SOCIAL SUPPORT AMONG RURAL COMMUNITY- DWELLING OLDER ADULTS AND ITS ASSOCIATION
WITH DEPRESSION AND QUALITY OF LIFE
TENGKU AMATULLAH MADEEHAH BINTI T MOHD
FACULTY OF MEDICINE UNIVERSITY OF MALAYA
KUALA LUMPUR
2019
SOCIAL SUPPORT AMONG COMMUNITY-DWELLING OLDER ADULTS AND ITS ASSOCIATION WITH
DEPRESSION AND QUALITY OF LIFE
TENGKU AMATULLAH MADEEHAH BINTI T MOHD
THESIS SUBMITTED IN FULFILMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR IN
PUBLIC HEALTH
FACULTY OF MEDICINE UNIVERSITY OF MALAYA
KUALA LUMPUR
2019
UNIVERSITY OF MALAYA
ORIGINAL LITERARY WORK DECLARATION
Name of Candidate: Tengku Amatullah Madeehah Binti T Mohd Name of Degree: Doctor of Public Health
Title of Project Paper/Research Report/Dissertation/Thesis (“this Work”):
Social support among community-dwelling older adults and its associations with health outcomes in Kuala Pilah, Negeri Sembilan.
Field of Study: Public Health
I do solemnly and sincerely declare that:
(1) I am the sole author/writer of this Work;
(2) This Work is original;
(3) Any use of any work in which copyright exists was done by way of fair dealing and for permitted purposes and any excerpt or extract from, or reference to or reproduction of any copyright work has been disclosed expressly and sufficiently and the title of the Work and its authorship have been acknowledged in this Work;
(4) I do not have any actual knowledge nor do I ought reasonably to know that the making of this work constitutes an infringement of any copyright work;
(5) I hereby assign all and every rights in the copyright to this Work to the University of Malaya (“UM”), who henceforth shall be owner of the copyright in this Work and that any reproduction or use in any form or by any means whatsoever is prohibited without the written consent of UM having been first had and obtained;
(6) I am fully aware that if in the course of making this Work I have infringed any copyright whether intentionally or otherwise, I may be subject to legal action or any other action as may be determined by UM.
Candidate’s Signature Date:
Subscribed and solemnly declared before,
Witness’s Signature Date:
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iii
SOCIAL SUPPORT AMONG RURAL COMMUNITY-DWELLING OLDER ADULTS AND ITS ASSOCIATIONS WITH DEPRESSION AND
QUALITY OF LIFE ABSTRACT
The ageing population has become a global phenomenon and is causing an increase in both the economic and healthcare burden in many countries worldwide. As people age, they become more dependent on the people around them. Lack of social support has been shown to be associated with increased mortality, poor physical and mental health, and poor quality of life. The overall aim of this study was to determine the association between structural social support and functional social support and two outcomes, namely depression and quality of life. This study consists of a systematic review and a cross- sectional study. First, a systematic review was conducted to critically analyse the literature on the association between social support and depression in the context of Asia.
Second, a cross-sectional study was conducted among 2324 community-dwelling older adults aged 60 years in Kuala Pilah district, Negeri Sembilan. The respondents for the cross-sectional study were recruited by multi-stage sampling and interviewed face-to-face using a structured questionnaire. Structural social support was measured using the Lubben Social Network Scale, functional social support using the Duke Social Support Index, depression using the Geriatric Depression Scale and quality of life was measured using the Short Form Heath Survey-12. The results of the systematic review showed that in 23 out of the 28 studies, higher social support was associated with reduced depression among community-dwelling older adults in Asia. The systematic review also highlighted the importance of the family as a source of support in reducing depressive symptoms in the older adults. The data gathered by the cross-sectional study was analysed using structural equation modelling (SEM). Activities of daily living were hypothesised to act as a
mediator between social support components and the outcomes of depression and quality of life, while age and chronic disease were treated as the confounders. Confirmatory factor analysis showed that support from family was the main indicator for structural social support. Older adults felt that having a role, being included in social groups, and having a confidant among family and friends were indicative of functional social support.
The results of the SEM showed that between the two components of social support, only
functional social support was found to be significantly associated with depression (b = -0.07), and quality of life (physical component (b = 0.08), mental component (b = 0.30)). In addition, the SEM showed that structural social support was associated
with functional social support (b = 0.05). Moreover, functional social support was also found to be significantly associated with both outcomes in both groups of older men and women. In conclusion, this study found that higher functional social support was associated with reduced depression and better quality of life. Older adults in Malaysia rely on family to provide for their social needs. Hence, social support should be optimised and be seen as an asset to the older adult as they age. Meanwhile, government policy and services must be geared towards assisting older adults who lack support from family to improve their quality of life.
Keywords: social support, depression, quality of life, community-dwelling, older adults.
v
SOKONGAN SOSIAL DALAM KALANGAN WARGA EMAS LUAR BANDAR DAN HUBUNGANNYA DENGAN KEMURUNGAN DAN KUALITI HIDUP
ABSTRAK
Penuaan penduduk telah menjadi fenomena global yang mengakibatkan peningkatan beban kepada ekonomi dan sistem kesihatan di kebanyakan negara di seluruh dunia.
Semakin seseorang itu berumur, semakin mereka bergantung kepada orang di sekitarnya.
Kekurangan sokongan sosial telah dikaitkan dengan peningkatan mortaliti, kesihatan fizikal dan mental yang lemah serta kualiti kehidupan yang rendah. Tujuan kajian ini adalah untuk menentukan hubungan antara struktur sokongan sosial dan fungsi sokongan sosial dengan dua hasil: kemurungan dan kualiti hidup. Kajian ini dibahagikan kepada dua bahagian. Pertama, ulasan literatur sistematik dijalankan untuk menganalisa secara kritis kajian yang mengkaji hubungan di antara sokongan sosial dan kemurungan di Asia.
Kedua, kajian secara keratan rentas telah dijalankan dalam kalangan 2324 orang warga emas berumur 60 tahun ke atas di dalam komuniti yang direkrut melalui persampelan pelbagai peringkat di daerah Kuala Pilah, Negeri Sembilan. Setiap responden ditemu bual secara bersemuka dengan menggunakan borang soal selidik. Struktur sokongan sosial diukur menggunakan Skala Rangkaian Sosial Lubben (Lubben Social Network Scale), fungsi sokongan sosial diukur menggunakan Indeks Sokongan Sosial Duke (Duke Social Support Index), kemurungan diukur dengan Skala Depresi Geriatrik (Geriatric Depression Scale) dan kualiti hidup diukur dengan menggunakan Soal Selidik Kesihatan Pendek 12-soalan (Short Form 12-item Health Survey (SF-12)). Hasil ulasan literatur sistematik mendapati 23 daripada 28 penyelidikan menunjukkan sokongan sosial yang tinggi mempunyai hubungan dengan kemurungan dalam kalangan warga emas di Asia.
Ulasan literatur sistematik ini menekankan peranan penting keluarga sebagai sumber sokongan dalam menurunkan gejala kemurungan dalam kalangan warga emas yang tinggal di komuniti di Asia. Data terkumpul daripada kajian keratan rentas dianalisa
menggunakan pemodelan persamaan struktur. Aktiviti kehidupan seharian telah diperkatakan untuk bertindak sebagai mediator di antara komponen sokongan sosial dan kemurungan serta kualiti hidup. Sementara itu, penyakit kronik dan umur dianggap sebagai faktor pembauran. Analisis faktor konfirmasi menunjukkan bahawa sokongan sosial daripada keluarga adalah indikator untuk struktur sokongan sosial. Warga emas berpendapat bahawa mempunyai peranan dalam keluarga, mengetahui apa yang berlaku dalam kalangan lingkaran sosial dan mempunyai pendengar dalam kalangan keluarga dan rakan-rakan merupakan indikator fungsi sokongan sosial. Keputusan pemodelan persamaan struktur menunjukkan bahawa di antara dua komponen sokongan sosial, hanya fungsi sokongan sosial didapati berkaitan dengan kemurungan (b = -0.07) dan kualiti hidup (komponen fizikal (b = 0.08), komponen mental (b = 0.30)). Sokongan struktur pula dikaitkan dengan sokongan fungsi (b = 0.05). Di samping itu, hubungan di antara sokongan sosial fungsi dan kedua-dua pemboleh ubah hasil adalah signifikan dalam kalangan warga emas lelaki dan wanita. Sebagai kesimpulan, peningkatan sokongan sosial persepsi mempunyai hubung kait dengan kadar kemurungan yang rendah dan kualiti hidup yang tinggi. Warga emas di Malaysia bergantung kepada keluarga untuk memberi keperluan sosial kepada mereka. Oleh itu, sokongan sosial yang ada perlu dipertingkatkan dan dijadikan sebagai aset kepada warga emas. Akan tetapi, bagi warga emas yang tidak mempunyai sokongan keluarga, dasar dan perkhidmatan kerajaan perlu membantu mereka meningkatkan kualiti hidup seiring dengan peningkatan jangka hayat.
Kata kunci: sokongan sosial, kemurungan, kualiti hidup, kehidupan dalam masyarakat, warga emas.
vii
ACKNOWLEDGEMENTS
Grace be to Allah for making it possible for me to finish this thesis. First and foremost, I would like to thank my dear parents for their sacrifice and the overwhelming support they have given me. Their tireless support has been a great motivation for me and has helped me to keep going. To my darling husband Asri, thank you for your understanding and constant encouragement. To my son Zayd, I hope that you will grow to become a person who loves knowledge. Thank you for welcoming me with a smile each day after work. I would also like to thank Qanitah, Alya and especially Maksu, for helping with babysitting. Mak and my in laws, thank you for your understanding these past few years.
To my supervisors, Associate Professor Dr Farizah Mohd Hairi and Professor Dr Claire Choo Wan Yuen, thank you for the guidance, laughter and the challenge. Not forgetting Professor Dr Noran Naqiah Mohd Hairi, our designated adopted supervisor, for your assistance. To Professor Dr Karuthan Chinna and Professor Dr Nooriah Salleh, your wisdom and knowledge has been priceless. To my seniors Raudah, Roslaili, Eliana, Shazana, Rajini, Norliana, thank you for giving me valuable advice. To Awatef and Sakinah, my ‘PEACE buddies’, Rosidah and Hafiz, I could not have done this without all of you. And finally, to my other colleagues (Alex, Chong, Ely, Firdaus, Peter, Rama, Sarbhan, Zetty) who constantly gave me the motivation to push forward, thank you!
In addition, I would like to acknowledge University of Malaya for supporting the Kuala Pilah Longitudinal Study in the form of funding (University of Malaya Grand Challenge Grant on Preventing Elder Abuse and Neglect Initiative (GC001B-14 HTM and GC001D-14HTM). Without strong research funding, we would not be able to collect valuable data and conduct important research. Last but not least, I would like to thank the Ministry of Education Malaysia for sponsoring my education, and my employer Universiti Sains Islam Malaysia for granting my study leave.
TABLE OF CONTENTS
Abstract ... iii
Abstrak ... v
Acknowledgements ... vii
Table of Contents ... viii
List of Figures ... xiii
List of Tables ... xv
List of Symbols and Abbreviation ... xviii
List of Appendices ... xxi
CHAPTER 1: INTRODUCTION ... 1
1.1 Chapter Overview ... 1
1.2 The Ageing Population ... 1
1.3 The Older Adult Population in Malaysia ... 5
1.4 Social Support ... 5
1.5 Depression and Quality of Life among Older Adults ... 7
1.6 Conceptual Framework of the Study ... 9
1.7 Problem Statement ... 11
1.8 Rationale for the Study ... 13
1.9 Research Questions ... 14
1.9.1 General Objective ... 14
1.9.2 Specific Objectives ... 15
1.10 Significance of the Study ... 15
1.11 Overview of the Thesis ... 16
ix
CHAPTER 2: LITERATURE REVIEW ... 18
2.1 Chapter Overview ... 18
2.2 Social Support ... 19
2.3 Mechanisms Linking Social Support to Depression and Quality of Life ... 21
2.4 Social Support and Depression ... 24
2.4.1 Introduction ... 24
2.4.2 Systematic Review on the Association between Social Support and Depression in Asia ... 29
2.4.2.1 Methodology ... 30
2.4.2.2 Results ... 34
2.4.2.3 Discussion ... 62
2.4.3 Conclusion ... 65
2.5 Social Support and Quality of Life ... 67
2.5.1 Introduction ... 67
2.5.2 Review of Literature Examining the Association between Social Support and Quality of Life ... 69
2.5.3 Conclusion ... 73
2.6 Government Policies and Social Support Studies in Malaysia ... 79
2.6.1 Introduction ... 79
2.6.2 Government Policies for Older Adults in Malaysia ... 79
2.6.3 Social Support Studies in Malaysia ... 81
2.6.3.1 Evidence on social support and depression ... 82
2.6.3.2 Evidence on social support and quality of life ... 87
2.6.4 Research Gaps ... 89
2.6.5 Conclusion ... 90
2.7 Review of Literature Examining the Relationships between Study Variables ... 92
2.8 Summary of the Literature Review ... 95
CHAPTER 3: METHODOLOGY ... 97
3.1 Chapter Overview ... 97
3.2 Study Design ... 97
3.3 Study Setting ... 97
3.4 Kuala Pilah Longitudinal Study ... 98
3.4.1 Author’s Contribution ... 99
3.5 Study Population ... 100
3.6 Sampling Method ... 100
3.7 Variables and Study Instruments ... 102
3.7.1 Exposure Variables ... 102
3.7.2 Outcome Variables ... 105
3.7.3 Independent Variables ... 107
3.8 Data Management ... 110
3.9 Statistical Analysis Procedures ... 110
3.10 Statistical Analysis ... 115
3.10.1 Descriptive Statistics ... 115
3.10.2 Structural Equation Modelling ... 115
3.11 Power Sample Calculation ... 120
3.12 Ethical Issues ... 122
CHAPTER 4: RESULTS ... 123
4.1 Chapter Overview ... 123
4.2 Socio-demographic Characteristics of the Study Population ... 123
4.3 Descriptive Characteristics and Bivariate Analysis ... 128
xi
4.3.1 Structural Social Support ... 128
4.3.2 Functional Social Support ... 131
4.4 Correlations between Social Support and Depression ... 133
4.5 Correlations between Social Support and Quality of Life ... 134
4.6 Structural Equation Modelling ... 136
4.6.1 Confirmatory Factor Analysis for Measurement Models ... 136
4.6.2 Multicollinearity ... 147
4.6.3 Path Analysis of Final Structural Model ... 148
CHAPTER 5: DISCUSSION ... 158
5.1 Chapter Overview ... 158
5.2 Introduction ... 158
5.3 Characteristics of the Study Population ... 159
5.4 Social Support, Depression and Quality of Life ... 168
5.4.1 Social Support and Depression ... 168
5.4.2 Social Support and Quality of Life ... 173
5.4.3 Reflection on the Mechanisms Linking Social Support to the Study Outcomes. ... 179
5.4.4 Gender Differences in the Association between Social Support and Depression and Quality of Life. ... 184
5.5 Other Findings ... 186
5.6 Summary of the Results ... 187
5.7 Strengths and Limitations of the study ... 188
5.7.1 Strengths of Study ... 188
5.7.2 Limitations of the Study ... 189
5.8 Implications of the Study Findings ... 191
5.8.1 Clinical Implications ... 191
5.8.2 Public Health Implications ... 192
CHAPTER 6: CONCLUSION ... 196
6.1 Chapter Overview ... 196
6.2 Conclusion ... 196
6.3 Recommendations ... 198
6.4 Future Research ... 201
REFERENCES ... 203
List of Publications and Papers Presented ... 234
APPENDIX A: Systematic Review Search Strategy Concepts and Keywords ... 235
APPENDIX B: Example of Search Protocol Performed in PubMed ... 236
APPENDIX C: Systematic Review Extraction Form ... 237
APPENDIX D: Newcastle-Ottawa Scale Assessment Form for Cross-sectional Studies ... 239
APPENDIX E: Weightage Calculation ... 243
APPENDIX F: Study Questionnaire in English ... 248
APPENDIX G: Study Questionnaire in Malay ... 259
APPENDIX H: Percentages of Missing Data ... 271
APPENDIX I: Ethical Approval from the Medical Ethics Committee University of Malaya ... 272
APPENDIX J: Histograms and Scatterplots for Descriptive Statistics. ... 273
APPENDIX K: Results of Complete Case Analysis ... 277
xiii
LIST OF FIGURES
Figure 1.1: Theoretical model of the pathway from social support to health. ... 10
Figure 1.2: Conceptual framework of the present study. ... 11
Figure 2.1: Pathways through which the social relationship affects health via the direct effects hypothesis. ... 22
Figure 2.2: The stress buffering hypothesis and its pathways in which social support influences responses to stressful events. ... 23
Figure 2.3: Social support framework. ... 33
Figure 2.4: PRISMA flow chart. ... 34
Figure 2.5: Conceptual framework of the present study. ... 96
Figure 3.1: Map of Negeri Sembilan and its districts. ... 98
Figure 3.2: Flow chart of sampling method. ... 101
Figure 3.3: Flow chart of the number of participants recruited and analysed in this study. ... 111
Figure 4.1: Marital status among older men and women. ... 126
Figure 4.2: Living arrangements of all participants, and by gender. ... 127
Figure 4.3: Conceptual framework for the structural equation modelling. ... 136
Figure 4.4: Initial measurement model for structural social support. ... 137
Figure 4.5: Final measurement model for structural social support. ... 138
Figure 4.6: Initial measurement model for functional social support. ... 140
Figure 4.7: Final measurement model for functional social support. ... 141
Figure 4.8: Initial measurement model for activities of daily living. ... 142
Figure 4.9: Final measurement model for activities of daily living. ... 143
Figure 4.10: Initial measurement model for the depression construct. ... 144
Figure 4.11: Final measurement model for the depression construct. ... 146
Figure 4.12: Results of multicollinearity between structural and functional measurement
models. ... 147
Figure 4.13: Significant and non-significant pathways of the full structural model. ... 148
Figure 4.14: Final structural model for the association of social support with depression and quality of life. ... 150
Figure 4.15: Final structural model for older adult men. ... 155
Figure 4.16: Final structural model for older adult women. ... 156
Figure 5.1: Conceptual framework and final model. ... 170
xv
LIST OF TABLES
Table 2.1: Systematic reviews of studies on social support and depression. ... 26
Table 2.2: Summary of studies included in the systematic review. ... 36
Table 2.3: Prevalence of depression among studies included in the systematic review. 41 Table 2.4: Score on Newcastle-Ottawa Scale for studies included in the systematic review. ... 42
Table 2.5: Social support measures used in the reviewed studies. ... 45
Table 2.6: Description of social support measures used in the reviewed studies ... 46
Table 2.7: Summary of findings for the association between social support and depression. ... 52
Table 2.8: Outcomes for the association between social support and depression in the reviewed studies. ... 55
Table 2.9: Summary of studies on the association between social support and quality of life. ... 74
Table 2.10: Current national policies and action plans for older persons in Malaysia. .. 80
Table 2.11: Summary of results from studies on social support and health outcomes among older adults in Malaysia. ... 84
Table 2.12: Summary of quality of life studies among older adults in Malaysia. ... 91
Table 3.1: Components of social support measured in this study. ... 105
Table 3.2: Category of depression based on the depression score. ... 106
Table 3.3: Operational definitions of covariates. ... 107
Table 3.4: Categories of cognitive impairment in the Mini Mental State Examination. ... 109
Table 3.5: Characteristics of participants who have missing data compared to those without missing data. ... 113
Table 3.6: Comparison of outcome measures between participants with missing and non- missing data. ... 114
Table 3.7: Model fit parameters. ... 118
Table 4.1: Socio-demographic profile of the study population. ... 125
Table 4.2: Number of children among the participants. ... 128
Table 4.3: Comparison of Lubben Social Network Scale scores by gender. ... 129
Table 4.4: Comparison of Lubben Social Network Scale scores by age groups. ... 129
Table 4.5: Distribution of participants’ answers to the items of the Lubben Social Network Scale. ... 130
Table 4.6: Distribution of participants’ answers to the items of the Duke Social Support Index. ... 132
Table 4.7: Comparison of Duke Social Support Index by gender and structural social support category. ... 132
Table 4.8: Social support scores among participants with different depression status. 134 Table 4.9: Correlation between social support and depression. ... 134
Table 4.10: Quality of life scores among participants, and by gender. ... 135
Table 4.11: Correlation between social support and quality of life. ... 135
Table 4.12: Inter-item correlation for the structural social support construct. ... 138
Table 4.13: Regression weights, AVE and CR values for structural social support. ... 139
Table 4.14: Inter-item correlation for the functional social support construct. ... 140
Table 4.15: Regression weights, AVE and CR values for functional social support. .. 141
Table 4.16: Inter-item correlation for the ADL construct. ... 142
Table 4.17: Regression weights, AVE and CR values for ADL. ... 143
Table 4.18: Inter-item correlation for items in the depression construct. ... 145
Table 4.19: Regression weights, AVE and CR values for depression construct. ... 146
Table 4.20: Regression weights for the full conceptual model. ... 149
Table 4.21: Regression weights for the final model. ... 151
Table 4.22: Results of path analysis of ADL as a mediator. ... 153
Table 4.23: Results for the unconstrained and constrained model for gender. ... 153
xvii
Table 4.24: Regression path coefficient by gender for unconstrained model. ... 157
LIST OF SYMBOLS AND ABBREVIATION
b : Standardised regression weight ADL : Activities of daily living AMOS : Analysis of moment structures AVE : Average variance extracted B : Unstandardized regression weight
B40 : Bottom 40% of the household income in the Malaysian population in terms of household income
CES-D : Centre of Epidemiological Studies Depression Scale CFA : Confirmatory factor analysis
CFI : Comparative Fit Index
CI : Confidence interval
Coef : Coefficient
CR : Composite reliability
CS : Cross-sectional
df : Degree of freedom
DoSM : Department of Statistics Malaysia
DSM-IV : Diagnostic Statistical Manual of Mental Disorder DSSI : Duke Social Support Index
DUFSS : Duke-UNC Functional Social Support Questionnaire
E : Standardised estimates
EB : Enumeration block
ELSA : English Longitudinal Study of Ageing
EQ-5D : European Quality of Life- Five Dimensions questionnaire EURO-D European Union Depression Scale
xix
EURO-D : European Union Depression scale GDS : Geriatric Depression Scale
GDS : Geriatric Depression Scale HAMD : Hamilton Depression Scale
IADL : Instrumental activities of daily living ICC : Interclass correlation coefficient IQR : Interquartile range
LQ : Living quarters
LSNS : Lubben Social Network Scale
MAR : Missing at random
MCAR : Missing completely at random
MCS : Mental Component Scale
MeSH : Medical Subject Heading MMSE : Mini Mental State Examination MNAR : Missing not at random
MOS-SSS : Medical Outcome Survey – Social Support Survey
MSPSS : Multidimensional Scale Perceived Social Support questionnaire NGO : Non-governmental organisation
NHMS : National Health Morbidity Survey
NOS : Newcastle Ottawa Scale
OPQOL : Old People Quality of Life Questionnaire
OR : Odds ratio
p : Probability
P.E. : Parameter estimates
PCS : Physical Component Scale
PRISMA : Preferred Reporting Items for Systematic Reviews
and Meta-Analyses
QOL : Quality of life
RM : Malaysian ringgit
RMSEA : Root mean square error of approximation
SD : Standard deviation
SE : Standard error
SEM : Structural equation modelling SF-12 : 12-item Short Form Health Survey SF-36 : 36-item Short Form Health Survey
SHARE : Survey of Health, Ageing and Retirement in Europe SPSS : Statistical Package for the Sciences
SSRS : Social Support Rating Scale Std E : Standardised estimate
TLI : Tucker Lewis Index
UK : United Kingdom
USA : United States of America WHO : World Health Organisation
WHO-QOL : World Health Organisation – Quality of Life Questionnaire WHOQOL-
BREF
: Abbreviated version of World Health Organisation Quality of Life Questionnaire
WHOQOL- OLD
World Health Organisation Quality of Life Questionnaire- Older adults
xxi
LIST OF APPENDICES
APPENDIX A: Systematic Review Search Strategy Concepts and Keywords ... 235 APPENDIX B: Example of Search Protocol Performed in PubMed ... 236 APPENDIX C: Systematic Review Extraction Form ... 237 APPENDIX D: Newcastle-Ottawa Scale Assessment Form for Cross-sectional Studies ... 239 APPENDIX E: Weightage Calculation ... 243 APPENDIX F: Study Questionnaire in English ... 248 APPENDIX G: Study Questionnaire in Malay ... 259 APPENDIX H: Percentages of Missing Data ... 271 APPENDIX I: Ethical Approval from the Medical Ethics Committee University of Malaya ... 272 APPENDIX J: Histograms and Scatterplots for Descriptive Statistics. ... 273 APPENDIX K: Results of Complete Case Analysis ... 277
CHAPTER 1: INTRODUCTION 1.1 Chapter Overview
The aim of this chapter is to provide a background on and rationale for this research.
First, the issue of global ageing is introduced followed by the description of the ageing population in Malaysia. From there, social support concepts relevant to this research are explained and how they are relevant to older adult’s lives are discussed briefly. A literature review on the association of social support and the outcomes of interest, is then summarised. Then, the problem statement, rationale, research questions and objectives for this research is outlined. This is then followed by an explanation of the significance of this study. Finally, the thesis overview is narrated in the last part of this chapter.
1.2 The Ageing Population
The world is witnessing an increase in life expectancy and a decline in birth rates.
Global fertility is predicted to fall from 2.5 children in 2025–2030 to 2.0 children in 2095–
2100 (United Nations Department of Economic and Social Affairs, 2015b). Women in high income countries who have higher education and higher income are having fewer children, and in middle-income countries a steady decline in fertility over recent years has also been observed (United Nations Department of Economic and Social Affairs, 2018). On the other hand, fertility rates in low-income countries, especially in African continent remains the same (Bongaarts, 2017). There has also been a reduction in early mortality, which is contributing to the ongoing increase in life expectancy (United Nations Department of Economic and Social Affairs, 2018). Indeed, globally, life expectancy is projected to increase from 70 years in 2010–2015 to 77 years in 2045–2050 (United Nations Department of Economic and Social Affairs, 2015b). The above- mentioned demographic changes are resulting in an increasing number of older adults globally and to the phenomenon of an ageing population that has triggered concern in many countries around the world.
2
According to the World Health Organisation (WHO) (World Health Organisation, 2011a), a person is defined as an older adult when they are aged 65 years and above.
However, this definition is usually applied in high-income countries. In low- and middle- income countries, an older adult is generally defined as a person who is aged 60 years old and above. A country is classified as having an ageing population when there is an increase in the proportion of older adults and a decline in the proportion of children and young people (World Health Organisation, 2011a). Globally, the number of older adults is projected to increase by 56% between 2015 and 2030, from 901 billion to 1.4 billion.
Furthermore, it is estimated that, by 2050, there will be 2.1 billion older adults, which is more than double the figure cited for 2015 (United Nations Department of Economic and Social Affairs, 2015a). However, concern has been expressed not only about the rise in the number of older adults, but also about the speed of the increase. In high-income countries such as France it took more than 100 years for the proportion of older adults to increase from 7% to 14%, which, in theory, should have given such countries enough time to adapt to the demographic change in the population. In contrast, Brazil, a middle- income country, will be home to the same percentage of older adults within just two decades. Therefore, low- and middle-income countries will need to find ways to adapt quickly to this demographic shift by developing policies for their older adult populations (United Nations Department of Economic and Social Affairs, 2015a).
This social transformation has multiple implications that range from a shift in the structure of the family to a higher burden on the healthcare system and greater financial challenges for governments (United Nations Department of Economic and Social Affairs, 2015a). As the number of older adults increases, the number of health problems will also rise. It is anticipated that, in particular, the prevalence of chronic and degenerative diseases will exceed that of infectious diseases. On the one hand, more people will suffer from non-communicable diseases such as heart disease, cancer and diabetes. On the other,
a greater proportion of the population will suffer from conditions such as dementia. In 2008, the WHO estimated that in high-income countries non-communicable diseases contributed to 86% of the burden of disease (World Health Organisation, 2011b). In contrast, in middle-income countries it accounted for 65% and in low-income countries for 37% of the disease burden. However, the WHO projects that in 2030 more than 50%
of the disease burden in low- income countries will be due to non-communicable diseases, and for more than 75% in middle-income countries (World Health Organisation, 2011b).
In addition, degenerative diseases such as dementia will also increase. In 2015, 46.8 million people were living with dementia, and it is anticipated that this figure will double every 20 years. Furthermore, it is estimated that in the year 2030, 74.7 million people will suffer from dementia, and this number will rise to 131.5 million in 2050 (Alzheimer’s Disease International, 2015). These projections give us a glimpse of the future burden and cost of healthcare that will affect healthcare systems around the world.
In response to the global ageing phenomenon and its consequences, in 2015, the WHO released a comprehensive publication entitled Global Strategy and Action Plan on Ageing and Health (World Health Organisation, 2015b). In that publication, the WHO recommended action in five priority areas: 1) committing to healthy ageing; 2) aligning health systems to cater for the needs of older populations; 3) developing systems for providing older adults with long-term care; 4) creating age-friendly environments; and 5) improving measurement, monitoring and understanding through research (World Health Organisation, 2015b). The WHO calls for governments all over the world to take action to address the issues on and around the ageing population. First, every government needs to focus on maintaining healthy ageing and on optimising the healthcare system. In the future, the healthcare system will need to be capable of providing services that encompass both the prevention and the management of advanced chronic conditions. In addition, systems for providing long-term care in support of quality of life, from capacity building
4
for later life to providing dignity in the end stage of life, should also be developed.
Moreover, older adults should also have access to age-friendly environments that enable them to remain as independent as much as possible. In addition to government action, activities that improve our understanding of the ageing population also need to be undertaken and the effectiveness of age-related programmes and policies needs to be monitored (World Health Organisation, 2015b).
The WHO places a particular emphasis on ensuring the healthy ageing of the population. The term ‘healthy ageing’ refers to maintaining the functional ability of an individual so as to enables well-being in old age (World Health Organisation, 2011b).
Essentially, it means that a person preserves their physical and mental capacities as they grow older. Measures to ensure healthy ageing include making changes to the environment to enhance access and being supportive of the varying needs and capacities of the older adults. The term ‘functional ability’ refers to the capabilities that enable an individual to perform the activities that they value (World Health Organisation, 2011b).
It is determined by the person’s intrinsic capacity and the environmental factors, and the interaction between them. A person’s intrinsic capacity is described as the abilities that a person can draw on which consist of physical and mental abilities. These abilities include the ability to see, hear, walk, think and remember (World Health Organisation, 2018b).
Environmental factors include policies, facilities, communities, technologies, culture, and relationships with other people (World Health Organisation, 2015a). These aspects are encompassed by the term ‘social support’, which is the focus of this research.
This study aims to determine the association between the social environment, specifically social support, and intrinsic capacity, specifically the mental health and quality of life of older adults. We are also interested in determining whether functional
capacity, in the form of activities of daily living (ADL), mediates this relationship. This study focuses on the older population in Malaysia.
1.3 The Older Adult Population in Malaysia
Malaysia, a country located in the Southeast of Asia, is an upper middle-income country with a total population of 32.8 million (Department of Statistics Malaysia, 2018b). In 2017, 6.2% of the Malaysian population were aged 65 years and above, equating to 1.9 million older adults. It is expected that in 2020, Malaysia will be categorised as a country with an ageing population and as an aged nation by 2035 (Department of Statistics Malaysia, 2016b).
The above increase in the proportion of older adults in Malaysia is in part due to the increase in life expectancy. In 2017, life expectancy in the country was 77.4 years among women and 72.7 years among men, compared to 76.8 years among women and 72.1 years among men in 2011 (Department of Statistics Malaysia, 2018b).
In 2014, older adults in Malaysia made an average of six visits to the physician per year. They were also admitted to hospital more and stayed in hospital longer compared to the general population (Institute for Health Systems Research & Institute for Health Policy, 2013). The above statistics indicate that something must be done to improve the health of older adults in Malaysia. One of the factors that seems to have a positive impact on health is social support.
1.4 Social Support
The impact of the social relationship on mortality was first reported by Berkman and Syme in 1979 based on a longitudinal study in which 6928 adults in Almeda County, California, United States of America (USA) were followed-up for nine years. The authors found that being married, having more contacts with close relatives and friends, being a
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church member and being active in informal and formal groups were associated with lower mortality rate (Berkman, L. F., & Syme, Berkman, & Syme, 1979). Since then, studies have explored the components of social relationships such as social support, social capital, and social participation.
Social support is a concept that describes the interaction between individuals and the exchange of resources among them (Cobb, 1979; Kaplan, Cassel, & Gore, 1977). This concept is important for older adults because as they age, they become more dependent on the people surrounding them to help them perform their daily tasks. Social support has been associated with mortality (Holt-Lunstad, Smith, & Layton, 2010), physical function (Everard et al., 2000), mental health (Kuiper et al., 2015; Schwarzbach, Luppa, Forstmeier, König, & Riedel-heller, 2014), and quality of life (Caetano, Silva, & Vettore, 2013).
Social support is defined as an exchange of resources between at least two individuals in which either one perceives it as intended to enhance the well-being of the recipient (Oxman, Berkman, Kasl, Freeman Jr, & Barrett, 1992). It has been described as two different constructs; structural versus functional (Shumaker & Brownell, 1984) and received versus perceived (Cobb, 1979). These constructs are defined as follows:
1. Structural social support refers to an individual’s organisational ties to other people and is measured by various factors such as size of social network, composition of social network, frequency of contact with network members, and multiplexity of the relationships between the individual and network members (Haber, Cohen, Lucas, & Baltes, 2007). Relationships that have frequent interaction and a ‘closeness’ are included in this measure. Superficial interactions such as one-off exchanges in a supermarket are not included.
2. Functional social support denotes the exchange of emotional, instrumental or tangible, informational and appraisal support (J. S. House, 1981; Thoits, 2016).
It is the qualitative aspect of social support and encompasses satisfaction with social support, having confidants, and social isolation (Schwarzbach et al., 2014;
M. Tajvar, 2015).
Moreover, functional social support has been further described by the constructs of received versus perceived (Cobb, 1979) social support, which can be measured as follows:
a) Received support: the reported exchange or utilisation of resources by an individual (Haber et al., 2007; Bert N Uchino, 2009).
b) Perceived support: a person’s potential access to social support when in need (Haber et al., 2007; Bert N Uchino, 2009).
Given the wide range of impacts that social support has on the older adult, including mental health and quality of life, it seems clear that more attention should be focused on optimizing this potentially beneficial resource.
1.5 Depression and Quality of Life among Older Adults
Depression is the most common mental health disorder suffered by older adults. It is a public health concern because of its association with increased risk of morbidity, decreased physical, cognitive and social function, risk of self-neglect and increased mortality (D. G. Blazer, 1982; D. G. Blazer, Hybels, & Pieper, 2001; Unsar, Dindar, &
Kurt, 2015). Depression not only has an effect on the individual, it also has an impact on the family and health services (Beekman et al., 2002). For instance, as a depressed older adult has an increased rate of physical decline, this causes them to become dependent on other people for basic daily functions (Kazama, Kondo, & Suzuki, 2011; Penninx,
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Leveille, Ferrucci, van eijk, & Guralnik, 1999). Family members then have to care for the older adult or engage informal care. A study conducted in Germany found that over a six- month period, the health utilisation cost among community-dwelling depressed older adults was 2.6 times higher than among those who were not depressed. The bulk of the cost was accounted for by inpatient treatment, informal care and out-patient non- physician services (Bock et al., 2014).
In 2015, the National Health and Morbidity Survey (NHMS) in Malaysia reported that 24% of older adults suffered from depression. The prevalence of depression in the rural areas was higher than in the urban areas at 30.3% versus 28.8%, respectively (Ministry of Health Malaysia, 2017c). Depression is often underreported in the country due to the stigma of diagnosis and lack of knowledge among family members that hinders their ability to detect symptoms among older adult family members. Left untreated, depression can lead to poor quality of life among older adults (Norhayati Ibrahim et al., 2013).
Quality of life is a multidimensional concept that encompasses health, physical, psychological, social and spiritual well-being (Farquhar, 1995; The WHOQOL Group, 1996). Generally, a person’s quality of life is gauged by asking them to rate their overall satisfaction in life with regards to the above-mentioned aspects. It is an important concept that has been catapulted onto centre stage due to the increase in life expectancy and ageing globally.
Historically, physicians focused on finding ways to help people live longer. However, it has been found that living longer is not necessarily better. Income, physical function, health, cognitive function, and ability to socialise are contributing factors to quality of life (Y. Chen, Hicks, & While, 2013). However, the relative importance of such factors is highly dependent on how each individual interprets what constitutes, for them, a good quality of life. That being said, having a good quality of life and a longer life expectancy
should go hand in hand. Studies to identify the factors that can improve the quality of life among older adults are needed in order for people to live a longer, happier and more fulfilled life. In a survey conducted in Ireland, 89% of older adults reported having a good quality of life despite only 14% of them being free from medical conditions (Garavan, Winder, Mcgee, & O’Boyle, 2000). Therefore, in light of the above discussion, this study focuses on the impact of social support on quality of life.
1.6 Conceptual Framework of the Study
This section provides an overview of the conceptual framework developed for this study. The conceptual framework is based on the literature and is further elaborated in Chapter 2 Section 2.6. The framework is primarily based on the work of Berkman et al.
who presented a conceptual model of how social network and social support affect health.
Their model describes a cascading causal process beginning with the macro-social and ending with the psychobiological processes that are linked dynamically. The macro level contains the social and structural conditions, which include culture, socio-economic factors, politics and social change. This macro level conditions the nature of the mezzo level, which contains structural social support (Lisa F. Berkman, Glass, Brissette, &
Seeman, 2000). The macro and mezzo levels are termed ‘upstream factors’. The social network described by Berkman et al. (2000) contains structural social support and its characteristics. Structural social support operates at the behavioural level by provision of social support, social influence, social engagement and accessibility to resources and material goods (Lisa F. Berkman et al., 2000). The ‘downstream factors’ consist of psychosocial mechanisms (micro level) which influences health through three pathways:
1) psychological pathways, 2) health behavioural pathways and 3) physiologic pathways.
Social support is embedded in psychosocial providing instrumental, informational, appraisal and emotional support mechanisms (i.e. functional social support) (Lisa F.
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Berkman et al., 2000; Sheldon Cohen & Syme, 1985; J. S. House, 1981). The model is depicted in Figure 1.1.
Figure 1.1: Theoretical model of the pathway from social support to health.
(Lisa F. Berkman et al., 2000)
Individuals have friends and family who are subjected to norms, peer pressure and social restrictions that influence health behaviour. Integration produces stability of the psychological state through the sense of belonging, purpose and security. A positive psychological state results in better self-care, reduces psychological negativity and enhances immune suppression (Cassel, 1976; Bert N. Uchino, 2006). This is also known as the direct effect hypothesis, whereby social support enhances health and well-being irrespective of health (Sheldon Cohen, 1988; Sheldon Cohen & Syme, 1985; J. S. House, 1981).
The current study adopts the above theoretical model to examine the direct association between structural social support and functional social support and two outcomes:
depression and quality of life. In the framework, structural social support is associated with functional social support. Also, activities of daily living acts as a mediator between social support and the outcomes of depression and quality of life. In addition, age and the
Social-structural conditions
(Macro)
Social- networks
(Mezzo)
Psychosocial Mechanism
(Micro) Pathways
Upstream Downstream
•Culture
•Socioeconomic factors
•Politics
•Social change
•Structural social support
•Characteristics of network ties
•Functional
social support •Health behavior pathways
•Psychological pathways
•Physiologic pathways
number of chronic diseases were included as confounders due to their hypothesised association with both exposure and outcomes. Gender is also considered to act as a moderator in the framework for this study. Further elaboration of the conceptual framework including evidence from the literature can be found in Chapter 2 under Section 2.7. The conceptual framework for the current study is illustrated in Figure 1.2.
Figure 1.2: Conceptual framework of the present study.
1.7 Problem Statement
The increasing ageing population leads to an increase burden on healthcare services.
In Malaysia, the prevalence of mental health showed an increasing trend from 10.7% in 1996 to 29.2% in 2015 (Ministry of Health Malaysia, 2015b). Depression is the most common mental health disorder affecting older adults in Malaysia. In 2015, 24% of older adults suffered from depression, which approximates to 462,000 older adults suffering from geriatric depression (Ministry of Health Malaysia, 2017c). This number grows yearly with the increasing number of older adults and increasing prevalence of depression.
Social Support
Age Chronic disease
Depression
Quality of life Activities of
daily living Gender
Structural Social Support
Functional Social Support
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Consequently, the expenditure on mental health is also increasing yearly. In 2015, expenditure on mental health amounted to 268 million Malaysian ringgit (RM), an increase from RM238 million in 2014 (Ministry of Health Malaysia, 2017b). The provision of services to manage older adults suffering from depression is required and ongoing. For example, in 2015, there were 58,041 attendances at out-patient specialised geriatric psychiatric clinics and a community-based specialist mental health services was launched (Ministry of Health Malaysia, 2017b). Given the growing ageing population in Malaysia, it seems a foregone conclusion that the demand for specialised healthcare for depression will only increase and become a burden on the healthcare system unless steps are taken to reduce the rate of incidence of depression among older adults.
Furthermore, an increase life expectancy does not necessarily go hand in hand with an increase in quality of life. Studies have shown than quality of life peaks between 60 to 70 years old and thereafter declines with increasing age (Barrett, Burke, Cronin, Hickey, &
Kamiya, 2011; Ward, McGarrigle, & Kenny, 2018). Older adults with poor quality of life require more attention in terms of healthcare costs or assistance in performing daily activities. Quality of life scores among older adults in Malaysia range from 47-55 for the physical component, 50-63 for the mental component, and stands at 59 for overall mean score (Norhayati Ibrahim et al., 2013; Sazlina Shariff Ghazali, Zaiton Ahmad, Nor Afiah Mohd Zulkefli, & Hayati Kadir Shahar, 2012; Zin et al., 2015) out of a possible total of 100. Therefore, research is needed to determine whether factors other than health that can assist in improving the quality of life among older adults in Malaysia.
1.8 Rationale for the Study
Given the increasing number of older adults in Malaysia, the government must take action to enhance the health and quality of life of this growing portion of the population.
Social support is a part of the environmental factor that contributes towards healthy ageing. However, social support is often forgotten by healthcare professionals in Malaysia as the healthcare services lens is often focused on diseases. The older adult health screening questionnaire does not include questions on social support. This implies that an opportunity for social intervention is being missed. Although family support is considered to be a norm of Malaysian culture, the characteristics of social support and its impact on older adults has not been studied adequately.
As social support influences multiple outcomes, including physical health, mental health, mortality and quality of life, the development and implementation of a policy focusing on social support may prove to be a cost-effective strategy for enhancing health and well-being at the population level (Annear et al., 2012). Family members, friends and community are sources of social support that should be utilised. Previous studies that investigated social support among older adults in the Western countries identified that support from friends is associated with health (Schwarzbach et al., 2014). However, this is not the case in Asia, as some studies have shown that support from family is more important than that from friends in terms of its the association with health (LaFave, 2017).
These differences across cultures indicate that the characteristics of social support required by Malaysian older adults needs to be explored specifically in order to understand the needs of this population better. Furthermore, rural older adults in Malaysia are at increased risk of poor health due to having lower income, education, and access to facilities compared to their urban counterparts (J. K. L. Teh, Tey, & Ng, 2014). Therefore,
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the purpose of this study is to describe the characteristics of social support among the rural population of community-dwelling older adults in Malaysia.
1.9 Research Questions
In light of the foregoing, this study aims to answer these following five research questions:
1. What is the evidence available for examining the association between social support and depression in Asia?
2. What are the characteristics of social support among rural community-dwelling older adults in Malaysia?
3. Is there an association between structural social support and functional social support and the outcome of depression among rural community-dwelling older adults in Malaysia?
4. Is there an association between structural social support and functional social support and the outcome of quality of life among rural community-dwelling older adults in Malaysia?
5. Does structural social support have a stronger association than functional social support with depression and quality of life?
From the research questions, the general and specific study objectives were determined and are outlined in the following section.
1.9.1 General Objective
The general objective of this study to examine the characteristics of social support and their associations with health outcomes among rural community-dwelling older adults in Kuala Pilah district, Negeri Sembilan, Malaysia.
1.9.2 Specific Objectives
In order to answer the above research questions and achieve the above-mentioned general objective, this study aims to meet the following five specific objectives:
1. To conduct a systematic review of the literature on social support and depression among community dwelling older adults in Asia.
2. To describe the characteristics of structural social support and functional social support among rural community-dwelling older adults in Kuala Pilah, Negeri Sembilan.
3. To identify the associations between social support and depression among rural community-dwelling older adults.
4. To identify the associations between social support and health-related quality of life among rural community-dwelling older adults.
5. To determine whether structural social support or functional social support is more important in terms of the association with depression and quality of life.
1.10 Significance of the Study
By providing evidence on the impact of social support on depression and quality of life, it is hoped that this study will help to convince policy makers of the need to give more attention to social support for older adults and to provide the necessary financial investment for the provision of social support services. It is also hoped that results of this research will be a factor in fostering a closer collaboration between the Department of Social Welfare and the Ministry of Health that will enable a holistic and seamless approach to provision of the services needed by older adults in Malaysia. In addition, it is hoped that this research will help healthcare professionals to gain a greater comprehension of the role that social support can play in alleviating depression and improving the quality of life of the older adult population.
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1.11 Overview of the Thesis
The thesis is divided into six chapters as described below.
Chapter 1 is the introductory chapter that introduces the whole research. A summary of the background to this research as the conceptual framework, problem statement, research questions and objectives are described in this chapter.
Chapter 2 presents the results of a systematic review of existing studies on the association between social support and depression among community-dwelling older adults in Asia. The results of a literature review on the association between social support and quality of life are also presented. In addition, the studies on social support that have been conducted specifically in Malaysia are summarised in this chapter.
Chapter 3 describes the methodology adopted for this research study. The study population as well as the processes employed for data collection, data management and statistical analysis are described in detail. The procedures adopted to analyse missing data analysis and the handling of missing data are also described in this chapter.
Chapter 4 presents the results of the research. This chapter is divided into two sections.
The first section describes the socio-demographic characteristics of the population and the characteristics of social support. The second presents the results of the structural equation modelling (SEM) analysis.
Chapter 5 contains a critical discussion of the results in the light of the research objectives. The characteristics of social support in the study population are compared with those found in previous studies. In addition, the results on the associations between social support and the outcomes of depression and quality of life are explained and related to the literature. Then, the study strengths and limitations of this study are highlighted and
the implications of the study for policy and public health are discussed with the aim of providing insights on the application of this research in the Malaysian context.
Chapter 6 concludes the thesis by providing a summary of the findings.
Recommendations and suggestions for future research directions are also presented in this final chapter.
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CHAPTER 2: LITERATURE REVIEW 2.1 Chapter Overview
The main purpose of the literature review conducted for this study was to explore the two main concepts of social support, namely, structural social support and functional social support. Through this review we aimed to ascertain how previous researchers measured these two concepts. We also synthesised the previous findings regarding the impacts of structural social support and functional social support on the two outcomes of interest to this study, namely, depression and quality of life. The results of the literature review are presented in five sub-sections. First, Section 2.2 provides an overview of the two main social support concepts. Following that, Section 2.3 explains the two mechanism by which social support affects depression and quality of life, namely the direct effect and the stress-buffering effect.
Next, Section 2.4 presents the results of a review of the literature on the association between social support and depression, with a particular focus on Asia. To this end, a systematic review was performed to gather data on this issue in relation to Asia because, in contrast to the West, the association between social support and depression has not yet been established. Moreover, there seem to be differences between the two contexts. The systematic review of studies on social support and depression in Asia is followed by a general review of the literature on the association between social support and quality of life, the results of which are presented in Section 2.5. This review encompasses studies that have been conducted around the world. The findings of these studies are discussed by country and by region, including the Southeast Asian region.
Then, Section 2.6 provides an overview of the social support policies that are currently in place in Malaysia. It then focuses specifically on reviewing the social support studies that have been conducted in Malaysia, which is the context of the current study. Section
2.7 describes the literature review of the associations between the study variables. Finally, in Section 2.8, a summary of this chapter is presented and the conceptual framework for this study is proposed. This framework is used as the basis for the analysis conducted by this study.
2.2 Social Support
Social support and its relationship with health have been studied with great interest by researchers around the world for the past 40 years (Lisa F. Berkman, 1984; Cobb, 1979;
James S. House, 1987; Thoits, 2016; Bert N Uchino, 2009; Bert N Uchino, Bowen, Carlisle, & Birmingham, 2012). As previously mentioned in Chapter 1, social support can be divided into structural social support and functional social support. Structural social support consists of the structural dimension of a person’s network (Sherbourne & Stewart, 1991). The term ‘structure’ is used to describe the existence, quantity and the interconnectedness of the social ties of an individual, which is also known as a person’s social network (Sherbourne & Stewart, 1991). The term is also used to refer to the stable social relationships patterns of an individual within their social network (Wills & Shinar, 2000). These relationships can include those with a spouse, with children, with other family members and with friends, and the pattern of these relationships are affected by the number of such people in a person’s life (Haber et al., 2007; Sherbourne & Stewart, 1991). It is important to note that the term ‘social network’ is used to describe the ties that represents the relationships between individuals and, strictly speaking, it is viewed as a separate concept from social support (Wills & Shinar, 2000). Social network analysis describes the existing relationships in a person’s social network using quantitative methods (Wills & Shinar, 2000). The social network is a measure of structural social support. For the purpose of clarity, in this thesis, the term ‘structural social support’ is used and we refer to the articles that use this terminology specifically where possible.
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However, at the same time, the contribution of social network analysis to the knowledge on structural social support is recognised.
In general, the greater the number of people in a person’s network the better their structural social support. However, there are more network features that may be relevant to health. While structural social support can be measured by the number of individuals in a person’s network, it can also be measured by the number of people living nearby that a person can depend on. This measure is commonly defined as the ‘proximity of contact’
(Lisa F. Berkman, 1984; Gallo, 1984). This measure is used to determine whether the individuals who are near enough for an older adult to contact are available if needed. This measure can be further refined by calculating the number of people that the older adult can confide in or ask for help (J Lubben, 2000).
In addition, the extent of structural social support can also be measured by living arrangements and frequency of contact. There are several categories of living arrangements which are categorised according to the person(s) with whom an individual lives with, such as a spouse, spouse and children, other family members, and others, or the person may live alone. Frequency of contact refers to the number of direct (face to face) or indirect (e.g. telephone) contacts that a person has in an average week. The frequency of contact indicates the extent of a person’s access to the other people in their life (Gallegos-Carrillo et al., 2009; Litwin & Stoeckel, 2014; J Lubben, 2000).
On the other hand, the concept of functional social support has two components:
received social support and perceived social support. The term ‘perceived social support’
refers to a person’s potential access to social support, while the term ‘received social support’ refers to the reported exchange or utilisation of social support resources by an individual (Haber et al., 2007; Bert N Uchino, 2009). Perceived social support measures the individual’s perceptions on the general availability of support. In determining the level
of received social support the individual is asked to recall instances where specific support was provided. This type of social support is usually received during stressful events and is thus prone to recall bias. Therefore, it is believed that perceived social support can provide a more accurate assessment of functional social support (Haber et al., 2007; Bert N Uchino, 2009). In the light of the above, this study focuses on perceived social support.
2.3 Mechanisms Linking Social Support to Depression and Quality of Life The direct effect hypothesis and stress-buffering effects hypothesis have been commonly used in the literature to explain the connection between social support and health (Sheldon Cohen, 1988; J. S. House, 1981). The direct effect hypothesis proposes that social support enhances health and well-being, irrespective of stress level (Sheldon Cohen & Syme, 1985). Individuals who have social support are subjected to norms, peer pressure and social restrictions that influences health behaviour. Having social support produces stability in the psychological state through a sense of belonging, purpose and security. The positive psychological states results in better self-care, reduced psychological negativity, and enhanced immune suppression (Cassel, 1976; Bert N.
Uchino, 2006). A higher level of structural social support also increases informational support which benefits the individual in terms of, for instance, access to medical services, thus resulting in positive health behaviours. Family and friends also provide instrumental social support such as clothing, food and housing, thereby preventing disease and limiting exposure risks (Sheldon Cohen, Gottlieb, & Underwood, 2000).
The stress-buffering hypothesis explains how social support buffers the impact of stress or adverse events that may otherwise affect health and well-being. Stressful events cause a stress reaction and leads to serious disruptions in the neuroendocrine and immune system which predisposes a person to ill health (Sheldon Cohen & McKay, 1984). The hypothesis suggests that social support may intervene at two different points. First, it may
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occur after the stressful event and before the stress reaction by giving a person the confidence to cope. Due to the availability of social support the individual perceives that the stressful event is manageable as resources are available. Second, social support can intervene between the experience of stress and the onset of pathological outcomes. Social support alleviates the impact of the stressful event by reducing the perceived importance of stress, dampens the physiological reaction to stress, or prevents or changes the maladaptive behavioural responses (S. Cohen & Wills, 1985; Sheldon Cohen et al., 2000).
In addition, good social support enhances resilience in the elderly when they pre-date adversity by enabling self-continuity and minimising stigmatisation resulting from the adverse event (Blane, Wiggins, Montgomery, Hildon, & Netuveli, 2011).
Figure 2.1 shows the pathways of the direct effects hypothesis and Figure 2.2 depicts those of the stress-buffering hypothesis. The stress-buffering effect model has been found to be less consistent than the main effect model (Lakey & Orehek, 2011; Maryam Tajvar, 2015; Thoits, 2011). Therefore, we have chosen to focus on the main effect model.
Figure 2.1: Pathways through which the social relationship affects health via the direct effects hypothesis (adapted from Underwood (2000)).
Social support
Services Information Psychological States
Health Promoting Behaviours
Neuro- endocrine Response
Physical Disease Psychiatric Disease
Health-relevant Biological Influences Social
influence
Figure 2.2: The stress buffering hypothesis and its pathways in which social support influences responses to stressful events.
(Source: S. Cohen, Underwood, & Gottlieb (2000)) Perceived Availability
of Social Resources
Perceived Received Social Resources
Perceived Received Social Resources
Stressful events
Appraisal of demands and of adaptive capacities
Perceived stress
Benign appraisal
Negative cognitive and emotional response
Physiological or behavioural responses
Physical disease
Psychiatric disease
