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Socioeconomic inequality in life expectancy in India

Miqdad Asaria (), Sumit Mazumdar, Samir Chowdhury, Papiya Mazumdar, Abhiroop Mukhopadhyay () and Indrani Gupta

LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library

Abstract: Introduction Concern for health inequalities is an important driver of health policy in India; however, much of the empirical evidence regarding health inequalities in the country is piecemeal focusing only on specific diseases or on access to particular treatments. This study estimates inequalities in health across the whole life course for the entire Indian population. These estimates are used to calculate the socioeconomic disparities in life expectancy at birth in the population. Methods Population mortality data from the Indian Sample Registration System were combined with data on mortality rates by wealth quintile from the National Family Health Survey to calculate wealth quintile specific mortality rates. Results were calculated separately for males and females as well as for urban and rural populations. Life tables were constructed for each subpopulation and used to calculate distributions of life expectancy at birth by wealth quintile. Absolute gap and relative gap indices of inequality were used to quantify the health disparity in terms of life expectancy at birth between the richest and poorest fifths of households. results Life expectancy at birth was 65.1 years for the poorest fifth of households in India as compared with 72.7 years for the richest fifth of households. This constituted an absolute gap of 7.6 years and a relative gap of 11.7 %. Women had both higher life expectancy at birth and narrower wealth-related disparities in life expectancy than men. Life expectancy at birth was higher across the wealth distribution in urban households as compared with rural households with inequalities in life expectancy widest for men living in urban areas and narrowest for women living in urban areas. Conclusion As India progresses towards Universal Health Coverage, the baseline social distributions of health estimated in this study will allow policy makers to target and monitor the health equity impacts of health policies introduced.

JEL-codes: N0 (search for similar items in EconPapers)
Pages: 9 pages
Date: 2019-05-09
New Economics Papers: this item is included in nep-hea
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Published in BMJ, 9, May, 2019, 4(3). ISSN: 0959-8138

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