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Mortality Burden and Socioeconomic Status in India

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  • June Y T Po
  • S V Subramanian

Abstract

Background: The dimensions along which mortality is patterned in India remains unclear. We examined the specific contribution of social castes, household income, assets, and monthly per capita consumption to mortality differentials in India. Methods and Findings: Cross-sectional data on 217 363 individuals from 41 554 households from the 2004–2005 India Human Development Survey was analyzed using multiple logistic regressions. Mortality differentials across social castes were attenuated after adjusting for household economic factors such as income and assets. Individuals living in the lowest income and assets quintiles had an increased risk of mortality with odds ratio (OR) of 1.66 (95% CI = 1.23–2.24) in the bottom income quintile and OR of 2.94 (95% CI = 1.66–5.22) in the bottom asset quintile. Counter-intuitively, individuals living in households with lowest monthly consumption per capita had significantly lower probability of death (OR = 0.27, 95% CI = 0.20–0.38). Conclusions: Mortality burden in India is largely patterned on economic dimensions as opposed to caste dimensions, though caste may play an important role in predicting economic opportunities.

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  • June Y T Po & S V Subramanian, 2011. "Mortality Burden and Socioeconomic Status in India," PLOS ONE, Public Library of Science, vol. 6(2), pages 1-8, February.
    • Handle: RePEc:plo:pone00:0016844
    DOI: 10.1371/journal.pone.0016844
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    2. Abhishek Singh & Praveen Kumar Pathak & Rajesh Kumar Chauhan & William Pan, 2011. "Infant and Child Mortality in India in the Last Two Decades: A Geospatial Analysis," PLOS ONE, Public Library of Science, vol. 6(11), pages 1-19, November.
    3. Jayanta Kumar Bora & Nandita Saikia, 2018. "Neonatal and under-five mortality rate in Indian districts with reference to Sustainable Development Goal 3: An analysis of the National Family Health Survey of India (NFHS), 2015–2016," PLOS ONE, Public Library of Science, vol. 13(7), pages 1-15, July.
    4. Rajeev Gupta & Prakash C Deedwania & Krishnakumar Sharma & Arvind Gupta & Soneil Guptha & Vijay Achari & Arthur J Asirvatham & Anil Bhansali & Balkishan Gupta & Sunil Gupta & Mallikarjuna V Jali & Tul, 2012. "Association of Educational, Occupational and Socioeconomic Status with Cardiovascular Risk Factors in Asian Indians: A Cross-Sectional Study," PLOS ONE, Public Library of Science, vol. 7(8), pages 1-10, August.
    5. Jayanta Kumar Bora & Rajesh Raushan & Wolfgang Lutz, 2019. "The persistent influence of caste on under-five mortality: Factors that explain the caste-based gap in high focus Indian states," PLOS ONE, Public Library of Science, vol. 14(8), pages 1-20, August.
    6. Swati Dutta, 2022. "Risk factors for child survival among tribal dominated states in India: a pooled cross sectional analysis," Journal of Population Research, Springer, vol. 39(3), pages 391-416, September.
    7. Nandita Saikia & Moradhvaj Moradhvaj, 2020. "Socioeconomic patterns and determinants of adult mortality due to external-causes in India: Analysis of nationally-representative, population-based survey data," VID Working Papers 2004, Vienna Institute of Demography (VID) of the Austrian Academy of Sciences in Vienna.
    8. Hossain, Babul & James, K.S., 2024. "Economics of widowhood mortality in adult women in India," Social Science & Medicine, Elsevier, vol. 340(C).
    9. Silvia Stringhini & Valentin Rousson & Bharathi Viswanathan & Jude Gedeon & Fred Paccaud & Pascal Bovet, 2014. "Association of Socioeconomic Status with Overall and Cause Specific Mortality in the Republic of Seychelles: Results from a Cohort Study in the African Region," PLOS ONE, Public Library of Science, vol. 9(7), pages 1-8, July.
    10. Nandita Saikia & Abhishek Singh & Domantas Jasilionis & Faujdar Ram, 2013. "Explaining the rural-urban gap in infant mortality in India," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 29(18), pages 473-506.

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