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Unpacking self-rated health and quality of life in older adults and elderly in India: a structural equation modelling approach
Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Epidemiology and Global Health. Vadu Rural Health Program, KEM Hospital Research Center, Pune, India .
Behavioural Science Institute, Radboud University, Nijmegen, The Netherlands.
Umeå University, Faculty of Medicine, Department of Public Health and Clinical Medicine, Epidemiology and Global Health.ORCID iD: 0000-0003-0556-1483
Vadu Rural Health Program, KEM Hospital Research Center, Pune, India .
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2014 (English)In: Social Indicators Research, ISSN 0303-8300, E-ISSN 1573-0921, Vol. 117, no 1, 105-119 p.Article in journal (Refereed) Published
Abstract [en]

The Study on global AGEing and adult health (SAGE) aims at improving empirical understanding of the health and well-being of older adults in low- and middle-income countries. A total of 321 adults aged 50 years and older were interviewed in rural Pune district, India, in 2007. We used Structural Equation Modelling (SEM) to examine the pathways through which social factors, functional disability, risk behaviours, and chronic disease experience influence self-rated health (SRH) and quality of life (QOL) amongst older adults in India. Both SRH and QOL worsened with increased age (indirect effect) and limitations in functional ability (direct effect). QOL, socio-economic status (SES), and social networking had no significant effect on SRH. Smoking was associated with the presence of at least one chronic illness, but this did not have a statistically significant effect on SRH. Higher social networking was seen amongst the better educated and those with regular income, which in turn positively affected the QOL rating. QOL had a direct, but statistically not significant, effect on SRH. In conclusion, the indirect effects of age on SRH mediated through functional ability, and the effects of SES on QOL mediated through social networking, provide new understanding of how age and socio-economic status affect SRH and QOL. By allowing for measurement errors, solving for collinearity in predictor variables by integrating them into measurement models, and specifying causal dependencies between the underlying latent constructs, SEM provides a strong link between theory and empirics.

Place, publisher, year, edition, pages
Springer, 2014. Vol. 117, no 1, 105-119 p.
Keyword [en]
Self-rated health, Quality of life, Functional ability, Social networking, Structural equation modeling
National Category
Public Health, Global Health, Social Medicine and Epidemiology
Identifiers
URN: urn:nbn:se:umu:diva-80263DOI: 10.1007/s11205-013-0334-7ISI: 000334178600006OAI: oai:DiVA.org:umu-80263DiVA: diva2:647971
Available from: 2013-09-13 Created: 2013-09-13 Last updated: 2017-12-06Bibliographically approved
In thesis
1. "In general, how do you feel today?" Self-rated health in the context of aging in India.
Open this publication in new window or tab >>"In general, how do you feel today?" Self-rated health in the context of aging in India.
2013 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Background Most aging research comes from the developed world. Aging research in India is focused on disease states and risk factors. Evidence on elderly health, physical performance and disability to understand the psycho-social or socio-behavioral risk is limited in India. Self-rated health (SRH) is used often in survey settings to quickly assess health status and is known to predict morbidity and mortality. The first wave of the Study on global AGEing and adult health (SAGE) survey provides an opportunity to explore the complex construct of SRH in the context of the aging process in its various key life domains of health, disability, cognition, activities of daily life, work, family, security and well-being in low and middle income settings.

Objectives This research aims to (a) understand pathways through which the social environment, functional disability, health behaviour and chronic disease experience influence SRH, (b) examine the role of SRH in predicting mortality, (c) validate SRH to improve its interpersonal comparability, and (d) assess how well estimates of SRH derived directly from a ‘small area’ survey compare with ‘small area’ estimates derived indirectly from a ‘large area’ survey.

Methods The Vadu Health and Demographic Surveillance System (HDSS) monitor health and demographic trends in a rural population of more than 100 000 in 22 villages in India since 2002. The full and short version of the SAGE survey was implemented in Vadu in 2007-09 among 321 and 5432 individuals aged 50 years and above, respectively. A structural equation model tested pathways through which social and biological factors influenced SRH. A Cox proportional hazard model examined the role of SRH as a predictor for mortality. Anchoring vignettes were used to evaluate SRH for reporting heterogeneity. The Hierarchical Ordered Probit model adjusted SRH for reporting heterogeneity. The SRH prevalence estimates for Vadu derived indirectly (indirect synthetic estimate, empirical Bayes estimate, Hierarchical Bayes estimate) from the national SAGE survey were compared with estimates derived directly from the Vadu SAGE survey, using different design and model-based techniques.

Results Older individuals reported poor SRH compared to those younger. Women rated their quality of life and SRH poorer than men. The effect of age on SRH was mediated through functional disability. Higher socioeconomic status and higher quality of life was in turn associated with better SRH but this relationship lacked statistical significance. Smoking or consumption of tobacco was associated with at least one chronic illness which in turn was associated with poor SRH and quality of life. However the association between chronic illness and SRH and quality of life was not statistically significant. Mortality risk was higher among individuals who reported bad/very bad SRH, disability and lack of spousal support independent of age and sex. There was strong evidence of reporting heterogeneity in SRH that was influenced by age, sex, education and socioeconomic status. The prevalence of ‘good / very good’ SRH was estimated to be 50%. This direct survey estimate compared well with the prevalence estimate of about 45% derived indirectly from model-based small area estimation methods. The indirect synthetic estimate for Vadu (23.2%) was a poor approximation to the direct survey or modelbased estimate.

Conclusion This research establishes the value and utility of SRH as a simple measure of health and predictor of mortality in an aging context. It provides evidence to formulate programs and policies towards an enabling social environment and an ability to function in key life domains of health and well-being. It highlights the need to identify and adjust self-rated responses for interpersonal incomparability prior to making comparisons across individuals or groups of individuals. It highlights the potential of using information from large national surveys by district level managers for planning and evaluation of policies and programs at the district or sub-district level. Finally, this research provides the basis for integrating SRH and related questions into routine HDSS.

Place, publisher, year, edition, pages
Umeå: Umeå universitet, 2013. 84 p.
Series
Umeå University medical dissertations, ISSN 0346-6612 ; 1601
Keyword
Self-rated health, quality of life, aging, mortality, disability, reportingheterogeneity, anchoring vignettes, India
National Category
Public Health, Global Health, Social Medicine and Epidemiology
Research subject
Epidemiology
Identifiers
urn:nbn:se:umu:diva-81200 (URN)978-01-7459-732-5 (ISBN)
Public defence
2013-10-25, Sal 135, by 9A, vån 1, Norrlands universitetssjukhus, Umeå, 09:00 (English)
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Available from: 2013-10-07 Created: 2013-10-03 Last updated: 2015-04-29Bibliographically approved

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