Social Indicators Research

, Volume 117, Issue 1, pp 105–119 | Cite as

Unpacking Self-Rated Health and Quality of Life in Older Adults and Elderly in India: A Structural Equation Modelling Approach

  • Siddhivinayak Hirve
  • Johan H. L. Oud
  • Somnath Sambhudas
  • Sanjay Juvekar
  • Yulia Blomstedt
  • Stephen Tollman
  • Stig Wall
  • Nawi Ng


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.


Self-rated health Quality of life Functional ability Social networking Structural equation modelling 



This paper uses data from the World Health Organization Study on Global AGEing (SAGE). SAGE is supported by the US National Institute on Aging through Interagency Agreements (OGHA 04034785; YA1323-08-CN-0020; Y1-AG-1005-01) and through a research grant (R01-AG034479). Health and Demographic Surveillance System, Vadu, is a member of the International Network for the Demographic Evaluation of Populations and Their Health (INDEPTH Network). The analyses and writing of this paper has been financed by the Umeå Centre for Global Health Research, Umeå University, with support from FAS, the Swedish Council for Working Life and Social Research (Grant No. 2006-1512) through its Ph.D. fellowship to the first author. We acknowledge the support of Kathy Kahn from INDEPTH Network and Somnath Chatterjee, Paul Kowal, and Nirmala Naidoo from WHO, Geneva, for coordinating this multi-country study. Thanks are due to Pallavi Lele and the Vadu HDSS team for their quality work and the older adult population of the Vadu Demographic Surveillance Area for their willingness to contribute their knowledge to this study.


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Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  • Siddhivinayak Hirve
    • 1
    • 2
  • Johan H. L. Oud
    • 3
  • Somnath Sambhudas
    • 1
  • Sanjay Juvekar
    • 1
  • Yulia Blomstedt
    • 2
  • Stephen Tollman
    • 2
    • 4
  • Stig Wall
    • 2
  • Nawi Ng
    • 2
  1. 1.Vadu Rural Health ProgramKEM Hospital Research CenterPuneIndia
  2. 2.Division of Epidemiology and Global Health, Department of Public Health and Clinical Medicine, Umeå Centre for Global Health ResearchUmeå UniversityUmeåSweden
  3. 3.Behavioural Science InstituteRadboud UniversityNijmegenThe Netherlands
  4. 4.Health and Population Division, School of Public HealthUniversity of WitwatersrandJohannesburgSouth Africa

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