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Popul Health Metr. 2010 Nov 16;8:30. doi: 10.1186/1478-7954-8-30.

Measuring the health of the Indian elderly: evidence from National Sample Survey data.

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1
Department of Global Health and Population, Harvard School of Public Health, Boston, USA. ytchen@hsph.harvard.edu.

Abstract

BACKGROUND:

Comparable health measures across different sets of populations are essential for describing the distribution of health outcomes and assessing the impact of interventions on these outcomes. Self-reported health (SRH) is a commonly used indicator of health in household surveys and has been shown to be predictive of future mortality. However, the susceptibility of SRH to influence by individuals' expectations complicates its interpretation and undermines its usefulness.

METHODS:

This paper applies the empirical methodology of Lindeboom and van Doorslaer (2004) to investigate elderly health in India using data from the 52nd round of the National Sample Survey conducted in 1995-96 that includes both an SRH variable as well as a range of objective indicators of disability and ill health. The empirical testing was conducted on stratified homogeneous groups, based on four factors: gender, education, rural-urban residence, and region.

RESULTS:

We find that region generally has a significant impact on how women perceive their health. Reporting heterogeneity can arise not only from cut-point shifts, but also from differences in health effects by objective health measures. In contrast, we find little evidence of reporting heterogeneity due to differences in gender or educational status within regions. Rural-urban residence does matter in some cases. The findings are robust with different specifications of objective health indicators.

CONCLUSIONS:

Our exercise supports the thesis that the region of residence is associated with different cut-points and reporting behavior on health surveys. We believe this is the first paper that applies the Lindeboom-van Doorslaer methodology to data on the elderly in a developing country, showing the feasibility of applying this methodology to data from many existing cross-sectional health surveys.

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