paper found that this was indeed the case and also that gait slowing, heart disease and chronic lung disease had the greatest impact on disability.

The third paper [24] expands on the analysis of the second paper by again considering the relationship between disease and disability but in greater detail. In this paper, three different measures of disability are compared, namely clinician-rated, informant-rated or proxy and self-report Australian Bureau of Statistics (ABS) scale. The contribution of clinically-diagnosed individual diseases and groups of diseases to these three different measures of disability is considered. In the second paper [23] disability was only measured by clinician rating. Thus the third paper [24] allows for an examination of whether or not the contribution of disease to disability is more accurately assessed when information about disability is obtained by clinician, proxy or self-report. This paper confirmed the hypothesis that, while the systemic diseases play an important role in disability, it is the neurodegenerative diseases and syndromes that are under-recognised by self-report and are most strongly associated with severe disability. The findings of this paper support the hypothesis that neurodegenerative diagnoses result in greater levels of disability and they are therefore the most likely to result in institutionalisation. It is recommended that assessments and diagnosis of neurodegenerative diseases should be included in disability assessments.

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The fourth paper [25] examines the predictors of formal/paid service use (i.e. community services and medical services) and of informal/unpaid service use or social support. This line of inquiry was established by the third paper [24] which identifies disability as an important predictor of health and community service utilisation and states that understanding the pathenogenesis of disability has implications for planning of future health services. The authors of paper four suspected that the major predictors of service use or support sources would turn out to be disease and disability and not other socio-demographic variables that may enable respondents to have greater service access (i.e. enabling factors) or may predispose respondents to the need for greater service use (i.e. predisposing factors). The theoretical basis of this paper is a behavioural model [26] whereby predictors of usage are categorised as needs (health status), enablers (“barriers to care”, e.g. low income) and predispositions (more “personal attributes that may predispose individuals to seek care”) [27, p53]. This paper confirmed that disability and disease are the major determinants of service use. With disease and disability controlled for, enabling and predisposing variables did not significantly predict additional medical service use or social support, but did predict small additional variation in some community service use.

The fifth paper [28] focuses on the characteristics and level of various types (i.e. instrumental, emotional, perceived and social involvement) of social support. The rationale for this paper builds on the finding that disease is the major factor that prevents older adults from remaining independent [7]. As a result people aged 75 years and over may rely on assistance from both informal and formal support sources in order to maintain independence. Analysing the characteristics and level of social support is an important research agenda because the majority of this assistance is provided by informal carers (i.e. family, friends, neighbours) in the older adult’s home. There is very little, if any, information on the nature of social support that focuses on people over the age of 75 years in Australia. Examining the nature and level of social support is also critical because lower levels of social support have been associated with mortality, disease and lower levels of well-being [16, 21, 29-41]. More specifically, this paper focuses on the differences in levels of social support between men and women and on the socio-demographic variables (i.e. gender, age, marital status and socio-economic status (i.e. education, occupation and income)) that are associated with social support. It was found that lower levels of social support are associated with a range of socio-demographic variables including increased age, male gender, single marital status and lower socio-economic status.

The final paper [42] relates the main factor examined by paper four (service use) to the main factor examined by paper five (social support). This paper tests Cantor’s ‘hierarchical compensatory’ mechanism [43] which predicts that the demands on formal services increase with the unavailability of social support, resulting in a negative association between formal service use and informal social support. The ‘bridging’ mechanism suggested by other researchers [44-47] is also tested. This is a mechanism where social networks not only provide direct assistance, but also bring respondents into contact with community and medical services resulting in a positive association between service use and social support. This paper examines which services and social

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supports are used by whom, and to what extent formal service use and informal social support demands are made together or in a complementary manner, for respondents of equal disease and disability. In addition, twenty exploratory socio-demographic variables are investigated in order to ascertain which ones predict more or less formal medical and community service use and more or less social support. Using a combination of detailed service use data and clinical assessment it was identified, among participants of equal disease and disability, that community IADL (instrumental activities of daily living) services and unpaid IADL social support operate in a compensatory fashion, with participants utilising either one or the other. In contrast, higher users of medical services were greater users of social support, thereby providing support for the bridging hypothesis. It was also found that it is disability associated with disease that predicts service utilisation.

Together these six papers indicate that disease, disability, service use and social

support form complex interrelationships. In the context of an ageing society that will result in greater numbers and proportions of older adults, this thesis provides increased knowledge and understanding of these four factors and their interrelationships. Disease and associated disabilities will create greater demand for medical and community services and for social support from informal social networks in an ageing society. Although further research is required, the results presented in this thesis will assist to adequately and efficiently plan aged care in the twenty-first century.

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Longitudinal Study of Hospital, Residential and Community Service Use by Older People Living in Dubbo, NSW. Sydney: Office on Ageing, Social Policy Directorate.

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Utilization: Physician and Hospital Utilization. In Ory M, Bond K, eds. Aging and

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Health Care: Social Science and Policy Perspectives. New York: Routledge, 1989, 81-98.

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16. Berkman LF, Glass T, Brissette I, Seeman TE. 2000. From Social Integration to

Health: Durkheim in the New Millenium. Paper retrieved May 11, 2000 on-line on the World Wide Web:

http://www.msoc-mrc.gla.ac.uk/SocialScienceMedicine/WorkshopB/BERKMAN-.pdf 17. Wilkinson R, Marmot M. 1998. Social Determinants of Health: The Solid Facts.

Geneva: WHO. 18. Schwarzer R, Leppin A. Possible Impact of Social Ties and Support on Morbidity

and Mortality. In Veiel HOF, Baumann U, eds. The Meaning and Measurement of Social Support. New York: Hemisphere, 1992, 65-83.

19. Bowling A. Social Support and Social Networks: Their Relationship to the

Successful and Unsuccessful Survival of Elderly People in the Community. An Analysis of Concepts and a Review of the Evidence. Family Practice 1991; 8 (1): 68-83.

20. House JS, Landis KR, Umberson D. Social Relationships and Health. Science

1988; 241: 540-545. 21. Gibson D, Mugford S. Expressive Relations and Social Support. In Kendig HL. ed.

Ageing and Families: A Support Networks Perspective. Sydney: Allen and Unwin, 1986, 63-84.

22. Waite LM, Broe GA, Creasey H, Grayson DA, Cullen J, O’Toole BI, Edelbrock D,

Dobson M. Neurodegenerative and Other Chronic Disorders Among People Aged 75 Years and Over in the Community. Medical Journal of Australia 1997; 167: 429-432.

23. Broe GA, Jorm AF, Creasey H, Grayson DA, Edelbrock D, Waite L, Bennett H,

Cullen J, Casey B. Impact of Chronic Systemic and Neurological Disorders on Disability, Depression and Life Satisfaction. International Journal of Geriatric Psychiatry 1998; 13: 667-673.

24. Waite LM, Creasey H, Grayson DA, Edelbrock D, Cullen J, Brooks WS, Casey B,

Bennett HP, Broe GA. Clinical Diagnosis and Disability Among Community Dwellers Aged 75 and Over: The Sydney Older Persons Study. Australasian Journal on Ageing 2001; 20 (2): 67-72.

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25. Broe GA, Grayson DA, Waite LM, Creasey H, Edelbrock D, Bennett HP, Brooks WS. Determinants of Service Use Among the Elderly: The Sydney Older Persons Study. Australasian Journal on Ageing 2002; 21 (2): 61-66.

26. Andersen RM. 1968. A Behavioral Model of Families’ Use of Health Services.

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M, Bond K, eds. Aging and Health Care: Social Science and Policy Perspectives. New York: Routledge, 1989, 52-77.

28. Edelbrock D, Buys LR, Waite LM, Grayson DA, Broe GA, Creasey H.

Characteristics of Social Support in a Community-Living Sample of Older People: The Sydney Older Persons Study. Australasian Journal on Ageing 2001; 20 (4): 173-178.

29. Cassel J. The Contribution of the Social Environment to Host Resistance.

American Journal of Epidemiology 1976; 104 (2): 107-123. 30. Cobb S. Social Support as a Moderator of Life Stress. Psychosomatic Medicine

1976; 38 (5): 300-314. 31. Kaplan BH, Cassel J, Gore S. Social Support and Health. Medical Care 1977; 15

(5, supplement): 47-58. 32. Berkman LF, Syme SL. Social Networks, Host Resistance and Mortality: A Nine-

year Follow-up Study of Alameda County Residents. American Journal of Epidemiology 1979; 109: 186-204.

33. Blazer DG. Social Support and Mortality in an Elderly Community Population.

American Journal of Epidemiology 1982; 115: 686-694. 34. Friedman HS, DiMatteo MR, eds. Interpersonal Issues in Health Care. New York:

Academic Press, 1982, 35. House JS, Robbins C, Metzner HL. The Association of Social Relationships and

Activities with Mortality: Prospective Evidence from the Tecumseh Community Health Study. American Journal of Epidemiology 1982; 116: 123-140.

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Heyden S, Tibblin G, Gehlbach SH. The Epidemiologic Evidence for a Relationship Between Social Support and Health. American Journal of Epidemiology 1983; 117 (5): 521-537.

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Physical Disease. Health Psychology 1988; 7 (3): 269-297.

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38. House JS, Landis KR, Umberson D. Social Relationships and Health. Science

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Medicine 1995; 57: 245-254. 41. Wilkinson R, Marmot M. 1998. Social Determinants of Health: The Solid Facts.

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Handbook of Aging and the Social Sciences. New York: Van Nostrand Reinhard, 1976, 415-449.

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CHAPTER 2. LITERATURE REVIEW 2.1 INTRODUCTION Disease, disability, service use and social support are each significant issues for older adults. In support of the publications that make up this thesis, this chapter reviews literature on each of these factors as well as some of the interrelationships between them. With regard to disease and disability, the physical aspects of health, both increase with age and are therefore most prevalent in very old adults such as those who participated in SOPS. The major causes of disease burden amongst Australians aged 65 years and over are ischaemic heart disease and stroke, followed by dementias [1-2]. Cognitive impairment in the form of Alzheimer’s disease, dementia and other neurodegenerative diseases is prevalent amongst older adults and a leading cause of disability [3]. Disability often results in an inability to remain independent at older ages and if older adults wish to remain in their own homes, as most do, then they often become increasingly reliant upon assistance from both formal services and their informal social networks. Further research is required to provide information on the nature of the relationship between disease and disability amongst very old adults. It is one of the aims of the present study to ascertain which diseases contribute most to disability and this study hypothesises that the neurodegenerative diseases will be most strongly associated with severe disability in this age group. There is an escalating interest in the role of social factors in determining health status because it is increasingly apparent that they play a larger than expected part [4]. Social isolation is associated with mortality and there is evidence that strong supportive social networks improve health status [5]. In a recent study the extent of informal social support received by older adults was most strongly related to need factors defined as the number of chronic conditions and levels of functional impairment. Thus social support was found to be strongly associated with disease and disability. Results from Penning’s study indicate that both informal social support and formal service use are directly and positively related to health [6]. The present study also found that disease and disability are the major determinants of service use [7]. Therefore there are complex interrelationships between disease, disability, service use and social support. At present little is known about the relationship between service use and social support and it is an aim of this study to further illuminate the nature of this relationship.

This literature review is divided into six main sections. The first three sections deal with the physical aspects of health and the last three sections are concerned with the social aspects of health. In the first two sections disease and disability are discussed separately and then in the third section the relationship between disease and disability is highlighted. Similarly, in the last three sections service use and social support are first introduced separately and then the relationship between service use and social support is discussed. Finally, this literature review contains a discussion of the significance of the project objectives and aims. Although the literature cited generally has relevance for all the publications in this thesis, certain sections of the

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review pertain more strongly to particular papers. The first section on disease relates mostly to paper one and the third section on the relationship between disease and disability relates more heavily to papers two and three. The fourth section on service use is most relevant to paper four and the section on social support to paper five. Finally, the section on the relationship between service use and social support relates to paper six. 2.2 DISEASE 2.2.1 Introduction to Disease Population ageing is a result of both increasing life expectancy and decreasing fertility rates. Throughout the twentieth century life expectancy has increased and at present most Australians can expect to live for eighty years on average [8]. However, apart from accidental death, most Australians will die from a disease and this fact alone indicates that the study of disease and an understanding of the nature and cause of various diseases is an important research agenda. Diseases of the circulatory system, cancers and diseases of the respiratory system are the main causes of death for both women and men aged 65 and over in Australia. Amongst people in this age group, these three types of disease account for over three-quarters of all deaths [8]. In the first half of the twentieth century increases in life expectancy were largely due to a rapid decline in maternal, perinatal and infant mortality mainly because of improved control of infectious diseases associated with childhood and early adulthood [9]. However, more recently there have been significant increases in life expectancy due to a decline in death rates among older Australians. This decline in death rates is especially true for diseases such as coronary heart disease and stroke for which mortality rates have fallen by almost seventy per cent since the late 1960s [8]. The continuing trend of more rapidly declining mortality rates since the 1970s is mainly due to falls in mortality from heart attacks, lung cancer and stroke. This decline in mortality rates has coincided with improvements in the treatment of cardiovascular disease, better control of hypertension, dietary changes and a decrease in tobacco smoking [9]. These trends have led to population ageing and they have important consequences for patterns of health, disease and disability in the community. For example, some of the issues raised are the preventability of various diseases, the risk factors for disease and the amount of time that older Australians will spend unable to live independently because of disability. This section on disease begins by defining disease and then discusses the various categories of disease used in the study. In SOPS, disease was divided into three categories, namely: neurodegenerative disease, systemic disease and psychiatric disease. Diseases in older adults are typically categorised in this way with neurodegenerative diseases or disorders of the brain forming an increasingly important category of disease in geriatric medicine. Some of these neurodegenerative diseases are incorporated in the broad category of dementia, including Alzheimer’s disease and

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Parkinsonism. Systemic diseases are disorders of the body as a whole or a part of the body and they include diseases such as heart disease, lung disease and bone and joint disease. Finally, psychiatric diseases are mental disorders such as depression and anxiety. Each of these three categories of disease will be considered in turn and this section will highlight their definition, a description of the diseases, outcomes of the diseases and specific issues related to the disease category. 2.2.2 Definition of Disease The definition of disease is subject to much debate because disease is extremely hard to define. The term encompasses such a wide variety of illnesses and conditions which affect the body and mind in so many different ways. This study adopts the definition of disease from Stedman’s medical dictionary as “Morbus; illness; sickness; an interruption, cessation, or disorder of body functions, systems, or organs.” [10, p444]. 2.2.3 Neurodegenerative Diseases Neurodegenerative diseases are defined as hereditary and sporadic conditions which are characterised by progressive nervous system dysfunction. These disorders are often associated with atrophy of the affected central or peripheral nervous system structures [11]. Population ageing has resulted in an unprecedented increase in the survival of people in developed countries beyond the age of 80 years. This increasing life expectancy is largely due to the success of public health interventions for the chronic age-related systemic diseases such as heart disease, stroke and cigarette-related lung disease and cancers [12]. The incidence of and mortality from these systemic diseases has been reduced by modification of risk factors such as diet, exercise and smoking [13]. In contrast to systemic diseases, mortality from neurodegenerative diseases is rising [14]. Neurodegenerative diseases increase in prevalence with advanced age [12] and the twenty-first century is predicted to be the “age of neurodegenerative disorders” [12, p57]. These diseases have poorly understood causes and age is often the only known risk factor [13]. The emerging new ‘epidemic’ which will dominate public health costs in Australia in the first part of the twenty-first century is an epidemic of the age-related neurodegenerative diseases [12]. Therefore, understanding the characteristics and causes of neurodegenerative diseases is crucial. Prolonged chronic disability is increasing amongst Australia’s aged population [8, 12]. One of the reasons for increasing disability in old age may be the neurological disorders that are not able to be prevented or modified at present but that are also not rapidly fatal [15]. Broe and Creasey state that “the challenge facing epidemiologic and gerontological research over the next decades is to seek new and modifiable risk factors for the neurodegenerative diseases and to prevent or delay these diseases in order to give a better quality of life to the increasing numbers of the ‘oldest-old’ in our community” [12, p57].

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Possibly the most well-known neurodegenerative diseases are encompassed in the term dementia and within this broad group of diseases the most commonly recognised is probably Alzheimer’s disease. However, dementia is also related to vascular disease, frontal lobe dementia, diffuse Lewy body dementia, AIDS-related dementia, Pick’s disease, progressive supra-nuclear palsy, alcohol-related dementia, Huntington’s disease, Parkinson’s disease and Down’s syndrome [8]. In SOPS only those neurodegenerative disorders most relevant to advanced old age were selected for study. The nature of neurodegenerative diseases is extremely complex and their causes and risk factors are not well understood. Broe and Creasey hypothesise that certain syndromes exist in advanced old age that lead to neurodegenerative diseases. The clinical syndrome of ‘brain ageing’ as seen in the oldest-old consists of memory impairment, cognitive slowing, motor slowing, a flexed posture and a slowed, unsteady gait. Broe and Creasey hypothesise that most of what was previously attributed to ‘brain ageing’ is actually due to the summation of early manifestations of the pathological processes leading to the neurodegenerative diseases of Alzheimer’s disease, Parkinson’s disease and gait ataxia due to mid-line cerebellar degeneration [12]. In another paper written by Waite, Edelbrock and others the independent contribution of age and disease to various neurological signs often claimed to be associated with increasing age is examined and it was found that “it is not aging to which many neurological signs should be attributed, but rather to the neurodegenerative syndromes that accompany aging” [16, p498 – see Appendix 1]. With these syndromes and signs in mind, the neurodegenerative disorders examined in SOPS were: instability or gait ataxia, immobility or gait slowing, cognitive impairment, motivation loss/behaviour change, dementia, parkinsonism, visual loss, and there was also a category for “other” neurodegenerative disorders. These neurodegenerative diagnoses and all other diagnoses made in SOPS were undertaken by clinicians with experience in geriatric medicine, after detailed history-taking and physical examination.

When people have a neurodegenerative disease their risk of developing the geriatric syndromes of confusion, incontinence and immobility with falls is increased. The risk of adverse drug reaction and prolonged complicated hospitalisation is also escalated and increasing dependency and institutionalisation are the common outcomes [12]. Falls result in the largest proportion of injury-related deaths and hospitalisation in older adults aged 65 years and over [17]. These deaths are largely due to complications that develop after the fall. The most common serious injury due to falls is fractures, with hip fractures being the most pertinent with regard to serious impairment and mortality [9]. In older adults hip fracture is associated with declining health status and long-term disability [2]. More women than men die due to falls and about one third of community-dwelling older adults have falls every year [17]. However, not all of these falls are linked to neurodegenerative diseases, with post-menopausal osteoporosis being a major risk factor for hospitalisation [9]. Most falls do not result in hospitalisation [17]. It is possible that many falls due to neurodegenerative diseases go unnoticed unless they require hospitalisation and that hospitalisation may be more likely if the older adult suffers from multiple pathology such as a combination of dementia and arthritis.

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Cognitive impairment increases exponentially with age [18-19]. With regard to older adults in Australia, dementia is the major cause of years lost due to disability (YLD) or disability burden [20]. The progressive loss of memory and other cognitive functions are the major symptoms of dementia and Alzheimer’s disease [9]. People who suffer from dementia generally lose their independence and dignity along with their mental capacity [18]. Parkinson’s disease involves losing motor skills and affects cognition, behaviour and mood. It is a neurological disease that is both progressive and incurable [9].

Dementia in particular is a significant health problem for older adults. Approximately half of the individuals diagnosed with dementia live in the community. However, as cognitive loss becomes more severe older adults with dementia will increasingly tend to use residential care. Older adults with dementia will experience memory impairment, increasing difficulties with everyday tasks, personality changes and later on they will progress to being incapable of acting independently [8]. Jorm et al. combined information from 22 studies world-wide and found that the relationship between prevalence of dementia and age is consistent and that prevalence rates double every 5.1 years up to about 95 years of age [21]. Kokmen et al. found that, with advancing age, there is a sharp increase in the incidence and prevalence of dementia [22]. There are also gender differences in the prevalence of dementia with more men developing multi-infarct dementia and more women developing Alzheimer’s disease [21]. By 2041 the population of people with dementia will have increased three and a half times in Australia whereas the total population will only increase by 40%. Dementia and other neurodegenerative diseases are very disabling and they result in enormous and increasing costs to the health system [3]. For these reasons it is important to consider the possibility of the prevention of dementia. Jorm claims that eliminating dementing diseases is unlikely in the near future but that postponing dementia is a realistic possibility. Postponement and even prevention of dementia may be possible through medication, decreasing occupational risk factors such as electromagnetic fields and through decreasing medical risk factors such as head trauma [23].

2.2.4 Systemic Diseases Systemic means “pertaining to or affecting the body as a whole” [24]. Therefore, systemic diseases are diseases affect the entire body. The most common systemic disease is cardiovascular disease, which includes all diseases of the heart and circulatory system. These result in 44.4% of deaths from all causes among Australians. Within the category of cardiovascular disease, coronary heart disease was responsible for 25.5% of deaths from all causes, stroke caused 9.7% and peripheral vascular disease caused 2.7% of all deaths [25]. Seventy four per cent of all deaths from stroke were in people aged 75 and over. Another major systemic disease is cancer, which is second only to cardiovascular disease as a cause of death in Australia, with 27% of male deaths and 24% of female deaths being attributable to cancer [25]. In 1999 cancer caused 28% of all deaths in Australia. Cancer is defined as “a range of diseases in which abnormal cells multiply and spread out of control” and its incidence increases

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with age [9]. The major types of cancer are colorectal or bowel cancer, lung cancer, melanoma and other skin cancers, breast cancer, cervical cancer and prostate cancer. Other systemic diseases include bone and joint disease, including arthritis, visual loss or blindness and obesity. The systemic diseases examined in SOPS were: heart disease, chronic lung disease, bone and joint disease, stroke, peripheral vascular disease, obesity and there was also a category for “other” systemic diseases. It is difficult to describe the experience of older adults who suffer from systemic disease because the term systemic disease encompasses such a wide range of different conditions with different outcomes. For example, heart attacks and strokes can be and often are rapidly fatal. However, many older adults recover from a heart attack and/or heart surgery to live fairly normal lives. A broader range of sufferers of coronary heart disease is increasingly being offered complex interventions like coronary artery bypass surgery and angioplasty [9]. Death rates from coronary heart disease have been significantly reduced due to advances in the treatment and management of the disease. On the other hand, non-fatal stroke is the major cause of long-term disability in adults [9]. A stroke frequently damages the sections of the brain that are responsible for speech and mobility. Other systemic diseases that can be very disabling are arthritis and blindness. Cancer has varying outcomes ranging from death to complete recovery and many cancers require intensive treatment ranging from surgery to chemotherapy and radiation. Trends in mortality from systemic diseases in Australia show an unparalleled reduction in mortality from cardiovascular disease in the last three decades. The reduction in cardiovascular mortality has been more than 50% for males, with a similar pattern occurring for females. The proportion of deaths attributable to cancer, however, has increased [9]. There has also been a fall in rates of death from respiratory diseases. The decline in mortality rates from cardiovascular and respiratory diseases since the late 1960s has had a major impact on Australia’s total mortality profile [25] and has led to increases in the proportion of older people in the Australian population [9]. The major risk factors for systemic diseases, especially cardiovascular disease, are: nutritional status, cholesterol, blood pressure, smoking, excess weight for height, alcohol, physical activity and multiple risk factors which normally implies a combination of high blood pressure, high blood cholesterol and cigarette smoking [25]. Kannel emphasises the importance of modifiable risk factors such as weight control, exercise and avoiding alcohol, salt and fat in the prevention of hypertension and cardiovascular disease [26].

2.2.5 Psychiatric Diseases

Psychiatry is defined as “a branch of medicine concerned with the diagnosis, treatment and prevention of mental illness” [24]. Therefore, psychiatric diseases are mental illnesses or disorders. The MeSH definition of mental disorders is

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“psychiatric illness or diseases manifested by breakdowns in the adaptational process expressed primarily as abnormalities of thought, feeling and behaviour producing either distress or impairment of function [27]. The AIHW categorises mental disorders other than dementia into three categories. The first category is affective disorders such as depression, bipolar disorder and dysthymia, the second is anxiety disorders and the third is substance use disorders [8]. There are significant problems with regard to reliability of available data on mental disorders amongst older adults [28]. Generally older adults are happier and report fewer worries than younger people [29-30]. Based on data from the 1997 ABS Survey of Mental Health and Wellbeing, it is estimated that, over a period of one year, affective disorders affect slightly less than 2% of older adults compared with 5% to 7% of younger age groups [31]. However, there are problems with the diagnosis of depression as it is often misinterpreted as a part of the ageing process. It is likely that prevalence figures for older adults are somewhat understated [18, 28]. As is the case with affective disorders, the reported prevalence of anxiety disorders at 5% and substance abuse disorders at 1% in older adults is also lower than for other age groups. Psychiatric diseases examined in SOPS were: depression, chronic anxiety state, personality disorder and there was also a category for “other” psychiatric diseases. Neurodegenerative diseases are considered as a separate category. This approach is similar to that taken in the study on the burden of disease and injury in Australia by Mathers et al. which also does not include dementias in the category of mental disorders [2].

One indicator that psychiatric diseases are a problem for older adults, particularly males, is the fact that the second highest risk group for suicide is males aged 75 years and over [18]. Suicide and attempted suicide are often used as proxy indicators of the extent of mental illness in a population. This is because mental disorder and specifically depression are major risk factors for suicide [9]. Suicide is an important cause of death in Australia and many more people attempt suicide than actually succeed. Steenkamp and Harrison indicate that over 2,500 people die due to suicide each year in Australia and in the financial year 1997/98 there were 25,120 episodes of hospitalised self-harm [32]. Therefore about ten times more people are admitted to hospital because of intentional self-injury than actually die due to suicide. Despite the fact that three to four times more men commit suicide than women, more women report affective disorders than men [8-9, 32]. The suicide rate amongst older men increases with age and it peaks at a rate of 39.8 per 100,000 at age 85 years and over. In the case of older women, the rate of suicide peaks at ages 75 to 79 years of age at a rate of 8.2 per 100,000 [8]. The AIHW states that “older men in particular are being targeted for prevention strategies to reduce depression such as may follow retirement or the loss of a partner” [8, p37]. In adult populations, depression is considered to have the greatest prevalence of all mental disorders. However, there are wide variations in estimates of depression in the population and they depend upon the samples, methods and measures used. Generally, self-report produces higher and more consistent estimates of depression than estimates based on psychiatric diagnosis. In populations of older adults by contrast, estimates of depression are not at all consistent, ranging from 38 per cent of

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those aged 65 and over to 3 per cent in self-report studies [33]. Blazer et al. 1987 suggest that diagnostic criteria such as DSM-III, or its revisions, “do not capture most depressed older adults living in community populations” [34, p119]. Amongst older adults it is common for depression to go unrecognised [19]. The Centre for Epidemiologic Studies Depression Scale (CES-D) was used to measure depression in SOPS [35]. It was developed by the National Institute of Mental Health to measure current self-reported depressive symptoms in the general population [33]. The CES-D has 20 items on a four-point frequency scale that is scored from 0 to 60 [36]. Depression was also measured by clinician diagnosis within the medical examination included in SOPS. The experience and outcome of psychiatric diseases varies widely. Depression often results in changes in mood, a sense of hopelessness and may result in loss of function. As indicated above, at the extreme, depression and other mental disorders may result in suicide or attempted suicide. Most suicides amongst older adult males have been linked to unrecognised or untreated depression [18]. Mental illness can culminate in complete breakdown and generally results in abnormalities of thought, feeling and behaviour. Anxiety can be extremely distressing and may manifest itself as paranoia. Less common psychiatric diseases such as schizophrenia involve symptoms such as psychosis and delusions. The effect of psychiatric diseases on ability to function and performance of everyday activities also varies widely. Severe forms of psychiatric disease can be extremely disabling. A number of psychological symptoms, including depression, are often experienced by people with one or more chronic illnesses. Several conditions like cancer, stroke and other neurological disorders, thyroid disorders, diabetes and arthritis have been found to increase the risk of depressive symptoms either as a side effect of drug treatment or because of their direct hormonal or neuroendocrine effects. Other factors associated with chronic illness may also contribute to an increased risk of depressive symptoms, such as fear, uncertainty, negative body image, loss of self-esteem and sense of identity and effects on employment status and interpersonal relationships [37]. 2.2.6 Multiple Pathology Amongst older adults, ill health is generally characterised by multiple, coexistent diseases or syndromes rather than the simple presence of one disease or syndrome [16 – see Appendix 1]. Cullen et al. state that “multiple coincident physical illnesses, psychiatric disturbances and cognitive impairments are common in the elderly” [38, p411]. The Commonwealth Department of Health and Aged Care also acknowledges that it is common for more than one mental disorder to co-exist and that this adds to the burden of disorder [19]. However, interrelationships between various disorders, particularly between neurodegenerative disorders, are poorly understood. It is the aim of the first paper in this thesis to examine disease patterns in the older population and particularly to examine the relationships of neurodegenerative disorders with each other

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and with vascular diseases and risk factors, thus taking into account the multiple pathology characteristic of the aged population [13]. 2.3 DISABILITY 2.3.1 Introduction to Disability

The older individuals become, the more likely they are to suffer from some form of disability [8]. Disability is a broad term and it is important to recognise that disability varies greatly in terms of both its level and outcome. Disease may or may not result in some form of disability. For example, an older adult may be visually impaired but if they use glasses they may function normally in their environment and hence not be disabled at all. On the other hand severe visual impairment or blindness may result in severe loss of ability to function normally in one’s environment and therefore be very disabling. If function is severely limited by, for example, arthritis or blindness, the use of an aid may be necessary and this aid may improve function to varying degrees. However, in some cases an older adult may require the assistance of another person in order to be able to perform an everyday task such as walking or eating a meal. With regard to service use and social support it is not so much the presence of disease that is important but rather whether or not this disease prevents an individual from functioning in their environment such as at work or in the home. The inability to perform everyday tasks may profoundly affect the quality of life of an individual. This section first discusses definitions of disability and second outlines the outcomes of disability assessed in SOPS. Third, this section introduces the measures of disability used in SOPS and, finally, the characteristics of disability in Australia are discussed briefly. 2.3.2 Definition of Disability The concept of disability is as difficult to define as that of disease. There is a variety of terms for disability and the levels and consequences of disability. Many of these terms are used inconsistently in the community and in academic research on disability, so it is important to define them clearly. The major terms used are: “impairment”, “disability” and “handicap” or “core activity restriction”. Other terms frequently used are “limitation” and “loss of function”.

According to the World Health Organization’s International Classification of

Impairments, Disabilities, and Handicaps (ICIDH), which was used at the time SOPS began (1991), disease or disorder or loss may lead to impairment, which in turn may lead to disability, which in turn may lead to handicap [39]. Therefore, impairment, disability and handicap were viewed as consequences of disease [25]. More recently WHO has acknowledged that disability may result from other factors such as injuries, traumas or accidents and it has moved away from a classification of disability as a consequence of disease [40].

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Impairment is defined as loss or abnormality of psychological, physiological or anatomical structure or function [25]. Thus impairment is the physical aspect of disability or the medical condition that may or may not result in loss of function. Disability is defined as disturbance to customarily expected activity, behaviour or performance, either directly or as a response by the individual to the impairment [25]. Thus disability prevents an individual from interacting in or with their world. Handicap is defined as social disadvantage resulting from disability or impairment. According to the AIHW, “The presence or absence of handicap and its severity are consequences of the interaction between the underlying impairment (i.e. medical condition), individual behaviour and attitudes, and the resources and social opportunities and restrictions affecting the individual” [25, p10]. Thus handicap prevents an individual from functioning.

The concept of handicap has recently been replaced by that of “core activity

restriction” [8-9]. Core activity restriction is a useful concept because it indicates level of dependency amongst older adults [8]. An individual has a core activity restriction when they need assistance, have difficulty or use an aid with the core activities of self care, mobility or communication, due to a disability [9]. Core activity restriction can be mild, moderate or severe and profound [8]. Individuals with severe or profound core activity restriction are those who sometimes or always need assistance with activities like self care, mobility and communication. The concept of core activity restriction is important because it is information on this subgroup with severe or profound core activity restrictions that is used to establish need for assistance and therefore demand for services. A severe or profound core activity restriction is reported by one in five older adults [8].

Both the proportion of people with disability and the severity of disability increase

significantly with age [8]. This fact is supported by the finding that both the prevalence and severity of disability increased markedly between phase one of SOPS and phase two [41]. Alpert indicates that the number of community-dwelling older adults living in America and aged 65 years or more with disabilities has climbed [42]. Women aged 85 years or over are more likely to have a severe or profound disability than men in the same age group (70% compared with 56%). The AIHW states that “any increase in numbers with a profound or severe core activity restriction has important implications for service providers, planners and policy analysts” [8, p38]. Over the next two decades, the number of older adults in this severe or profound core activity restriction category is predicted to rise by almost one hundred per cent in Australia. In 2001 there were 524, 900 older adults with a severe or profound core activity restriction and this figure is projected to increase to 1, 083, 600 in 2022 [8]. 2.3.3 Outcome of Disability (IADL, ADL, Mobility) The outcomes of disability most commonly assessed are Instrumental Activities of Daily Living (IADL) and Activities of Daily Living (ADL). Difficulties with mobility are often included in the assessment of IADL, however, in SOPS mobility was assessed

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separately. IADL includes measures of everyday instrumental activities such as shopping, cooking, housework, financial management, gardening/lawnmowing and home repairs. ADL includes measures of everyday self care activities such as showering, dressing, feeding, toileting and footcare. Mobility includes measures such as ability to use public transport, walking 200 metres, walking up and down stairs, transfer (getting in or out of a bed or chair) and mobility around the house. People generally begin by having IADL disabilities and then as their level of disability becomes more severe they are unable to perform ADL tasks or personal care.

The division of disabilities into IADL, ADL, and mobility categories used in SOPS is valuable because the types of formal services required by older adults align with the range of conditions that result in disability. For example, the most common disabling condition is arthritis, followed by musculoskeletal conditions [8]. This is reflected in the fact that the most common need among the core activities for all age groups was the need for assistance with mobility. Thus, disability is an important predictor of health and community service utilisation [7, 43]. In paper three [43], disability is divided into IADL, ADL and mobility categories whereas in paper six [44], community services are broken down by these same categories. The need for assistance with IADL, ADL and mobility activities increases with age. For example, only 5% of those aged 65-69 years need assistance with self care, whereas 10% of those aged 70-79 need self care assistance and this rises to 31% of those aged 80 years and over [8]. 2.3.4 Measures of Disability used in SOPS There are many different instruments or scales available that measure disability. Disability was measured in three different ways in SOPS. First by clinician assessment during which a medical practitioner conducted a semistructured history, physical examination and neuropsychological battery and then rated disability according to Kilsyth disability scales. Second, an informant or proxy also rated disability of the older adult according to Kilsyth disability scales. Third, a social scientist interviewed each participant at home and administered a modified form of the Australian Bureau of Statistics (ABS) methods of assessment of disability and handicap. Thus disability was measured by self-report, proxy and clinician. The Kilsyth disability scales and the ABS disability and handicap assessment methods used are described in the following two sections. 2.3.4.1 The Kilsyth Disability Scales The Kilsyth disability scales were developed by Akhtar et al [45]. In these scales, disability is identified by discovering abnormality during the previous week, in one or more of five areas: mobility, continence, domestic care, self-care, and psychiatric care. The Kilsyth disability scales measure disability in ADL (dressing, feeding and toileting all scored on a four point scale from 0 to 3), mobility (a single item on a five point scale from 0 to 4) and IADL (cooking, housework and shopping all scored on a three point

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scale from 0 to 2). For self-care and instrumental activities, the sub-item scores are totalled so that a score of 9 for ADL and a score of 6 for IADL represent maximum disability. This is the method used to score disability using the Kilsyth scale in paper 3 [43]. However, in paper 2 [46], the items of mobility, continence, cooking, housework, shopping, dressing, feeding and toileting were each scored on a 0-1 scale, with 0 representing maximum independence and 1 maximum dependence, to yield a total score ranging between 0 and 8. Akhtar et al., who assessed the level of agreement between independent assessments of disability by a health visitor and a doctor, conclude that the Kilsyth disability scales produce “results of reasonably objective validity” [45, p103]. These scales were chosen for use in SOPS not only because they include the more usual elements of IADL, ADL and mobility ratings but also because they include continence and psychiatric care which are particularly important in the population under study, namely people aged 75 years or more. These two additional elements are particularly important for individuals suffering from neurodegenerative disease. Another reason for the inclusion of these scales is their brevity. Thus the major benefits of these scales are that they are relatively quick to administer or rate and yet they are comprehensive and particularly useful in populations where there is a relatively high prevalence of neurodegenerative disorders. 2.3.4.2 Assessment of Disability and Handicap Used by the ABS and in SOPS The ABS has conducted several surveys of disability in Australia. The concepts and definitions used by the ABS are based on the World Health Organization’s International Classification of Impairments, Disabilities, and Handicaps (ICIDH) [39]. A person is defined as having a disability if they have one or more specific conditions that have lasted or were likely to last for six months or more. These conditions are: loss of sight (even when wearing glasses or contact lenses); loss of hearing; speech difficulties in native language; blackouts, fits or loss of consciousness; slowness at learning or understanding; incomplete use of arms and fingers; incomplete use of feet or legs; long-term treatment for nerves or an emotional condition; restriction in physical activities or in doing physical work; disfigurement or deformity; need for help or supervision because of a mental disability; long-term treatment or medication; difficulty gripping and holding small objects; long-term effects of head injury, stroke, or any other brain damage, and; any other long-term condition resulting in restriction.

The ABS defines a handicapped person as “a disabled person aged 5 years or over who was further identified as being limited to some degree in his/her ability to perform tasks in relation to one or more of the following five areas: self-care, mobility, verbal communication, schooling and/or employment” [25, p11]. The ABS also assesses severity of handicap for people aged 5 or more for: self-care, mobility and verbal communication [25]. A person is defined as having a severe handicap if personal help or supervision is required or the person is unable to perform one or more of the tasks. A person is defined as having a moderate handicap if no personal help or

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supervision is required, but they have difficulty performing one or more of the tasks. Finally, a person is defined as having a mild handicap if no personal help or supervision is required and no difficulty is experienced in performing the tasks, but the person uses an aid, or has difficulty walking 200 metres or up and down stairs. In SOPS, which began in 1991, the concept of handicap was used as is indicated above. It should be noted that the concept of ‘core activity restriction’, which has replaced that of handicap, is a relatively new one which the ABS used in the 1998 Survey of Disability, Ageing and Carers [47]. There is very little difference in the way these two concepts are measured, however, the introduction of a new term to replace that of handicap is important given the negative connotations and stigma associated with this term. As Racino notes, the World Health Organization’s emphasis on activities and participation and limitations in these areas of life is intended to “move toward more neutral language and away from concepts of disablement” [48, p6]. However, the following discussion will continue to use handicap as this was the term used in SOPS.

A large part of the ABS disability and handicap assessment was used in SOPS. SOPS assessed the presence or absence of disability, and IADL, ADL and mobility handicaps. Respondents were asked if they had one or more of the conditions defining disability and then they were asked if they required assistance with a task, had difficulty with a task or used an aid to perform a task in order to assess level of handicap. The IADL tasks assessed in SOPS were: private transport, shopping/errands, meals preparation, heavy housework, light housework, laundry, gardening/lawnmowing, home repairs and financial management. The ADL tasks assessed in SOPS were: showering/bathing, dressing, eating/feeding, footcare, incontinence management and using the toilet. Mobility tasks assessed in SOPS were: using public transport, going to/getting around places away from home, moving about the house and transfer. The benefit of this ABS/SOPS assessment is that it is quite comprehensive. However one of the weaknesses of this type of assessment is that it relies on self-report which is often unreliable, especially in people who are cognitively impaired. Another weakness is that the ABS disability and handicap assessment is quite lengthy and often a shorter scale measuring disability is all that time will permit in a multi-disciplinary community survey such as SOPS. The ABS disability and handicap assessment was chosen for use in SOPS because the ABS conducts regular surveys of disability and handicap in Australia and therefore comparability with their data and findings is possible. Also the findings of the ABS surveys on ageing and disability are widely used and quoted in Australia, for example by the AIHW [8-9]. 2.4 THE RELATIONSHIP BETWEEN DISEASE AND DISABILITY 2.4.1 Introduction

In discussing the relationship between disease and disability, it is important to distinguish between various models of disability and how they relate to disease. Disability can be understood and explained through a variety of conceptual models. At

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one extreme there is the “medical model” which is opposed at the other extreme by the “social model” [40, p20]. The medical model views impairment, disability and handicap as consequences of disease. Disability is seen as a direct cause of disease, trauma or other health condition and as a problem of the individual. Thus medical care is required, generally by professionals giving individual treatment. WHO states that in this medical model “medical care is viewed as the main issue, and at the political level the principal response is that of modifying or reforming health care policy” [40, p20]. However, as indicated at the very beginning of the section on disability, professionals and people with disabilities themselves have been unable to agree upon a definition of disability. A medical definition of disability emphasises the amount and kind of physical and mental dysfunction. However, for others, disability is viewed as a social concept where disability is defined by the ability to perform certain roles and tasks expected by society. Coudroglou and Poole state that “within this conceptualization, disability is viewed from the perspective of social norms, that is, task and role expectations organized around spheres of life activities such as self-care, education, family relations, recreation and employment” [49, p6].

Michailakis identifies three models evident in disability research [50]. First, there is the medical model which is the traditional view. Despite the fact that this model has come under much recent criticism, Michailakis states that “within disability research the medical perspective still holds a position as, if not the only valid, at least the most fundamental in a hierarchic order in relation to other perspectives” [50, p210]. The second model of disability is the social model and finally there is the individual-society model of which the WHO definition of disability is an example. In the next section studies using the medical model of disability will be reviewed and in the following section the social model will be discussed. Finally, the model used by WHO and also used in SOPS will be discussed as a model that aims to synthesise the medical and social models.

2.4.2 The Medical Model of Disability

Limitations in function as a result of impairment, disability and handicap are associated with expensive health care costs and poor quality of life for older adults. The role of chronic medical conditions in causing functional limitation has important implications for preventing disability and for providing adequate care to old people who become disabled [51]. It is hypothesised by Fries that there will be a delay in the age at onset of diseases leading to a shorter period of disability at the end of life which he calls the “compression of morbidity” [52, p133]. However, Olshansky and Ault argue that Fries’ theory is far from certain as we enter “the age of delayed degenerative disease” [53, p361]. The prevalence of disability is declining [54-55]. However, there is a simultaneous increase in the life expectancy of people with disabilities [56]. Therefore, it appears that despite an increase in the number (though a decrease in the proportion) of disability free older adults, the anticipated “compression” of morbidity is not occurring. There are several studies using the medical model and focusing on the impact of disease on disability using samples of old people living in the community.

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These studies have found that the neurodegenerative disorders and disorders affecting the joints and limbs have the greatest impact on disability [38, 45, 57-58]. Each of these studies and its findings will now be examined in turn.

In three surveys, Akhtar et al. studied 808 people aged 65 or more living at home in urban Scotland [45]. Their aim was to investigate the prevalence of disability and its causes in three random samples. Disability was found to be present in 227 participants and, in these participants, 382 clinical diagnoses considered to contribute to disability were made by doctors with experience in geriatric medicine [45]. The major cause of disability, found in 48 per cent of these disabled participants, was a neurological disorder [45, 59]. The second most frequent contributor to disability was cardiorespiratory disease, affecting thirty-eight per cent of participants and the third was joint disease, affecting twenty-four per cent of participants. Results clearly demonstrate the great importance of neurological disease as a cause of disability in old age [45]. It is possible that the reason joint disease was the third most important contributor to disability rather than the second most important contributor, as found in other studies [57-58], was because Akhtar et al. combined cardiovascular and respiratory diagnoses into one category and it was this category that was found to be the second most important contributor to disability. Cullen et al. surveyed 126 people with cognitive impairment aged 70 and over living in the community in Canberra, Australia [38]. The association between clinical diagnoses and the extent of disability was investigated. It was found that neuropsychiatric disturbances (disorders of cognition, behaviour and mood) and extrapyramidal gait disorders are major independent predictors of disability. The authors of this study recognise that their results cannot be extrapolated to those free of cognitive impairment or in institutional care but state that despite this fact, “the prevalence of neuropsychiatric and neurodegenerative diseases in the elderly means that attempts to prevent, reduce or manage disability in the elderly rest to a major extent on a greater understanding of these conditions” [38, p420]. Irrespective of its degree, cognitive impairment is a marker of disability [38] and this contention is supported by other studies [45, 57-58]. Cullen et al. argue that priorities for medical research should be diseases that result in long-term disability rather than those that kill because, in general, quality of life is valued more than length of life. Diseases that disable older people have significant public health implications, and interventions that prevent or delay the onset of these conditions promise to be of great benefit to old people and their carers [38]. Kay et al. conducted a study on 412 patients aged 70 years or over living in hospitals, nursing homes or sheltered accommodation or receiving care from the domiciliary nursing services, and of 100 old people living in the community in Hobart, Australia [57]. This study examined the respective roles of mental and physical factors in contributing to dependency. Results indicated that, of the physical indices, mobility and upper limb function were both strongly related to dependency. It was also found that “of the mental indices, cognitive impairment, nearly always due to dementia, was of outstanding importance” [57, p842]. Kay et al. note that their results are consistent with

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those of Sandholzer’s general practice study of old patients in which locomotive and cognitive impairments were also found to be the two main causes of disability. Sandholzer studied a group of 100 patients of a general practice in Germany, all of whom were aged 65 or over and were living in private households [58]. One of the aims of this study was to assess the relative contributions of different forms of physical and mental impairment to disability. It was found that disability was largely determined by locomotive impairment and by cognitive impairment due to organic mental illness. Many previous studies on disability focused only on a single disease such as arthritis [60] or coronary disease [61]. Other studies have included only a limited spectrum of neurodegenerative diagnoses [62]. There are only a few studies that examine disability in relation to a comprehensive set of systemic, psychiatric and neurodegenerative diagnoses as is the case in SOPS [38, 45]. In these studies, the severe grades of disability were mainly associated with the neurodegenerative disorders, particularly dementia and gait disorders. The above information on disability stems largely from a medical or clinical definition of disability in which the relationship between disease and disability is seen as a direct one. The four studies discussed above are largely based on the medical model and generally discuss implications for geriatric medicine and/or general practice. Sandholzer defines disability as “a loss or reduction of functional ability and activity that follows impairment” [58, p190]. Thus disability is viewed solely as a consequence of disease. Generally these studies do not include social indices that may affect and contribute to disability and handicap but instead are limited to medical diagnoses and which of these contribute most to disability. Cullen et al. do include a measure of social function but this is only asked of informants, not participants [38]. These four studies do provide information on which clinical diagnoses contribute most to disability and they highlight the importance of neurodegenerative diseases in this regard. From these studies it is possible to conclude that because of the escalating epidemic of neurodegenerative diseases, especially dementia, there will be significant disability in older adults as a result. The fact that each of these studies identifies neurodegenerative disorders as a major contributor, if not the major contributor to disability in community-dwelling populations, has significant implications for public health policy. It will become increasingly important to discover the causes of neurodegenerative diseases and ways to prevent or delay their onset as well as to provide appropriate services to disabled dementia sufferers and their carers. However, these studies do not assess the importance of social factors such as social networks and social support, service usage, financial resources and other socio-economic and socio-demographic factors in contributing to disability and handicap. The following sections outline two other models that take these factors into account to varying degrees. The social model argues the opposite of the medical model and thus views disability and handicap as the consequence of social factors alone and the individual-society model aims to synthesise and integrate both the medical model and the social model.

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2.4.3 The Social Construction of Disability The second model is the social model. As Michailakis indicates, in the social

model “there is no causality between impairment (biology-organism) and ‘handicap’, but on the contrary that ‘handicap’ is a particular form of discrimination and that discrimination has social origins” [50, p211]. Disadvantage is seen to be culturally, socially, economically and politically constructed and is not seen as an effect of impairment. Michailakis states that “according to this understanding ‘handicap’ is neither located in the impaired part of the body nor in the relation between the individual’s inability and society’s demands - as in the WHO scheme - but exclusively belongs to an excluding and oppressive society” [50, p212]. Disability is viewed as a social creation [63]. Abberley (1997 pp166-170) also highlights the notion of impairment as a social product and outlines some common features of disadvantage [64].

In the social model disability is created by social barriers and the inability of

society to create opportunities for people with disabilities to participate in the normal life of the community on an equal footing with others. For example, the fact that the general public is unable to use sign language disables people with hearing impairments, the fact that there is very little reading material in Braille disables people with visual impairment, the fact that public attitudes to people with non-visible disabilities is often hostile disables these individuals, and the lack of ramps disables wheelchair users. In this model it is only in specific settings that impairments become critical and disabling [65]. Thus, disability is viewed as a social construction. This social constructionist school of thought is sometimes called the minority group model. The term ‘minority group’ is used because people with disabilities are considered to be members of a minority group that are prevented from becoming ‘normal’ members of society and are discriminated against [66]. Donoghue presents two main reasons why the social constructionist school of thought has failed to replace the medical model in America. First, he criticises the landmark civil rights declaration called the Americans with Disabilities Act (1990) for its ideological basis. Donoghue argues that this Act “was won only through a costly compromise that effectually led to an ideological surrender to the same medical model of disability that it had attempted to replace” [66, p200]. Second, the importance of social structure in determining the legitimate definition of how disability arises and what it means to be disabled has been neglected in America. Donoghue contrasts the situation in America with that in Britain, claiming that there has been much greater emphasis on disability as a social construction in the British literature [66].

Ferguson presents several strengths of the social model [67]. First, it has

encouraged a focus on rights and dignity and the struggles of minority groups. Second, it is dynamic in the sense that it examines how the socially created definitions of disability and dependence have changed from an historical perspective. Third, the social model has encouraged a change in the language used to describe people with disabilities and has highlighted the power of such language in shaping thoughts and attitudes.

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The social model is not without its critics. Despite presenting the above strengths of the social constructionist point of view, Ferguson argues that this perspective “unintentionally justifies the continued exclusion of people with the most severe levels of retardation” [67, p51]. One of the reasons for this unintentional exclusion is because social constructionism “assumes that humans are agents in the social interpretation of their world” which is often not the case with people with severe intellectual disability [67, p54]. Marks claims that there are complex social factors that shape how disability is produced and that the social model fails to fully address these factors [65]. First, disability is conceptualised with a focus on certain kinds of barriers at the expense of others. For example, there is very little emphasis on people who experience emotional distress, communication difficulties or have learning difficulties and the disabling barriers presented to them. Emphasis has been on how “certain kinds of physical barriers are faced by white, Western, male wheelchair users” and thus centres on people with mobility impairments [65, pp87-88]. Second, another criticism of the social model is that it emphasises work and independence and thus adopts many of the values of capitalist society. Third, the social model has been criticised for the way in which a person is identified as having a disability. The model defines a person as having a disability if that person identifies themselves as having a positive disability identity. In other words, the social model suggests that if a person identifies as having a disability, then they are defined as disabled. However, Marks states that “many people with impairments and chronic illnesses would not necessarily identify themselves or be identified as disabled” [65, p 88]. Barnes, like Donoghue, makes a distinction between American socio-political analyses of disability and that in Britain. However, Barnes criticises both American and British approaches because they “tend to undervalue the impact of western culture in the oppression of disabled people” [68, p44]. Barnes claims that writers concerned with the experience rather than the production of both impairment and disability have tended to focus more on this impact of western culture.

2.4.4 The Individual-society Model Finally, there is the individual-society model. Michailakis argues that the WHO scheme falls into this category. Basically, disability is viewed as “the result of the interaction between the disabled individual and society” and “the demands and requirements from society determine whether an injury or impairment becomes a handicap or not” [50, p210]. It is when society does not take impairment into account that it becomes a handicap. In this model the focus shifts partially to society. In general, it is not enough to rehabilitate an individual to live and work in what is referred to as a ‘normal’ environment but is in fact an environment that is set up and developed with disability-free people as the norm. Instead society must be adapted as far as possible to meet the individual’s needs. Aspects of the environment that could be adapted in this way would include, for example, social policy, laws, special education and architectural aspects [50]. Neither impairment nor disability necessarily leads to handicap in the WHO scheme.

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It is evident that different solutions are proposed depending upon which model of disability one adopts. As indicated above [see section 2.3.2], for SOPS the WHO scheme current in 1991 was adopted with its definitions of impairment, disability and handicap which are viewed as hierarchical. Michalakis argues that the WHO scheme is an example of the individual-society model [50]. WHO periodically updates its classifications and definitions of disability and WHO’s most recent classification is known as ICF, which stands for International Classification of Functioning, Disability and Health [40]. In ICF WHO attempts to synthesise or integrate the medical model and the social model. WHO adopts a “biopsychosocial” approach and, aims to take into account both individual and environmental factors [40, p20]. Two individuals with the same disease may have vastly different outcomes in terms of functioning, abilities and ability to cope depending on societal, environmental and personal factors. For example, environmental factors external to the individual may have a positive or negative effect on a person’s performance as a member of society, on that person’s capacity to perform actions or tasks and on their body function or structure. In ICF, environmental factors are classified on two different levels – individual and societal [40]. Individual environmental factors include the physical and material aspects of an individual’s immediate environment (e.g. home, workplace, school) as well as direct contact with others such as family, acquaintances, peers and strangers. Societal factors include organisations and services related to the work environment, community activities, government agencies, communication and transportation services, informal social networks and social support, laws, regulations, formal and informal rules, attitudes and ideologies. In the following quotation, WHO summarises its current approach to disability:

“Disability is characterized as the outcome or result of a complex relationship between an individual’s health condition and personal factors, and of the external factors that represent the circumstances in which the individual lives. Because of this relationship, different environments may have a very different impact on the same individual with a given health condition. An environment with barriers, or without facilitators, will restrict the individual’s performance; other environments that are more facilitating may increase that performance. Society may hinder an individual’s performance because it either creates barriers (e.g. inaccessible buildings) or it does not provide facilitators (e.g. unavailability of assistive devices).” [40, p17].

WHO also acknowledges the contribution of personal factors to disability and

states that these factors may have an impact on the outcome of various interventions [40]. Personal factors are characteristics of the individual that are not part of a health condition or health states such as gender, race, age, other health conditions, fitness, lifestyle, habits, upbringing, coping styles, social background, education, profession, past and current experience (past life events and concurrent events), overall behaviour pattern and character style, individual psychological assets and other characteristics. All or any of these personal factors may play a role in disability at any level, however these factors are not classified in ICF.

The WHO classification provides a very good model of disability because it

attempts to explain the reasons for individual outcomes. There are many different contextual factors that affect how individuals cope with a disability and some have far

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better outcomes than others. For example the presence or absence of social support can have a significant influence on how an older adult copes with a disability, as can the presence or absence of financial resources. The issue of why some older adults, and indeed individuals of any age, cope well with a disability and others do not is an interesting one. WHO with its recognition of environmental, societal and personal factors goes a long way towards providing an answer to this question. It aims to measure how people function in their world and views their interactions in and with the community. Disability needs to be measured in the specific environment of the individual to have meaning because a person may have a disability and yet have no handicap, whereas another person may have the same disability but have a severe handicap. The WHO scheme highlights the fact that impairment does not necessarily mean the presence of disability, which in turn does not necessarily mean the presence of handicap. The scheme aims to grapple with the complex issue of the relationship between disease and disability and the relationship between the definition of disability and outcomes for specific individuals in specific settings.

Unlike previous WHO classifications, ICF has moved away from being a

“consequence of disease” classification and become a “components of health” classification [40, p4]. This change in emphasis means that now constituents of health are identified whereas previously the focus was on the impacts of diseases or other health conditions that may follow as a result. It would be fair to say that there has been a fundamental change in the way that the relationship between disease and disability is viewed. Previous WHO schemes were based on a much more direct relationship between disease and disability, whereas now WHO recognises that there are a host of contributing factors including environmental, societal and personal factors. As WHO states “thus, ICF attempts to achieve a synthesis, in order to provide a coherent view of different perspectives of health from a biological, individual and social perspective” [40, p20]. The old concept of handicap did incorporate environmental and societal factors to some extent because not all disabilities necessarily became handicaps. Handicap was viewed as a consequence of the underlying impairment (medical condition), individual attitudes and behaviour, and restrictions, social opportunities and resources influencing a person [25]. 2.4.5 Disability and Older Adults

Abberley criticises several studies for the extent to which they produce and

propagate a misidentification of who people with disabilities are. He claims that the stereotype of people with disabilities is of young people in wheelchairs and that this is far from the reality of the majority of people with disabilities [64]. Abberley cites research which found that only 9.8% of people with disabilities were under 45 years of age. He states that “causes of impairment were also found to be at odds with the stereotype” [64, p172], citing research that indicates that the major causes of severe disability are arthritis (31%), stroke or Parkinsonism (15%) and cardio-respiratory conditions (13%). This research found that 57.9% of impaired adults were over 65 years of age. Abberley states that it is this group of older adults that a Royal College of

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Physicians report identified as the group for whom provision is least adequate. This misidentification of people with disabilities can be seen to perform several important functions for the current social system. As Abberley notes, “by directing attention away from impairment associated with ageing, it naturalises this aspect of the situation, and reduces the amount of perceived disability in society, so that disability appears as ‘exceptional’. In reality about five and a half million, or one in ten people, in Britain today are disabled, approximately the same as the proportion of the workforce who are currently suffering from unemployment” [64, p173]. 2.5 SERVICE USE 2.5.1 Introduction

Most studies on service use among older adults in a community sample agree that diseases and/or disabilities are the primary predictors of service use [69-77]. Population ageing means that both the number and proportion of older adults is expected to increase significantly for the foreseeable future. Older adults as a group use disproportionately larger amounts of health services than younger people or, in other words, service use is associated with age [77]. Increasing disease at older ages leads to increasing disability and both of these factors in turn lead to greater usage of health and community services [71]. In addition, the cost of both health and community services is rising [72]. For these reasons understanding and modelling the determinants of service usage amongst older adults, in particular those aged 75 years and over, is becoming increasingly important. Paper four examines determinants of service use among people aged 75 years or over living in Sydney, Australia [7]. Much research in the past few decades has focused on understanding the determinants or predictors of service usage. This section first defines service use as it is employed in SOPS. Second, it highlights factors which other studies found to be determinants of service use as background to the analyses in paper four. Finally, this section describes Andersen’s behavioral model of health services use, which is the theoretical and methodological basis of the analyses of the determinants of service use in paper four. Research on health service use among older adults most commonly employs the behavioral model [69] which was developed and subsequently modified by Andersen [78-79]. 2.5.2 Definition For the purposes of this study, service use is defined as tasks performed by organisations or individuals that are received by and of benefit to older adults. This includes medical services, community services and informal social support. This section examines medical or health services and community services only. Social support is examined in the following section. In SOPS, medical services were divided into three measures, namely: days in hospital (per annum), specialist visits (per annum) and ambulatory care visits (per annum; to a general practitioner, medical centre or

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casualty). A score for total medical service usage was also calculated [7]. There were twenty-one state sponsored community services available to participants in SOPS and therefore included in the study. These were classified into four groups. First, the ADL community services including home nursing and home help (bathing). Second, the IADL community services including meals on wheels, home help (general), day care, laundry, home maintenance, gardening-lawnmowing, shopping and home modifications. Third, the mobility community services including transport and podiatry-chiropody. Fourth, the allied health community services including optical, hearing, medical supply, speech therapy, occupational therapy, dietary, psychological counselling, physiotherapy, social work-welfare and dental. These measures were chosen because of their relationship to the disability measures of ADL, IADL and mobility. Service usage measures were also chosen in an attempt to be exhaustive, that is, measures aimed to reflect all available services to these older adults living in the Central Sydney Health Area in 1991. Total scores for each of these four sub-groups were calculated, as well as a score for total community service use [7]. 2.5.3 Determinants of Service Usage Disease and disability are the primary determinants of both formal and informal service use among older adults [69, 71-72, 74-75]. Chronic diseases lead to disabilities which are responsible for rising health service utilisation [71]. Because disease and disability are associated with age, older adults are disproportionately high users of health services. This generalisation, however, can be misleading. In fact, a substantial portion of the service utilisation attributed to older adults is due to the extensive demand generated by a relatively small subgroup [75]. Mossey et al. reviewed the major studies that investigated the consistency of formal health service utilisation by older adults and found “that need as defined by health status is the most salient determinant of whether the individual is a consistently high, medium, or low user” [75, p96].

Several authors examined the predictors or determinants of service usage. First, Blaum et al. found that different diseases have different relative impacts on the amount of health services utilisation and also that different chronic diseases have a different combination of direct and indirect effects on health services utilisation [71]. Predictors of health services utilisation included the specific chronic diseases of hypertension, arthritis, diabetes, cancer and atherosclerotic heart disease. Second, Blaum et al. also found that self-rated health status and total number of disabilities were predictors of health services utilisation among older Americans [71]. Third, Coulton and Frost found that service use among older adults was primarily associated with need defined as disease (health status/level of impairment) and disability [72]. They also found that socially isolated older adults use fewer services in general and that they seem to have minimal ties to community agencies. These individuals may have small social networks with few available resources and they may be at high risk of deterioration and institutionalisation unless special efforts are made to reach them [72]. Therefore in two American studies Blaum et al. and Coulton and Frost found that disease, in particular

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certain specific diseases, and disability were major predictors of service usage as well as self-rated health and social support/social networks. An Australian study with similar findings which examines predictors or determinants of service usage in the form of visits to hospital is the Dubbo Study. This study is a prospective study of non-institutionalised older adults aged 60 years and over living in Dubbo, New South Wales [80]. It included 1,237 male and 1,568 female participants who were representative of Australian-born older adults in the general population [74]. McCallum et al. investigated hospital, residential and community service use among older adults living in Dubbo and found that, apart from age and gender, measures of health status were the major predictors of hospitalisation [74]. These measures of health status included previous doctor visits, previous hospital use, disability, diabetes, prior coronary heart disease (CHD), current smoking and high blood pressure. Disability was found to be a major predictor of hospitalisation and of nursing home admission. Health factors were also the major predictors of cumulative length of stay in hospital. Therefore, disease and disability were found to be the major predictors or determinants of health service usage in the form of visits to hospital. McCallum et al. conclude that some of the health factors that predict hospitalisation, such as risk factors like smoking and high blood pressure, are targets for health promotion and disease prevention activities. Elimination of the effects of smoking would decrease the odds of being admitted to hospital by 40% and lowering blood pressure would decrease the odds of being admitted to hospital by 20% [74]. 2.5.4 Determinants of Service Usage: Andersen’s Behavioral Model The behavioral model of health services utilization was first presented by Andersen in 1968 [78]. It has been subsequently revised and refined by Andersen and his colleagues [81-85]. In this model, predictors of service usage are placed into three classes of variables. The three classes of variables are predisposing factors, enabling factors and need factors. Predisposing factors are “personal attributes that may predispose individuals to seek care” [69, p53]. Enabling factors are those that make health services available such as income, insurance coverage and having access to a regular source of care [86]. Need factors refer to health status as evidenced by subjective (perceived) health and objective (assessed) health status and functional level [69]. Each of these three factors, which contribute to health services use in the behavioral model, will now be considered in turn. The predisposing component of the behavioral model predicts that some individuals have a greater propensity for using health services than other individuals [77]. Andersen states that “this propensity toward use can be predicted by family characteristics which exist prior to the onset of specific episodes of illness” [78, p15]. Individuals or families who have these characteristics are more likely to use health services even though the characteristics themselves are not directly responsible for health service use. Predisposing factors include the sub-components of family composition (demographics), social structure and health beliefs. Demographics are

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generally measured by age, gender, marital status and family size. Social structure is generally measured by employment, education and ethnicity. Health beliefs are generally measured by questions about attitudes to medical care, physicians and disease, as well as worries about one’s health. These three sub-components comprise the socio-cultural element of the behavioral model [77]. The enabling component of the behavioral model holds that despite being predisposed to use health services, an individual must also have the means to obtain them. Therefore, enabling factors include those things that make health services available to an individual or family [78]. Enabling factors are divided into the two sub-components of family resources and community resources. Family resources are generally measured by income, the presence of health insurance and having a regular source of care. Community resources are generally measured by physician to population ratios and hospital bed to population ratios, as well as by geographic location and population density. These two sub-components of the enabling characteristics comprise the economic component of the behavioral model [77]. The predisposing and enabling components of the behavioral model are necessary conditions for the use of health services but they are not sufficient conditions [77]. An individual must also have or perceive some illness or its possibility for the use of health services to occur. This need component of the behavioral model is the most immediate cause of health services use. Like the enabling component, the need component has two sub-components, and they are perceived need and professionally evaluated need. Perceived need, or illness, is generally measured by a self-reported global measure of health status. Professionally evaluated need is measured by the variables of seeing a doctor for symptoms and regular physical examinations [78]. Measures of activity limitations, especially those involving the basic activities of daily living are often used in research as proxies for physician’s assessments of such limitations and these measures provide a more objective assessment of need than perceived health [77]. Andersen’s initial behavioral model of health service has been subsequently revised on a number of occasions [79]. In Figure 1 below is a schematic representation of the version used in this study.

Andersen’s behavioral model has been criticised for being an oversimplification of reality and for omitting important variables [86]. Wan states that “criticisms of this behavioral model lie in its overemphasis of structural determinants and its failure to specify the social-psychological process through which physical health is perceived, evaluated and acted upon” [69, p53], citing Mechanic [87], Ward [88] and McKinlay [89] as sources. However, all models involve simplification and Andersen’s model has proven to be and remains today a useful tool in the study of the service utilisation of older adults. It is the analytical model used most frequently in the study of health services in general [77] and also with specific regard to studies involving older adults [69]. Several recent studies, many on older adults, have employed this model [90-94]. The selection of Andersen’s as the most appropriate model for use in SOPS is confirmed by this widespread and recent usage. Not only does it appear still to be the most useful way of modelling service use by older adults, but it allows for the comparison of results with other studies that have used the model.

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Measurement of the need component of the behavioral model has also been

criticised. Illness is generally measured by a self-reported global measure of health status and this has been criticised as being inadequate. Sources of available data do not contain indicators of professional need assessments and this necessitates reliance on respondents’ perceptions and self-reports which is inadequate for the formation of public policy [86]. The present study aims to rectify this criticism of past research by assessing needs, defined as diseases and disabilities, by using qualified medical practitioners [7].

Figure 1: Andersen’s Behavioral Model of Health Service Use

Adapted from [86, p471] 2.6 SOCIAL SUPPORT 2.6.1 Introduction Paper five examines the characteristics of social support in the SOPS sample [95]. An association between social relationships and health has long been noted by researchers [5, 96-106]. In Australia, associations have been found between perceived social support and well-being, and social support has been found to reduce the likelihood of depression amongst older adults [107-108]. Kendig and Brooke state that “The Australian Longitudinal Study of Ageing and Dubbo studies also found that the

PREDISPOSING ENABLING NEED USE

Demographic

Social Structure

Health Beliefs

Family Resources

Community Resources

Perceived

Evaluated

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presence of a spouse is consistently related to lower morbidity and mortality” [107, p129]. Therefore an examination of social support is crucial to an understanding of the health and well-being of older Australians. Recent research identified social support as only one of several critical pathways by which social networks may influence physical and mental health status. Berkman et al. identify five mechanisms by which the structure of social networks might influence disease patterns: social support, forces of social influence, levels of social engagement and participation, the regulation of contact with infectious disease and access to material goods and resources [109]. Social support is the mechanism most commonly studied and this section will be restricted to a discussion of social support.

It is the contention of this thesis that identifying the characteristics of social support amongst older adults is important because lower levels of social support have been associated with higher mortality, poor health and lower levels of well-being. This section first defines social support. Definition of terms is critical in the area of research on social relationships because many terms have been used loosely and interchangeably [109]. Second, this section introduces and defines the types of social support examined in SOPS. Third, an examination is made of social support as a predictor of disease, mortality and lower levels of well-being. Fourth, the various theories of the relationship between social support and health are outlined. Fifth the importance of the identification of causal mechanisms between social support and health is highlighted. Finally, the way social support was measured in SOPS is discussed. 2.6.2 Definition

Social relationships are usually conceptualised in one of two ways, either as social support or as social networks [110]. As with many concepts in this area there has been confusion and inconsistency regarding the meaning of these two terms [111]. In general, social support refers to the quality or function of social relationships and social networks refer to the quantity or structure of social relationships. Social networks are sometimes referred to as more objective measures of structure whereas measures of social support are seen as more subjective measures [112].

Some researchers have adopted social support as a more global term

encompassing social networks [113], however in this thesis the term social support is used in its more restricted sense. This thesis adopts Shumaker and Brownell’s definition of social support as “an exchange of resources between at least two individuals perceived by the provider or the recipient to be intended to enhance the well-being of the recipient” [114, p13]. The notion of resources suggests that the support provided through relationships with others is valuable to the recipient. Thus, assistance cannot be defined as support unless the resource provided is perceived to be beneficial to the recipient.

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This thesis wishes to avoid negative stereotyping of older adults as always dependent and always in receipt of social support. Older adults make substantial contributions to their family, friends and voluntary organisations [107]. In an earlier study of people aged 60 and over residing on the Central Coast, NSW, Australia, Edelbrock found that respondents as a group “gave more instrumental resources to network members than they received and undertook large amounts of voluntary and charity work often providing services for the elderly in need of assistance in this way” [115, p66]. However, using the same indicator of instrumental resources given and received, measured in hours per annum, the people aged 75 years and over in SOPS were found to receive more instrumental resources from network members than they gave in total. Despite the fact that this comparison is between two different samples it does tend to indicate that with advancing age older adults become more dependent upon social network members for social support, as a group. There is of course wide variation between individuals. Some over-75 year old people in the SOPS sample gave substantial amounts of resources to network members, some were even carers, but many were also frail and dependent upon others for social support. 2.6.3 Types of Social Support

The most commonly assessed resources exchanged within social relationships constitute the main measures or types of social support examined in the literature. For the purposes of this thesis these resources are: instrumental support, emotional support and presence of a confidant, perceived support, and social involvement/participation. Other researchers have included appraisal and informational support instead of perceived support and social involvement/participation [109]. At the time of question selection for the SOPS instrument (1990-1991) it was thought that it would be too difficult to accurately measure appraisal support and informational support. Perceived support was included because of the importance of perceived support in the work of Henderson et al. [116] and Seeman and Berkman [117]. Research by Henderson et al. upheld their hypothesis that “where there is a perceived lack of those provisions supplied through social bonds, morbidity is higher” [116, p579]. Seeman and Berkman highlighted the importance of perceived availability and perceived adequacy of support and consequently these concepts were included in SOPS [117]. Questions on appraisal and informational support were also omitted from SOPS for the purposes of brevity. The following section will define and discuss the four types of support included in SOPS.

Instrumental support is the tangible, material or physical resources needed for

daily living. Berkman et al. define instrumental support as “help, aid or assistance with tangible needs such as getting groceries, getting to appointments, phoning, cooking, cleaning or paying bills” [109, p17]. Unlike emotional support, significant instrumental support is dependent upon the availability of close family members. If these close family members are unavailable institutionalisation is the likely outcome for frail and vulnerable older adults [107]. Van Tilburg notes that poor health will generally result in an increased need for instrumental support [118]. The fact that poor health is

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associated with increasing age suggests that the need for instrumental resources will be greater with advancing age. Instrumental support has often been ignored in definitions of social support and yet this type of support is especially important for older adults for reasons outlined in the following quotation:

“Over one-third of the elderly require some degree of long-term supportive service, and an estimated 80-90% of this instrumental support is provided by family members (Brody, 1980); therefore, the need for expanding the definition of social support to include this often-neglected support dimension is clear.” [119, p202].

Berkman et al. cite Thoits’ [120] definition of emotional support stating that this

type of support is related to the amount of “love and caring, sympathy and understanding and/or esteem or value available from others” [109, p17]. In the Ageing and the Family Project relatives were particularly likely to be confidants and as such they reinforced a sense of personal worth. Friends on the other hand were available for social activities and for giving acceptance to older adults [107]. Wilkinson and Marmot state that low levels of emotional support are associated with lower levels of well-being, more depression and higher levels of disability [5]. In SOPS emotional support was ascertained by asking respondents if they could count on anyone for emotional support, for example, listening to them if they need to talk about their worries and problems or helping them make a difficult decision. In addition, a confidant is defined as one special person with whom an individual feels very close and intimate, who shares confidences and feelings and is dependable.

Perceived support is divided into two categories, namely perceived availability of

support and perceived adequacy of support. Perceived availability of support is an individual’s perception of having someone to count on if assistance is needed. Perceived adequacy of support is the respondent's perception of whether support currently received is sufficient [117]. Kendig and Brooke outline a number of studies identifying associations between perceived support and measures of well-being [107]. These studies include the Ageing and the Family Project study and the Australian Longitudinal Study of Ageing.

Social participation and involvement includes activities such as: attendance at

groups, clubs and organisations; getting together with others; and engaging in pleasurable social activities such as visiting or going out with friends. Kendig and Brooke state that “in the Australian Longitudinal Study of Ageing, well-being was related less to family interaction (which can be obligatory) and more to diffuse and voluntary social activity in the community” [107, p127]. Gibson and Mugford found that poor mobility, shrinking social networks and the absence of other personal resources may result in low levels of social activity amongst older adults [121].

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2.6.4 Social Support as a Predictor of Disease, Mortality and Lower Levels of Well-being

The relationship between social support and health has received increasing research attention since the 1970s [122]. Characteristics of social relationships have been recognised as risk factors for disease and mortality and there has been a shift in medicine from a focus on traditional physical risk factors to a more holistic view of individuals within the context of their environment, including their relationships with others. This paradigm shift occurred because traditional attempts to explain causation of diseases as a product of known risk factors for physical or systemic disease (e.g. cardiovascular, musculoskeletal, respiratory) offer only a partial explanation [113]. Many disease cases cannot be classified using a conventional taxonomy, and traditional methods focusing on physical disease alone can explain neither placebo effect nor the observed tendency toward general susceptibility to disease of particular groups of people. That is, the observation that a small proportion of all people exposed to combinations of negative psychosocial, environmental and life experience characteristics suffer from more illness of all kinds [123]. For these reasons researchers have increasingly turned their attention to psychosocial risk factors for disease, not as an alternative explanation but as a means to explain observed reality more adequately.

Focusing on the physical disease process itself has led to the identification of

modifiable risk factors such as lipids, salt, weight and exercise and this traditional approach remains useful when identifying specific causes of illness and death. Interventions aimed at modifying these risk factors have in turn resulted in disease prevention and increased life expectancy. However in order to explain current patterns in morbidity and mortality, even taking into account these significant advances, it appears that an additional level of explanation is required [123]. The nature of social relationships is one of a number of psychosocial risk factors for health and well-being that are now receiving vigorous research attention. Watson and Hall state that during the 1970s and 1980s there was “a growing realisation that social factors play a larger than expected role in the determination of health status” [4, p23]. For example, some older adults clearly have an advantage over others and they remain active, happy and healthy well into advanced old age. The behavioural and social factors that contribute to this advantage are receiving increasing interest [4].

The characteristics of social relationships that have been examined as risk factors

for disease and mortality include both characteristics of social networks and characteristics of social support. The characteristics of social networks include size of network, social isolation, density of network, connectivity, contact frequency, network composition and proximity of network members. The characteristics of social support that have been examined as risk factors for disease and mortality include receipt of and type of instrumental support, receipt of and availability of emotional support, presence of a confidante, perceived support (including perceived availability and perceived adequacy), informational support, appraisal support and social activity levels. Social isolation has emerged as a predictor or mortality [124]. Consistent evidence exists for the relationship

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between emotional support and psychological well-being [125]. Perceived support has also been highlighted as a risk factor for morbidity [116].

The strongest evidence exists for associations between social support and both

mortality and mental health. There is less evidence for an association between social relationships and physical diseases [112]. However this may be due to the concentration of research effort on mental health and emotional support, leading to one of the most powerful generalizations: that adverse life events cause fewer negative mental and psychological health effects if emotional support is provided [125]. Uchino et al. provide an excellent literature review on the relationship between social support and physiological processes [124]. This literature review of eighty-one studies finds that “social support was reliably related to beneficial effects on aspects of the cardiovascular, endocrine, and immune systems” [124, p488]. There was evidence for the stress-buffering hypothesis [see section 2.6.5.3] in some studies. In addition, emotional support emerged as an important dimension of social support. However, there are limitations to the methodologies of many studies. These limitations include cross-sectional and correlational designs, the conceptualisation of both social support and physiological processes as unidimensional, absence of the reporting of data on the psychometric properties of social support measures, and the lack of prospective studies [124].

2.6.5 Major Hypotheses on the Relationship Between Social Support and Health As indicated above, convincing evidence exists for a relationship between social support and health [122]. Sherbourne et al. found that “patients with high levels of social support had significantly better levels of physical functioning and emotional well-being than did patients with low levels of support” [126, p241]. In addition, results on the physical functioning of older adult patients indicated that low levels of social support were particularly damaging. Bowling claims that “many studies suggest that there is a relationship between social support and physical and psychological health status, risk of institutionalization and mortality of the elderly” [127, p68]. It is the contention of this thesis that the data and results presented in paper five are significant because social support has been found to have an important association with health status and well-being both in the general population and amongst older adults. If there is an association between social support and health then it is crucial to understand the characteristics of social support, particularly in populations of advanced age where dependence on social support is high. For these reasons the following sections will outline the various hypotheses on the relationship between social support and health, beginning with the general relationship and then examining the two most widely used hypotheses: the main or direct effect hypothesis and the buffering hypothesis. Finally the minimum threshold hypotheses, health as an independent variable and the possibility of a combination of hypotheses will be discussed briefly.

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2.6.5.1 The Existence of a Relationship

Although initial enthusiastic claims about the health effects of social relationships have been tempered more recently with valid criticisms, there is a general consensus that aspects of social relationships influence mortality and morbidity both directly and indirectly [109, 125, 128]. Researchers differ according to their explanation of the nature of this relationship and most explanations can be categorised under one or a combination of the following hypothesis types. 2.6.5.2 Main or Direct Effect Hypothesis

The main effect hypothesis is one explanation of how social relationships affect health. It is argued that social relationships have a direct or independent effect on health status [129]. Social integration is assumed to be a basic human need and without it individuals are thought to be more susceptible to disease. More research is needed on the mechanisms through which this effect operates but some suggestions are that integration in a social network leads to a greater sense of stability, control, predictability, purpose, self-worth and identity, and that it facilitates feedback and the perception that support provided in the event of need will be adequate [112]. It is also possible that social integration influences the immune system and that it encourages the adoption of health-promoting behaviours.

Most research argues the case for social relationships as a positive factor in

health promotion. However a view that has received little attention until recently is the potential for negative aspects of social relationships to promote ill health [125, 129-131]. Several studies have examined these negative aspects of social relationships. First, Krause tested two competing hypotheses, one being that satisfaction with support is determined primarily by the amount of assistance provided by significant others, and the other being that negative interaction may play a greater role in this process. This nationwide United States survey of older adults found that “negative interaction appears to be more strongly related to satisfaction with support than measures of support received from others” [132, pP59]. Second, Schuster et al. found that negative interactions predict depressed mood more than supportive interactions. These authors state that supportive interactions, usually emphasised in the literature, may be less important for mental health than the absence of negative interactions [133]. Finally, McMahon et al. examined negative life events, social support and their impact on depression in three personality types and their findings allow for the inference that stress leads to depression. However these authors found that social support was not directly beneficial nor did it buffer the negative effects of stress with regard to depression in any personality group [134].

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2.6.5.3 Stress Buffering Hypothesis

Another explanation of how social relationships influence health is by protecting or buffering an individual in the presence of stress [129]. This theory hypothesises an indirect or mediating role of social relationships between the stressor and health outcomes. Social support can protect people from the disease-causing effects of stress in two main ways. First, by changing an individual's perception of a stressor, such as bereavement or illness, thereby enhancing ability to cope and preventing a stress response. Second, by reducing the amount of stress experienced with possible physiological and/or behavioural impact, for example, immune system response or encouragement of health-promoting behaviour [112, 125]. The kind of social support measured may be crucial to the identification of a stress buffering effect.

The multidimensional measurement of support functions is essential in

determining the mechanisms by which support affects health and well-being. Type of support may be especially important in understanding when social support buffers the pathenogenic effects of stress. Hence, buffering effects may occur only when the kinds of available support match the need elicited by the stress a person is experiencing. This issue is complicated somewhat in that, in many cases, multiple needs are elicited by the same stressor and needs may shift over the course of the stress experience [112]. Two literature reviews on the stress buffering hypothesis are Cohen and Wills [135] and Alloway and Bebbington [136]. The two most commonly adopted and tested hypotheses are the main or direct effect hypothesis and the stress buffering hypothesis. There is considerable support for both explanations and as Bowling states “it is, however, still unclear whether any effect of social support on health is direct or as the result of a buffering effect” [122, p48]. The following three sections will briefly describe some other possible explanations of the relationship between social support and health. 2.6.5.4 Minimum Threshold Hypothesis

Social relationships may only adversely affect health if they fall below a certain critical level. For example, individuals may not be at risk unless they have fewer than two network members, with the greatest risk occurring for people with no network members at all [117]. The minimum threshold hypothesis implies that the association between social support and health is not linear but that there is a threshold or levelling-off effect instead. 2.6.5.5 Health as an Independent Variable

Researchers have pointed out that the discovery of an association between aspects of social relationships and dimensions of health status does not necessarily mean that social support determines health status. Social support may not be an independent variable as is frequently assumed. Poor social support and poor social networks may be a product of disease rather than a cause [131]. This theory has received little attention and it

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is the basis for many recent calls for longitudinal studies to verify the direction of causality between social relationship variables and health variables. 2.6.5.6 Combination of Hypotheses

Recognition of the multidimensional nature of social relationships has led to the view that both the main and buffering effects operate in different contexts depending on the measure or particular aspect of social relationships that is being assessed. It is also possible that a combination of the above explanations or theories is required to adequately explain the impact of social relationships on chronic disease processes [113]. The literature provides evidence for both the main/direct and the buffering hypotheses and it appears that further comparisons of these two theories may be considerably less important than identification of how social support comes to affect specific disease outcomes [112]. 2.6.6 Identification of Causal Mechanisms between Social Support and Health

There is general agreement that the most important focus for future research is no longer on the existence of a relationship between social support and health but rather on the discovery of the processes or mechanisms that link social relationship and health indicators [107, 125]. Such processes may be physiological, cognitive or behavioural [112]. There is also consensus regarding the need for more specific hypotheses and the development of theories to discover specific pathways between particular disease types and particular support or network variables [112, 129]. Therefore an understanding of the complex nature of disease processes, social support and social networks is required.

It is likely that the role of social support in both etiology and recovery is, to some

degree, similarly mediated. In both cases, support may influence health through the promotion of self-care and immunologic competence. Future work should focus on these mediators and on the emotional and psychological states that trigger these mechanisms. This work should also recognize that support is a complex concept that can only be understood when research is designed to investigate specific conceptions of support that are theoretically linked to the processes under consideration [112].

The link between the kind of support and specific outcomes depends on our

hypotheses concerning the pathenogenesis of a particular disease or decline and the process by which a particular kind of support inhibits that process or promotes recovery [129]. Some examples of hypotheses on how social relationships may affect specific health outcomes for older adults are:

1. Sudden loss of emotional support due to death of a close friend may have a critical impact on the health of a very vulnerable and frail older person and a much weaker impact on a healthy and vigorous old person [113, 129].

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2. It is unlikely that a relatively short-term exposure to social isolation could substantially contribute to a long-term disease process. For example, perceived availability or adequacy are unlikely to be predictors of atherosclerosis [129]. 3. The type of support that prevents a functionally impaired older person from being admitted to a nursing home (instrumental) is different from the kind of support needed to prevent depression (emotional) [129]. 4. The provision of instrumental support by a geographically proximate network member is most likely to enable a frail older person to remain at home. This is very different from the aspects of network structure that are related to recovery from myocardial infarction or hip fracture [129]. 5. If lack of instrumental support is an important factor in determining entry into a nursing home versus maintenance in the community, then having a child living nearby may be a critical factor in determining the availability of such support. Alternatively, if some physical conditions are caused by psychological states brought on by isolation and loneliness then lack of a more extensive network to provide emotional support may be the critical factor [117]. 2.6.7 How Social Support was Measured in SOPS The following sections discuss how social support was measured in SOPS. Questions and instruments used to measure social support derive from a number of sources and reasons for their choice are explained. Because a description of how social support was measured is not included in paper five, the measures used are discussed in the sections below. In SOPS social support was not measured by using any recognised instrument or scale. It is a very complex phenomenon and there was no instrument or scale available at the time of development of the questionnaire for SOPS which adequately covered the dimensions of social support that required measurement. No scale existed which was short, simple to understand, relevant to older adults, psychometrically sound, and, therefore suitable for incorporation into a large Australian multidisciplinary project such as SOPS. The dimensions of social support that needed to be measured were: instrumental support, emotional support, perceived support and social involvement. Recently, an Australian scale suitable for older adults has been devised for measuring social support [137]. However, this scale was not available at the time that instruments were selected for inclusion in SOPS. Goodger emphasises "the paucity of brief, inexpensive, psychometrically sound scales suitable for use with older people", also stating that "exploration of the links between social support and older people has been hampered by a lack of consensus on operational definitions of social support, and the use of a plethora of scales which have poor supporting psychometric properties" [137, p260]. After considering at length available instruments and the dimensions of social support that needed to be measured, each type of social support

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was approached separately and a series of simple questions were devised that would measure each type of social support. This approach of disaggregating the concept of social support is supported by several other authors [138-142]. Even if scales that measured the four specific types of social support (i.e. instrumental, emotional, perceived and social involvement) had been available at the time that the instrument for this study was devised, time constraints in this multidimensional longitudinal study would have made their inclusion impractical. In the following sections the questions used to measure each type of social support in this study are explained more fully. 2.6.7.1 Measurement of Instrumental Support in SOPS Because instrumental support is by definition tangible support, it is fairly easily quantified. In this study instrumental support was measured by asking respondents for the frequency and duration of a range of instrumental support tasks that they received from informal sources. Frequency and duration of these tasks were then multiplied together for each network member to provide a score of the hours per annum that each particular task was performed. Individual task scores were then added together to provide a composite score of the total instrumental support provided by each network member in hours per annum and this score was then converted to weeks per annum to provide the final continuous variable for instrumental support used in subsequent regression analyses. The instrumental support tasks measured in this study were divided into three groups and were obtained largely from those used by the Australian Bureau of Statistics in their Disabled and Aged Persons survey to measure disability and handicap [143]. The three groups are: instrumental tasks, self-care tasks and mobility tasks. Instrumental tasks measured were: private transport, shopping/errands, meals preparation, heavy housework, light housework, laundry, gardening/lawnmowing, home repairs and financial management. Self-care tasks measured were: showering/bathing, dressing, eating/feeding, footcare, incontinence management and using the toilet. Mobility tasks measured were: using public transport, going to/getting around places away from home, moving about the house and getting in or out of a bed or chair (ie transfer). 2.6.7.2 Measurement of Emotional Support in SOPS Emotional support in this study is measured in several different ways. First, by using the term itself in a question taken from Seeman and Berkman’s survey: “Can you count on anyone to provide you with emotional support? (Talking over problems or helping you make a difficult decision)” [117, p748]. Seeman and Berkman only asked for the main provider of emotional support in the last year, however SOPS collected data on all network members. This provided a more complete picture of the social support provided to old-old people by allowing each respondent to nominate up to six

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providers of emotional support in order of their importance. This also permitted the construction of a continuous variable for emotional support based on the number of emotional supporters that each respondent had, ranging from zero to six. The second way that emotional support was measured was by assessing whether or not each respondent had a confidant. Again, this question was obtained from Seeman and Berkman's questionnaire and the question was: “Is there any one special person you know that you feel very close and intimate with - someone you share confidences and feelings with, someone you feel you can depend on?” [117, p748]. The third way that emotional support was measured was by asking each respondent how close they felt to each network member. The question asked: How close to ...(person's name) do you feel? The participant could respond in one of four ways, either by saying that they felt very close, fairly close, not too close or not at all close to that network member. The idea for this question also came from Seeman and Berkman, however Seeman and Berkman only asked this question about children of respondents [117]. Finally, SOPS wished to ascertain whether or not negative aspects of social support cause ill health and therefore respondents were asked: Does your relationship with ...(person's name) cause you stress for any reason? This question was asked for each network member and respondents replied with either "yes" or "no". 2.6.7.3 Measurement of Perceived Support in SOPS Perceived support was measured in two ways, first as perceived availability of support and second as perceived adequacy of support. Perceived availability of support is based on a person's perception of whether or not support would be available in a hypothetical instance of need. Seeman and Berkman measured this by asking respondents: "Can you count on anyone to help you with daily tasks or provide you with emotional support?" [117, p739]. In SOPS the hypothetical instance of illness was chosen, as opposed to instrumental or emotional support, because respondents may confuse actual availability of support with perceived availability of support in the case of instrumental and emotional support. Perceived availability assesses who would provide support if a need arose whereas actual availability assesses who actually does provide support. The question used in SOPS came from the Dubbo study questionnaire [80]. The Dubbo study is a study on older adults residing in Dubbo, a regional centre of New South Wales, Australia. The researchers who devised the Dubbo study questionnaire were interested in measuring social support as well as other aspects of Dubbo's older adult population, especially health. When choosing social support measures for SOPS, some questions used in the Dubbo study were selected to facilitate comparison with the population of older adults in Dubbo. These questions were also short and easy to understand and therefore suitable for inclusion in a large epidemiological study such as SOPS. The question on perceived availability of support used in SOPS and the Dubbo

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study asks: "How much can you count on people when you are ill?". Respondents could choose between the categories of: a great deal, quite a lot, a little or not at all. Perceived adequacy of support is based on people’s perception of whether support currently received is sufficient or whether they feel they need more support. The two questions used in SOPS to measure perceived adequacy of support were taken from Seeman and Berkman's questionnaire [117]. In the first question on perceived adequacy of support respondents were asked "Could you use more help with ... (each self-care and mobility task)" and they were able to answer: a lot more help, some more help, a little more help and no. There are six self-care tasks (showering/bathing, dressing, eating/feeding, footcare, incontinence management and using the toilet) and four mobility tasks (using public transport, going to/getting around places away from home, moving about the house and getting in or out of a bed or chair (ie transfer)). Scores for all self-care and mobility tasks were converted to a score between zero and one where zero means no help needed and one means a lot more help is needed. These scores for each task were then added together to create a total perceived adequacy score for instrumental support ranging from zero (no help needed) to ten (help needed for all tasks). In the second question on perceived adequacy of support respondents were asked "Could you use more emotional support than you receive?”. They had the option of selecting between the categories of: a lot, some, a little and no. 2.6.7.4 Measurement of Social Involvement/Participation in SOPS Questions measuring social involvement and participation in this study, with the exception of the Frenchay Activities Index, were taken from the Dubbo study questionnaire [80]. Social involvement or participation was measured in four ways. The first question was: "How often do you attend meetings or programs of groups, clubs or organisations that you belong to?". Respondents had the option of choosing one of four categories: weekly or more often, about monthly, less than once a month or never. The second question aims to measure getting together with or visiting other people and it was "How often do you get together with friends, neighbours or relatives and do things you like to do, e.g. go out together or visit in each other's homes?". Again respondents could choose between the options of weekly or more often, about monthly, less than once a month or never. The third question aims to measure attendance of religious services and simply asks "How often do you attend religious services?". For this question respondents had the option of choosing between six categories and these were: never, about once a year or less, several times a year, about once a month, two or three times a month and every week or more. Finally, social involvement/participation was measured by using the Frenchay Activities Index (FAI) [144]. The FAI was originally devised as a means of assessing social activities after stroke. Fifteen general (as opposed to personal) activities are measured: meals preparation, washing up, washing clothes, light housework, heavy housework, local shopping, social occasions, walking outside for more than 15 minutes,

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hobbies, driving car/bus travel, travel outings, gardening, household/car maintenance, reading and gainful work. These activities are relevant to older adults and this was one of the reasons for the inclusion of the FAI in SOPS. The scale includes many homemaking activities and little weight is given to work because this bias toward routine daily chores is important for older adults who comprise the population prone to stroke [144]. The scale is also short, containing only 15 questions, and it is easy to administer by the interviewer, two major considerations in a population-based epidemiological study such as SOPS. The FAI uses the sum of the fifteen activities to produce a score range between 0 (low) and 45 (high). The scale aims to measure more complex activities or activities requiring greater decision-making and organisation than an activities of daily living scale (ADL) would measure. It also aims to measure social activity as opposed to social support. This is done in a fairly objective manner based on the frequency of actual activities undertaken in the last 3 months and the last 6 months rather than on the quality of these activities. Despite the fact that a number of the activities assessed in the FAI are more commonly known as IADL the authors of the FAI argue that it “is intended to measure activities which are not essential to functional independence but which reflect a higher level of independence and a more ‘social survival’ ” [144, p179]. The rationale for nominating the FAI as a measure of social activities is further supported by the assessment of construct validity which indicated that there was a relationship between disability and social function. In addition, factor analysis indicated a common underlying construct and correlations with other measures were as expected. When tested the scale was found to be valid, reliable, sensitive, simple, communicable and relevant [144]. 2.6.8 Social Support This thesis attempts to overcome some of the methodological difficulties of previous research on social support as indicated in section 2.6.7 above. It also aims to capture some of the heterogeneity contained in the very diverse group of adults aged 75 years and over. Social support literature can be criticised for not distinguishing between different age groups [145], and between gender and socioeconomic status groups [119]. Fine highlights important differences between people who are cognitively impaired and those who are physically impaired, and between people who live alone and those living with others [146]. By ignoring such sub-groups researchers make the assumption that the characteristics and effects of social support are the same for all sub-groups. This thesis examines the characteristics of social support by considering much of this heterogeneity. Social support is described with regard to differences in age, gender, marital status, socioeconomic status (education, previous occupation, income) and sample type. This research is important because little is known about the characteristics of social support and its diversity across these sub-groups with regard to community-dwellers aged 75 years and over in Australia. This information is critical because social support predicts mortality, health and well-being [see sections 2.6.1; 2.6.4; 2.6.5.1]. Findings from SOPS indicate that although most participants received adequate social support, there were sizeable groups that had low levels of social support and were quite isolated. These groups included: the fifty per cent who did not

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attend groups, clubs or organisations; the twenty-two per cent who had only one to five social network members; the twenty per cent who had no emotional supporters and; the fifteen per cent who had no confidant, amongst others [147]. It is these groups of older adults who may be at risk of mortality, poor health and low levels of well-being. 2.7 THE RELATIONSHIP BETWEEN SERVICE USE AND SOCIAL SUPPORT 2.7.1 Introduction In general the literature on service use agrees that disease and disability (needs factors) are the major determinants of service use among older adults. However, this literature on service use can be criticised in several ways. First, research methodology most commonly involves cross-sectional designs using a behavioural model. Cross-sectional studies have limitations because causality cannot be infered. Criticisms of the behavioural model have been previously outlined [see section 2.5.4]. Second, the service use literature frequently includes only crude measures of the needs factors of disease and disability, almost always with a sole reliance on self-report. Third, there are problems with the measurement of service use end points and service use is often aggregated from quite distinct services into a single end point. Despite general agreement that social relationships do impact on health status, the social support literature can also be criticised for various reasons. First, the social support literature can be criticised for poor conceptualisation of social support and social networks including analysing supportive ties only, assuming all ties are supportive and reliance on simplistic overall measures of network structure, such as size and density. Second, the social support literature can be criticised for poor methodology and research design, including sole reliance on self-reported health and symptom measures rather than clinical assessment, the use of cross-sectional designs in which it is impossible to establish the direction of causality, the fact that comparatively few studies have utilised population-based research designs, failure to acknowledge the heterogeneity of the study populations and to assess variability based on gender, age, marital status, education, occupation and income with regard to possible health effects on sub-groups. Finally, the social support literature can be criticised for the lack of recognised and accepted social relationship instruments with known reliability and validity, despite a proliferation of poor measures. At this stage in the development of this research area it is difficult to know what construct/s an instrument is measuring or if an instrument is tapping the construct it claims to measure. There have been extensive studies, as outlined previously, on both service use and social support and both groups of literature provide an insight into provision of care and impact on health and well-being of older adults despite their limitations. Inconsistencies across study findings may be due to the limitations outlined above. However, in order to comprehensively address the issues of care provision, it is more important to examine the interrelationship between service use and social support and

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this interrelationship is the focus of this section. Very little is currently known about this interrelationship between service use and social support.

The interrelationship between service use (formal service use) and social support (informal service use) is at present unclear. The extent to which formal and informal demands are made together or in a complementary manner and which services are used by whom is not yet known for participants of equal disease and disability. Identifying the conditions under which social support facilitates versus discourages the use of formal (community and medical) services is an important research agenda [148]. The debate as to whether social support either encourages or discourages the use of formal services is a significant one because it affects both policy and practice. If family, friends and neighbours do in fact act as a bridge or a link to the use of formal services then older adults with low social support are at risk of being marginalised. This scenario would indicate the need for the targeting of this “at risk” group through policies and interventions that bring them into contact with needed services. In effect policy-makers and practitioners would need to substitute for the “bridging” role normally played by social networks. If, on the other hand, family, friends and neighbours compensated for or in some way discouraged the use of formal services this would raise a different set of issues for policy-makers and practitioners. For example, which types of assistance are best provided by social networks and which types of assistance are best provided by formal services? In addition, the issue of carer burden and overburdening social networks would require greater attention, as well as the question of how older adults could be linked to formal services that would be of great benefit to them and their informal supporters (e.g. education and information campaigns and advertising). This thesis makes a significant contribution to new knowledge by providing greater insight into the relationship between service use and social support.

Paper six examines this relationship between unpaid social support and the use of formal health services, and in it two major mechanisms are tested [44]. The first mechanism, postulated by Cantor, is the “hierarchical compensatory” mechanism, which suggests that when social support is unavailable from the preferred social network the demands on formal services are increased [149]. This mechanism implies that once disease and disability are controlled, there will be a negative association between informal social support and formal service use. The second mechanism proposed by other researchers is termed the “bridging” mechanism [148, 150-152]. This mechanism proposes that because social networks bring individuals into contact with community and medical services where appropriate, as well as providing direct assistance, there will be a positive association between informal social support and formal service use. Therefore, in one mechanism, the relationship between unpaid social support and formal service use is viewed as being hierarchical and compensatory, and in the other this relationship is viewed as being complementary. The next section will discuss Cantor’s “hierarchical compensatory” mechanism in more detail and the following section will discuss the “bridging” mechanism proposed by other researchers.

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2.7.2 Cantor’s “Hierarchical compensatory” Mechanism Cantor views the support system of older adults as consisting of spouse, children, siblings and other relatives, friends, neighbours, and formal organisations [149]. She argues that the more important distinctions may be between kin (mainly children), non-kin (friends and neighbours) and formal organisations (or their paid representatives, including tertiary support givers as defined on page 436). In a study of 1,552 people aged 60 years or more living in the inner city of New York, Cantor assessed to whom older persons turned for social support (both formal and informal) and why. In order to examine what determines the role of various support providers of older adults, Cantor tested four alternative models of how the support system, both formal and informal, operates [149]. The first model is the “additive” model, whereby “each support element performs randomly chosen tasks which added together increase the social supports available to the elderly person” [149, p453]. The second is the “asymmetrical” model in which one element of support (e.g. kin, non-kin, formal) dominates all forms of support to the exclusion of all other elements. Neither of these two models is supported by research findings. The third model is the “task-specific” model which emphasises the nature of the task and the characteristics of the various support elements which are more suited to certain tasks. In this model, kin most appropriately carry out the traditional kin-associated tasks involving long-term history and intimacy. However, only tasks that do not require proximity or immediacy will be appropriate for kin due to the geographic dispersion of many children. In contrast, neighbours “can be expected to assist with tasks requiring speed of response, knowledge of and presence in the territorial unit” [149, p453]. Friends, on the other hand, are seen as uniquely in a position to deal with problems involving similarity of experience and history, and peer group status. The final model is the “hierarchical-compensatory” model which suggests that there is a hierarchy or an order of preference in the choice of the support element (kin, non-kin or formal). Kin are generally viewed as the most appropriate support providers, followed by significant others and lastly by formal organisations. Thus, “the function of support giving is generally ordered according to primacy of the relationship of the support giver to the elderly recipient rather than to the nature of the task” [149, p453]. Other elements of the support system act in a compensatory manner or as a replacement when the initially preferred element is absent. In order to test the four models of how the support system operates, a series of ten hypothetical critical incidents was developed [149]. For each hypothetical situation, participants were asked to whom, excluding a spouse, they would most likely turn for assistance. In the findings a hierarchical pattern emerged, with kin, preferably children, being clearly the support element of first choice. In addition to the hierarchical preference of kin over non-kin, there was also a compensatory nature to the functioning of the support system. Cantor states that “as the presence of a child becomes increasingly more removed, the support function begins to be shared by other relatives, friends, neighbours and even, in some cases, formal organisations” [149, p460]. The nature of the task was found to be an important factor in some specific instances, particularly in the areas of socialisation (loneliness and companionship) and money.

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However, Cantor concludes that “the hierarchical nature of support preference and the replacement or compensatory role of non-kin seem to be paramount” [149, p461] and she therefore postulates that a new model, the “hierarchical-compensatory” model, best fits the empirical data [149, p434]. The hierarchical compensatory mechanism postulates that older adults have an order of preference when choosing a caregiver and that this order of preference is based on the closeness of the relationship with the caregiver [153]. In this model, older adults prefer assistance from spouses in the first instance, then from children followed by other relatives, friends and neighbours. The use of formal services is only viewed as a last resort [153-154]. Logan and Spitze found some evidence for the hierarchical compensatory hypothesis [150]. They studied 554 people aged 60 years or more living in New York State. In their study, “people who live with a spouse or another person are less likely to use “other” community-based services, and people who receive help from adult children are less likely to use either these services or senior centers and meal programs” [150, pS33]. Xiaolian studied 120 chronic obstructive pulmonary disease patients with a mean age of 54.73 years living in Chengdu, China. Support for Cantor’s hierarchical compensatory mechanism was also found in this study. Participants first selected their spouse as a source of support, followed by adult children and then other family members [155].

On the other hand, Penning’s findings were inconsistent with the hierarchical compensatory mechanism. Penning interviewed 661 older adults aged 65 years and over living in British Columbia, Canada. As health declined, care was not first provided by informal carers and in the last instance by formal services. Rather, as need increased due to chronic illness and disability, the use of all forms of care (self, informal and formal) increased [6]. The hierarchical compensatory model has several major weaknesses [153] that may explain some of the findings listed in the recent studies cited above. First it assumes that the order of preference for choice of caregiver is not at all influenced by the nature of the task performed. Second it assumes a positive relationship between older adults and their kin whereby exchanges within social networks are always positive and beneficial to older adults. Third it ignores the dynamics of changing demographics by assuming that older adults live in traditional households with a spouse and/or children living within close proximity. Thus it ignores increases in the divorce rate and decreasing fertility rates resulting in the availability of fewer children to provide assistance. In addition, the increasing number of women in the full-time labour force is a factor frequently ignored when employing the hierarchical compensatory model of support. Finally, it ignores the impact of cultural and personal experiences with care providers and service agencies on the care-seeking patterns of frail older adults [153]. The influence of cultural and personal experiences with care providers on the care-

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seeking behaviours of older adults is significant. For example, if the care recipient is of a different cultural background than the care provider, the care recipient may be reluctant to seek sufficient/adequate levels of care due to cultural and language barriers. On the other hand, the care recipient from a different cultural background may choose not to use formal services and may rely on family members because of a stronger commitment to familial members or larger support networks. Luong states that “research findings indicate that the large, well connected, extensive, and long-lasting support networks among many African American elderly have contributed to their high reliance on informal community-based long-term care services, rather than formal long-term care services” [153, p2]. 2.7.3 The “Bridging” Mechanism Logan and Spitze [150] claim that the “bridging” mechanism was hypothesised by Sussman in 1976. Sussman does not use the term “bridging” but does refer to “family-bureaucratic organization linkages” and argues that family members act as facilitators, protectors, and mediators for older adult members in their efforts to handle the demands of institutional and organisational bureaucracies [152, p443]. The family continually engages in linkage activities with bureaucratic organisations on behalf of its older adult members. Children and relatives inform their older adult members about such things as housing, pensions, medical care and other available options and entitlements and in this way they act as information resources for older adults, linking them with formal services [152]. Logan and Spitze explain the “bridging” hypothesis in the following way: “People’s informal network may act as a bridge between the older person and formal services, bringing the person into contact with public service providers and thus facilitating formal care” [150, pS25]. People with stronger informal networks may make more use of formal services and thus informal social support is viewed as a possible enabler of formal service use [148, 151]. The “bridging” mechanism is sometimes called the linking mechanism [156]. This is because it is argued that the informal social network links older adults to formal services while simultaneously remaining greatly involved in assisting these older adults [154].

George refers to contradictory findings regarding the impact of social support on formal service use [148]. She indicates that some research supports the linking (bridging) hypothesis which argues that social support facilitates access and entry to formal service use, thus increasing it. Other research supports the hierarchical-compensatory hypothesis, which George terms the substitution hypothesis, suggesting that social support decreases the likelihood of formal service use because people turn to formal providers only when and if informal sources of social support are unavailable or unable to provide assistance. George [148] and Chappell [151] both found evidence for the “bridging” hypothesis in their studies. Chappell did not find evidence of a negative correlation

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between the three care systems of self-care, informal care and formal care. Instead of a “substitutability” between these care systems, Chappell found that they appeared to be “complementary, co-existing with one another” [151, p176]. The issue of “complementarity” was raised by Sussman, who explained it by indicating that older adults could receive assistance from formal services and in this way they would not become a burden on family members while still maintaining linkages with family [152, p422]. George asked a sample of 510 caregivers of older adults suffering Alzheimer’s disease or a related disorder about their use of eight community-based service programs relevant to management of dementing illness. Results from this study also support the linking or bridging hypothesis as there was a positive correlation between objective measures of social support and measures of formal service use [148]. Logan and Spitze mainly found evidence for the “hierarchical-compensatory” mechanism and only some evidence for the “bridging” mechanism. They found a positive correlation between living with others and home-based services and also between help from friends and use of other community-based services. These findings provide some support for the “bridging” hypothesis [150]. These results suggest a more complex reality than can easily be encompassed by current models of the relationship between informal social support and formal service use. Logan and Spitze conclude by highlighting the need for greater consideration of this complex relationship in future research [150]. As indicated above [see section 2.7.1], the relationship between informal social support and formal service use is at present unclear. It is not known whether the availability of informal support acts as an enabling factor, linking older adults to formal services, or whether it acts as a need factor, implying that if informal support is available older adults may not perceive a need for formal services [150]. The present study aims to examine the relationship between informal social support and formal service use and to test both the “hierarchical-compensatory” mechanism and the “bridging” mechanism in order to determine the circumstances under which each may apply. Paper six investigates whether there is a positive or negative association between various measures of community and medical service usage and various measures of informal social support [44]. In this paper, respondents were asked about any social network member who provided any social support (either ADL, IADL or mobility). The paper thus addresses a major limitation of past research which rarely takes the full informal social network into account [150]. 2.8 DISCUSSION, OBJECTIVES AND AIMS 2.8.1 Significance of the Project Aims The “old-old” age group, defined in this study as people aged 75 years and over, is the age group most in need in terms of disease, disability, service use and social support. This age group is experiencing the highest rates of growth of all age groups and will continue to do so into the foreseeable future [157]. In addition age, particularly

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advanced age, is significantly related to poor health, disability and service use. Therefore, it is the “old-old” age group that does and will increasingly experience disproportionately higher rates of disease and disability. Disease and disability mean greater dependency, especially on informal social networks in the form of social support and also on formal services. For these reasons it is imperative that accurate information on this advanced age group be available to policy makers and practitioners in geriatric medicine and gerontology. At present the lack of information on this age group in Australia and elsewhere represents a significant knowledge gap. This study sets two objectives to assist in filling this void. It provides information first on physical aspects of health, namely disease and disability and the relationship between them and second on social aspects of health, namely service use and social support and the relationship between them for people of advanced age. The broader objective of this study is to contribute towards the improvement of the health, well-being and quality of life of Australians aged 75 years and over. Improving understanding of the nature and interrelationships between disease, disability, service use and social support will enable policy makers and practitioners to allocate scarce resources to where they are most needed. For example, this study highlights the importance of neurodegenerative diseases and the fact that they result in greater levels of disability. An awareness of the emerging “age of neurodegenerative disorders” can assist the targeting of resources in policy and practice, which in turn should result in improved well-being and quality of life for people of advanced age who suffer from neurodegenerative diseases, as well as their carers. In a similar way the aims of this study to better understand the nature of disease, the relationship between disease and disability, the determinants of service use, the characteristics of social support and the relationship between service use and social support are critical. This information will assist in guiding funding and resource allocation to where it is most needed and in this way enhance the health, well-being and quality of life of people of advanced age. Each of these aims represents a significant knowledge gap with regard to community-dwelling Australians aged 75 years and older, particularly the way in which formal service use and informal social support interrelate. More specifically, an understanding of disease patterns at advanced ages can assist in targeting interventions and preventative campaigns for specific diseases and groups of diseases (e.g. neurodegenerative, systemic and psychiatric). In addition this knowledge enables research directions and priorities to be established that may lead to an understanding of the causes of prevalent diseases such as neurodegenerative diseases and hence to possible cures. Similarly, increased understanding of which specific individual diseases and groups of diseases lead to greater disability and hence greater service use and reliance on social support also greatly assists policymakers, practitioners and researchers. This knowledge is helpful for establishing funding priorities and policy directives, targeting interventions and directing research initiatives.

Another aim of this study is to find the determinants of service use in advanced age groups. This aim is significant because it allows the determination of service usage patterns and highlights those factors that predict and create demand for services. For

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example, in this study disease and disability were found to be the major determinants of service use. This knowledge assists in formulating policies that will assist people with disabilities and their carers. Similarly an understanding of the nature of social support among community-dwellers aged 75 years and over enables those groups most at risk to be identified. For example: are people over 75 years of age with low social support and therefore at greater risk of poorer health and low levels of well-being likely to be male or female and; does socio-economic status determine levels of social support? These issues and greater knowledge of groups at risk assists in the targeting of scarce resources to appropriate sectors of the community-dwelling Australian population aged 75 years and over and in this way may enhance the health, well-being and quality of life of this population and its most vulnerable, frail and/or dependent members.

Finally, the area about which possibly least is known is the relationship between

informal social support and formal service use. It would be valuable to know whether informal social support and formal service use complement each other, that is have a positive association, or whether they compensate for one another and thus have a negative association. For example individuals who use high amounts of social support may rely on few or no formal services in a “hierarchical compensatory” model. In this case these individuals and their carers may benefit from an education campaign aimed at making them aware of medical and community services that may greatly assist them and reduce carer burden. On the other hand, social networks may bring older adults into contact with or link them to formal medical and community services. In this case those older adults with low social support will need to be targeted in order to ensure that they have adequate access to such services. These are only two examples of the potential use of this information and, as was found in this study, it is possible that for some services and service groups Cantor’s “hierarchical compensatory” mechanism applies whereas for others the “bridging” mechanism applies. 2.9 CONCLUSION

This literature review raises a number of questions that will be addressed in the following papers. First, what is the prevalence of various clinically diagnosed diseases (neurodegenerative, systemic and psychiatric) in the SOPS sample? Paper one examines the disease patterns in an “old-old” population and the impact of age on disease prevalence. Second, what is the relative impact of particular diseases on clinician-rated disability? Paper two assesses which diseases have the greatest effect on clinician-rated disability. Paper three broadens the analyses in paper two by examining the contribution of clinically diagnosed individual diseases to three different measures of disability (i.e. clinician-rated, informant-rated or proxy and self-report). Paper three also examines the contribution to these three disability measures by groups of diagnoses (diseases), namely neurodegenerative, systemic and psychiatric. This paper analyses whether the contribution of disease to disability is more accurately assessed when information about disability is obtained by clinician, proxy or self-report. Fourth, what are the major determinants or predictors of formal/paid service use (i.e. medical services and community services) and of informal/unpaid service use or social

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support? Using Andersen’s behavioral model, paper four examines whether these determinants are disease and/or disability (i.e. need factors) or whether they are other socio-demographic variables that may enable participants to have greater service access (i.e. enabling factors) or may predispose participants to the need for greater service use (i.e. predisposing factors). Paper four also addresses the possibility that these determinants of service usage may be different for distinct types of services. Fifth, what are the characteristics and levels of various types of social support (i.e. instrumental, emotional, perceived and social involvement) received by community dwellers aged 75 and over? Paper five addresses this question as well as examining the socio-demographic variables associated with social support and the differences in levels of social support between men and women. Finally, what is the relationship between informal social support and the use of formal medical and community services? Paper six assesses the extent to which demand for informal social support and formal service use are compensatory and the extent to which they are complementary. In other words, does the relationship between informal social support and formal service use provide support for Cantor’s “hierarchical compensatory” mechanism or for the “bridging” mechanism? Paper six also examines which of twenty socio-demographic variables predict more or less formal medical and community service use and more or less social support.

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83

CHAPTER 3. PAPER 1 NEURODEGENERATIVE AND OTHER CHRONIC DISORDERS AMONG PEOPLE AGED 75 YEARS AND OVER IN THE COMMUNITY Louise M Waite1, G Anthony Broe1, Helen Creasey1, David A Grayson1, John S Cullen1, Brian O’Toole2, Dorothy Edelbrock1,3, Mathew Dobson1. 1. Centre for Education and Research on Ageing, Concord Hospital, Sydney, Australia. 2. Department of Public Health, University of Sydney, Sydney, Australia. 3. Centre for Social Change Research, School of Humanities and Human Services, Queensland University of Technology, Brisbane, Australia.

Medical Journal of Australia 1997; 167: 429-432.

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CHAPTER 4. PAPER 2 IMPACT OF CHRONIC SYSTEMIC AND NEUROLOGICAL DISORDERS ON DISABILITY, DEPRESSION AND LIFE SATISFACTION G Anthony Broe1, AF Jorm2, Helen Creasey1, David Grayson1, Dorothy Edelbrock1,3, Louise M Waite1, Hayley Bennett1, John S Cullen1, Barney Casey1. 1. Centre for Education and Research on Ageing, Concord Hospital, Sydney, Australia. 2. Psychiatric Epidemiology Research Centre, Australian National University, Canberra, Australia. 3. Centre for Social Change Research, School of Humanities and Human Services, Queensland University of Technology, Brisbane, Australia.

International Journal of Geriatric Psychiatry 1998; 13: 667-673.

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CHAPTER 5. PAPER 3 CLINICAL DIAGNOSIS AND DISABILITY AMONG COMMUNITY DWELLERS AGED 75 AND OVER: THE SYDNEY OLDER PERSONS STUDY Louise M Waite1, Helen Creasey1, David A Grayson1, Dorothy Edelbrock1,2, John S Cullen1, William S Brooks1, Barney J Casey1, Hayley P Bennett1, G Anthony Broe1,3. 1. Centre for Education and Research on Ageing, Concord Hospital, Sydney, Australia. 2. Centre for Social Change Research, School of Humanities and Human Services, Queensland University of Technology, Brisbane, Australia. 3. Prince of Wales Medical Research Institute, University of New South Wales, Sydney, Australia.

Australasian Journal on Ageing 2001; 20: 67-72.

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CHAPTER 6. PAPER 4 DETERMINANTS OF SERVICE USE AMONG THE ELDERLY: THE SYDNEY OLDER PERSONS STUDY GA Broe1,2, DA Grayson3, LM Waite2, H Creasey2, D Edelbrock2,4, HP Bennett2, WS Brooks2. 1. Prince of Wales Medical Research Institute, University of New South Wales, Sydney, Australia. 2. Centre for Education and Research on Ageing, Concord Hospital, Sydney, Australia. 3. Department of Psychology, The University of Sydney, Sydney, Australia. 4. Centre for Social Change Research, School of Humanities and Human Services, Queensland University of Technology, Brisbane, Australia.

Australasian Journal on Ageing 2002; 21: 61-66.

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CHAPTER 7. PAPER 5 CHARACTERISTICS OF SOCIAL SUPPORT IN A COMMUNITY-DWELLING SAMPLE OF OLDER PEOPLE: THE SYDNEY OLDER PERSONS STUDY Dorothy Edelbrock1,2, Laurie R Buys2, Louise M Waite1, David A Grayson3, G Anthony Broe1,4, Helen Creasey1. 1. Centre for Education and Research on Ageing, Concord Hospital, Sydney, Australia. 2. Centre for Social Change Research, School of Humanities and Human Services, Queensland University of Technology, Brisbane, Australia. 3. Department of Psychology, The University of Sydney, Sydney, Australia. 4. Prince of Wales Medical Research Institute, University of New South Wales, Sydney, Australia.

Australasian Journal on Ageing 2001; 20: 173-178.

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CHAPTER 8. PAPER 6 THE RELATION BETWEEN UNPAID SUPPORT AND THE USE OF FORMAL HEALTH SERVICES: THE SYDNEY OLDER PERSONS STUDY Dorothy Edelbrock1,2, Louise M Waite1, G Anthony Broe1,3, David A Grayson3,4, Helen Creasey1. 1. Centre for Education and Research on Ageing, Concord Hospital, Sydney, Australia. 2. Centre for Social Change Research, School of Humanities and Human Services, Queensland University of Technology, Brisbane, Australia. 3. Prince of Wales Medical Research Institute, University of New South Wales, Sydney, Australia. 4. Department of Psychology, The University of Sydney, Sydney, Australia.

Australasian Journal on Ageing 2003; 22: 2-8.

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CHAPTER 9. GENERAL DISCUSSION 9.1 THE PRINCIPAL SIGNIFICANCE OF FINDINGS 9.1.1 Introduction Older adults are not a homogenous group and old age may span thirty to forty years of life. There are several stages that older adults live through. The ‘young-old’ generally refers to individuals aged 65 to about 75 years, the ‘old-old’ comprise people aged 75 to about 85 years and finally, the ‘very-old’ or the ‘oldest-old’ refers to those aged 85 years and over [1]. SOPS examines older adults in the last two stages of life and hence includes considerable heterogeneity amongst individuals. This study is significant because very little is known about people aged 75 years and over. SOPS investigates a large random sample of community-based Australian older adults in this age group from a multidisciplinary perspective and as such it is unique. In Australia about 93 per cent of older adults aged 65 years and over live in the general community [2]. With such a large proportion of older adults living in the general community it is important to understand their disease patterns, disabilities, service use patterns and social support characteristics. This study has examined these aspects of community-dwelling older adults and has investigated some of the interrelationships between these factors. Even less is known about the relationship between disease and disability and the relationship between service use and social support in older adults aged 75 years and over than is known about the characteristics of disease, disability, service use and social support per se in this population. The ultimate aim of this research is to enhance the health, well-being and quality of life of older adults aged 75 years and over through improved knowledge and understanding. This discussion will first present the significance of the findings of papers one to three on disease and disability and second discuss the significance of the findings of papers four to six on service use and social support. Third, this discussion integrates the findings of the overall study within a model. Fourth, implications for practice and research are outlined and finally some unanswered questions are highlighted with suggestions for future research. 9.1.2 Disease and Disability

This thesis began by asking the question: What is the prevalence and pattern of various clinically diagnosed diseases in an ‘old-old’ population? Results indicate that neurodegenerative disorders have the largest and most significant increases with age. Systemic diseases on the other hand tended to decrease in prevalence with advancing age and low prevalences of depression and anxiety were found. This age-related increase in neurodegenerative disorders supports the hypothesis that neurodegenerative disorders will come to dominate the health care needs of older adults, particularly when combined with population ageing. There is an emerging new

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‘epidemic’ of neurodegenerative diseases [3-4] and possibly the most significant finding from this study is the central importance of neurodegenerative diseases to the future.

The identification of the importance of neurodegenerative diseases in this study

was enabled by the thoroughness, quality and comprehensiveness of the study’s methodology and design. Few other studies include a medical examination where clinicians diagnosed a broad range of diseases nor do they examine as broad a range of neurodegenerative diseases. The use of a community sample and clinician diagnosis in SOPS enabled a more accurate assessment of cognitive impairment than self-report, which is particularly unreliable for respondents with dementia. It also enabled a representative assessment of disease patterns without the selection bias found in hospital or medical record-based studies.

This thesis then asked the question: What is the relative impact of particular diseases on disability in this population? Results indicate that neurodegenerative diseases are prominent contributors to all measures of disability. As a group, neurodegenerative diseases have the largest impact on disability. A principle finding is that neurodegenerative diseases result in greater levels of disability and consequently they are the most likely to result in institutionalisation. Neurodegenerative diseases and syndromes are common in populations of older adults and one of the findings of this study is that these neurodegenerative diseases and syndromes are likely to be underestimated by self-report. A major recommendation of this study is that disability assessments should include assessments and diagnosis of neurodegenerative diseases [5]. While systemic diseases play an important role in disability, the neurodegenerative diseases and syndromes are under-recognised by self-report and yet are most strongly associated with severe disability. These findings provide further evidence to support the hypothesis that neurodegenerative diseases will come to dominate the health care needs of older adults.

In this thesis disease and disability were found to be the main determinants of formal service use and informal social support. More is known about disease than about the relationship between disease and disability. Results from this thesis show that although diseases are important, it is their associated disabilities which are the major determinants of service usage. Disability was found to be an important predictor of health and community service usage and of informal social support. Previous research has identified dependency, often measured by ADL or IADL dependencies, as associated with mental impairment. Howe reviews 21 studies of community care conducted in Australia between 1990 and 1995 and reports that “one aspect of dependency that was consistently identified in studies focusing on high need clients was the high proportions of such clients reported as having a mental impairment” [6, p123]. This summary of previous research supports the finding of this thesis that it is the neurodegenerative diseases that are most strongly associated with severe disability and thus dependency.

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9.1.3 Service Use and Social Support In relation to the social aspects of health it was found that disease and disability

are the main predictors of service use and social support. More specifically, disability mainly predicted unpaid social support and community service use, whereas both disease and disability predicted medical service use. In this thesis Andersen’s behavioural model was used to investigate determinants of service use and social support. However, the use of the behavioural model is far from ideal [7] and paper 4 questioned the utility of this model in examining the prediction of service usage, including social support [8]. It appears that the enabling and predisposing factors in the model play a far less important role in the prediction of service usage, including social support, than do the needs factors of disease and disability. If this is the case, future research on determinants of service use would do well to incorporate measures of disease and disability instead of, or in addition to, measures of sociodemographic variables assessed in previous studies. To date much Australian health services research has not included client characteristics [6], as SOPS did.

The characteristics of social support in a community-dwelling population of older adults aged 75 years and over in Australia were largely unknown before SOPS. A greater understanding of social support is of paramount importance at advanced ages because as disease and disability result in loss of independence, it is often the social network that older adults turn to for support. This study has shed some light on the nature and extent of social support in this population aged 75 years or more. A positive finding is that most respondents have adequate social support and are socially active. However, lower levels of social support are associated with increased age, male gender, single marital status and lower socioeconomic status. These groups of older adults may be at risk of poorer health and wellbeing because it is widely accepted that social support is protective against adverse health outcomes and low levels of wellbeing [9-23].

This thesis reveals important differences in social support between men and

women aged 75 years and over. Social networks provided women with more instrumental support than men and women reported having more providers of emotional support. Women also reported their daughters as major confidants, supporters and persons to be relied upon when ill and that they attended more groups, clubs and organisations than men. Men tend to nominate their spouse as their confidant and/or emotional supporter whereas women tend to nominate daughters and close friends. Men reported less emotional support than women and more men had no emotional supporters or confidant. These men may experience mental health difficulties and lower levels of well-being [17]. It is possible that these men will experience problems when their spouse dies or is incapacitated. Despite having lower levels of emotional support and social activity than women, men did not perceive their social support as being inadequate.

The ways in which formal service use and informal social support interrelate

have been made clearer by this study, though still little is known. This study explores

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the extent to which formal service use and informal social support are used together, complementing each other, and the extent to which they are used instead of each other, in a compensatory fashion. Paper 6 found that unpaid IADL social support and community IADL service usage are negatively correlated [24]. In other words, unpaid IADL social support is used when community IADL services are not used. This finding supports Cantor’s “hierarchical compensatory” model. In an attempt to explain this finding, it is possible that, because higher levels of education and socioeconomic status were associated with greater use of community services, older adults and/or their social networks are ignorant of the availability of community services. Another possible explanation is that this finding reflects the choice of older adults and/or their social networks. It was also found that unpaid ADL and IADL social support is used in combination with medical services, specifically days in hospital and ambulatory care visits [24]. This finding lends support to the “bridging” hypothesis. Of particular importance with regard to the cost of public hospital care is the finding that social isolation predicts more days in hospital. This finding confirms that “length of stay in hospital is not necessarily an indicator of the severity of the patient’s illness” and supports the contention that non-clinical factors can affect length of stay in hospital [25, p65]. Having fewer coresidents also predicted greater use of community services in SOPS. 9.1.4 Overall Findings The model in Figure 2 below provides a schematic overview of the findings of this study. Indicated by the letter A are the findings on the characteristics of disease. Results show that neurodegenerative diseases are prevalent in this population and that they increase significantly with age, unlike systemic diseases. Arrow number 1 indicates the finding that disease, particularly neurodegenerative disease, is disabling. Chronic disorders cause disability which in turn leads to increased depression and reduced life satisfaction [26]. Arrows 2 and 3 represent the finding that disease is a major predictor of both service use (particularly medical service use) and social support. Similarly, arrows 4 and 5 indicate that disability was also found to be a major predictor of service use (particularly community service use) and social support. Indicated by the letter B are the findings on the characteristics of social support. Results indicate that groups of older adults at risk of lower levels of social support and thus poorer health and wellbeing are those of more advanced age, male gender, single marital status and lower socioeconomic status [see section 9.1.3]. Findings also show significant gender differences in social support highlighting the heterogeneity of this group of ‘old-old’ people [see section 2.6.8]. Finally, arrows 6 and 7 represent findings on the relationship between service use and social support. Arrow 6 indicates that as IADL community service use increases, the use of IADL social support decreases (negative correlation) as predicted by Cantor’s ‘hierarchical-compensatory’ mechanism. On the other hand, arrow 7 indicates that as the use of medical services increases so too does the use of ADL and IADL social support (positive correlation) as predicted by the ‘bridging mechanism’ [see section 9.1.3].

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With regard to the relationship between service use and social support, there are a number of theories being advanced at present and research into this relationship is in its infancy. This study tested both the ‘hierarchical-compensatory’ mechanism and the ‘bridging’ mechanism and found that both were in operation in different instances. With regard to IADL community services it was found that these services are negatively correlated with IADL social support. This relationship indicates that older adults tend to use either IADL community services or IADL social support or, in other words, IADL community services are utilised when IADL social support is not. Therefore the ‘hierarchical-compensatory’ mechanism applies with regard to IADL community services. On the other hand, in relation to medical services it was found that these services are positively associated with both ADL and IADL social support. This relationship indicates that medical services tend to be used in conjunction with social support and that therefore the ‘bridging’ mechanism applies with regard to medical services. These findings indicate that different theories operate simultaneously for different types of services and different types of social support. Thus future research needs to test the various theories and disaggregate service use and social support into

B. Social

Support

Disability

A. Disease

Service Use

Particularly Neurodegenerative Diseases

1

4

2

3

5

Hierarchical-compensatory

Bridging 6

7

Figure 2: Diagrammatic Summary of Findings

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distinct types as was done in this study. Another theory that should be tested is the task-specific model which argues that the choice of provider will depend to a large extent on the nature of the task to be performed [27]. Findings from SOPS provide support for this theory because the source of assistance was found to depend upon the task involved. In a report to the Commonwealth Department of Veterans’ Affairs, Dent, Edelbrock and others found that formal services were by far the major source of assistance for personal care whereas respondents relied primarily on social support for household tasks [28]. Yet another possible explanation for the relationship between service use and social support is that when an older adult becomes ill or disabled they use more services and social support of all types [29]. Research into the relationship between service use and social support is still in its early stages and this study makes a significant original contribution to this body of knowledge by ascertaining when the ‘hierarchical-compensatory’ mechanism applies and when the ‘bridging’ mechanism applies. Paper six attempts to explain the associations found between service use and social support in this study. There are several possible explanations for the negative correlation found between IADL community services and IADL social support. This negative association may reflect choice or preference on the part of older adults and their support networks as implied by the ‘hierarchical-compensatory’ mechanism. On the other hand this association may indicate ignorance of the availability of community services which is supported by the fact that greater levels of community service usage were associated with higher levels of socioeconomic status and education. There are also possible explanations for the positive correlation found between medical services and both ADL and IADL social support. For example, it is possible that when older adults become ill or disabled, as indicated by their use of medical services, they simultaneously engage both ADL and IADL social support. Another possible explanation for the associations found between service use and social support is the potential influence of perceived availability of services on help-seeking behaviour. Perception of the availability of services on the part of older adults and/or their support network members may lead them to rely on social support if a service is perceived as unavailable or on the other hand if a service is viewed as readily available it may be more likely to be accessed. 9.1.5 Implications for Public Health, Practice and Research

The major significance of these findings from a public health point of view is that health and community services need to target those diseases that are both prevalent and disabling. This study identifies neurodegenerative diseases as both prevalent and disabling and as such it is recommended that they receive greater attention in the targeting and development of services and interventions. It must be remembered that SOPS investigates adults who are 75 years of age or more. Because disease and disability are associated with age, it is this group of older adults that is more likely to be frail and dependent and as such will require health and community services as well as informal social support in order to remain in the general community.

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Older adults are disproportionately high users of services as a group. For

example, in America, although older adults comprise just one eighth of the population, they use more than one third of total health care expenditure [7]. In Australia 42% of people aged 65 years and over living in the community expressed a need for some form of assistance to help them stay at home [25]. Because service use is associated with age the participants of this study will require even more assistance and use even higher proportions of expenditure on health care and aged care because of their more advanced age. This thesis identifies several groups of very old adults in need who should be targeted with regard to the development of services and interventions and in terms of resource allocation and also greater research attention:

• Older adults with neurodegenerative diseases and their carers • Individuals with disabilities, particularly as a result of neurodegenerative

diseases, and their informal support networks • Men, particularly those with no confidant and few or no emotional

supporters • Older adults with low socioeconomic status (low education, low

occupational status and low income) • Older adults with single marital status • People who have never married • Individuals in the 75 year and over category who are of even more

advanced age • People who are socially isolated with low levels of social support

This study confirms the hypothesis that non-fatal diseases with few modifiable

risk factors will gain in importance in populations of older adults. There is not enough recognition given to the cost, burden and disabling nature of neurodegenerative diseases. Mathers et al. have identified dementia as the third leading cause of disease burden amongst older Australians [30]. Possibly some reasons why neurodegenerative diseases are not more often identified as leading causes of disability are: (i) that they are often not considered as a group, (ii) that a broad range of neurodegenerative diseases is often not considered, and (iii) there are significant problems with diagnosing neurodegenerative diseases using self-report. These limitations have all been addressed by this study.

9.2 FUTURE RESEARCH

Further research is needed in particular in the area of the contribution of individual disease diagnoses to service use. In this study individual diseases were aggregated into a single disease endpoint for the purpose of examining the determinants of service use. Therefore there is a need to differentiate and examine the specific diseases that are the major predictors of service use. Because of the significant

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contribution of neurodegenerative diseases to disability, it is an important recommendation of this study that future research include cognitive and gait assessment as well as information on function from a proxy, given the unreliable nature of self-report in the case of neurodegenerative disease.

This study is by no means exhaustive in terms of the examination of the

interrelationships between disease, disability, service use and social support. Much more complex multidisciplinary research of the type conducted in SOPS is required in order to better comprehend the nature of the interrelationships between these four factors. This study has focused on the relationship between disease and disability, between disease, disability and service use and between service use and social support, however, there are many more possible combinations of interrelationships between these four factors. Similarly, the focus of the present study has been on the characteristics of disease and social support. Further research is required that examines the nature of disability and service use in community-dwelling populations of people aged 75 and over. 9.3 CONCLUSION

This study has highlighted the importance of neurodegenerative diseases in

advanced old age. Neurodegenerative diseases are both prevalent and severely disabling in this population. Disease and disability, particularly from neurodegenerative conditions, are the major predictors of service use and social support in this ‘old-old’ representative group of older adults. This study has contributed significantly to filling knowledge gaps regarding the nature of the relationship between disease and disability and that between service use and social support. In addition it has shed light on the nature of disease and social support in an Australian community-dwelling sample of people aged 75 years and over. These contributions to gerontological research are significant particularly in the light of population ageing, the large proportion of over 75 year olds living in the community and the substantial resources devoted to caring for people in this age group with diseases and disabilities, particularly as a result of neurodegenerative disorders.

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APPENDIX A1. NEUROLOGICAL SIGNS, AGING, AND THE NEURODEGENERATIVE SYNDROMES LM Waite1, GA Broe1, H Creasey1, D Grayson1, D Edelbrock1,2, B O’Toole3. 1. Centre for Education and Research on Ageing, Concord Hospital, Sydney, Australia. 2. Centre for Social Change Research, School of Humanities and Human Services, Queensland University of Technology, Brisbane, Australia. 3. Department of Psychiatry, University of Queensland, Brisbane, Australia.

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