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Socioeconomic Inequalities in Non-Communicable Diseases Prevalence in India: Disparities between Self-Reported Diagnoses and Standardized Measures

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  • Sukumar Vellakkal
  • S V Subramanian
  • Christopher Millett
  • Sanjay Basu
  • David Stuckler
  • Shah Ebrahim

Abstract

Background: Whether non-communicable diseases (NCDs) are diseases of poverty or affluence in low-and-middle income countries has been vigorously debated. Most analyses of NCDs have used self-reported data, which is biased by differential access to healthcare services between groups of different socioeconomic status (SES). We sought to compare self-reported diagnoses versus standardised measures of NCD prevalence across SES groups in India. Methods: We calculated age-adjusted prevalence rates of common NCDs from the Study on Global Ageing and Adult Health, a nationally representative cross-sectional survey. We compared self-reported diagnoses to standardized measures of disease for five NCDs. We calculated wealth-related and education-related disparities in NCD prevalence by calculating concentration index (C), which ranges from −1 to +1 (concentration of disease among lower and higher SES groups, respectively). Findings: NCD prevalence was higher (range 5.2 to 19.1%) for standardised measures than self-reported diagnoses (range 3.1 to 9.4%). Several NCDs were particularly concentrated among higher SES groups according to self-reported diagnoses (Csrd) but were concentrated either among lower SES groups or showed no strong socioeconomic gradient using standardized measures (Csm): age-standardised wealth-related C: angina Csrd 0.02 vs. Csm −0.17; asthma and lung diseases Csrd −0.05 vs. Csm −0.04 (age-standardised education-related Csrd 0.04 vs. Csm −0.05); vision problems Csrd 0.07 vs. Csm −0.05; depression Csrd 0.07 vs. Csm −0.13. Indicating similar trends of standardized measures detecting more cases among low SES, concentration of hypertension declined among higher SES (Csrd 0.19 vs. Csm 0.03). Conclusions: The socio-economic patterning of NCD prevalence differs markedly when assessed by standardized criteria versus self-reported diagnoses. NCDs in India are not necessarily diseases of affluence but also of poverty, indicating likely under-diagnosis and under-reporting of diseases among the poor. Standardized measures should be used, wherever feasible, to estimate the true prevalence of NCDs.

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  • Sukumar Vellakkal & S V Subramanian & Christopher Millett & Sanjay Basu & David Stuckler & Shah Ebrahim, 2013. "Socioeconomic Inequalities in Non-Communicable Diseases Prevalence in India: Disparities between Self-Reported Diagnoses and Standardized Measures," PLOS ONE, Public Library of Science, vol. 8(7), pages 1-12, July.
    • Handle: RePEc:plo:pone00:0068219
    DOI: 10.1371/journal.pone.0068219
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    1. Olusoji Adeyi & Owen Smith & Sylvia Robles, 2007. "Public Policy and the Challenge of Chronic Noncommunicable Diseases," World Bank Publications - Books, The World Bank Group, number 6761, December.
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    2. Joko Mulyanto & Dionne S. Kringos & Anton E. Kunst, 2019. "The accuracy of self-report versus objective assessment for estimating socioeconomic inequalities in disease prevalence in Indonesia," International Journal of Public Health, Springer;Swiss School of Public Health (SSPH+), vol. 64(8), pages 1233-1241, November.
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    11. Saxena, Akshar & Mendenhall, Emily, 2022. "Syndemic thinking in large-scale studies: Case studies of disability, hypertension, and diabetes across income groups in India and China," Social Science & Medicine, Elsevier, vol. 295(C).
    12. Ilke Onur & Malathi Velamuri, 2018. "The gap between self-reported and objective measures of disease status in India," PLOS ONE, Public Library of Science, vol. 13(8), pages 1-18, August.
    13. Mendenhall, Emily & Omondi, Gregory Barnabas & Bosire, Edna & Isaiah, Gitonga & Musau, Abednego & Ndetei, David & Mutiso, Victoria, 2015. "Stress, diabetes, and infection: Syndemic suffering at an urban Kenyan hospital," Social Science & Medicine, Elsevier, vol. 146(C), pages 11-20.
    14. Thomas, Ranjeeta & Burger, Ronelle & Hauck, Katharina, 2018. "Richer, wiser and in better health? The socioeconomic gradient in hypertension prevalence, unawareness and control in South Africa," Social Science & Medicine, Elsevier, vol. 217(C), pages 18-30.
    15. Perianayagam Arokiasamy & Uttamacharya & Kshipra Jain, 2015. "Multi-Morbidity, Functional Limitations, and Self-Rated Health Among Older Adults in India," SAGE Open, , vol. 5(1), pages 21582440155, February.
    16. El-Sayed, Abdulrahman M. & Palma, Anton & Freedman, Lynn P. & Kruk, Margaret E., 2015. "Does health insurance mitigate inequities in non-communicable disease treatment? Evidence from 48 low- and middle-income countries," Health Policy, Elsevier, vol. 119(9), pages 1164-1175.
    17. Jinkook Lee & McGovern, Mark E. & David E. Bloom & P. Arokiasamy & Arun Risbud & Jennifer O?Brien & Varsha Kale & Peifeng Hu, 2015. "Education, Gender, and State-Level Gradients in the Health of Older Indians: Evidence from Biomarker Data," Working Paper 228841, Harvard University OpenScholar.
    18. Regina Moczadlo & Harald Strotmann & Jürgen Volkert, 2015. "Corporate Contributions to Developing Health Capabilities," Journal of Human Development and Capabilities, Taylor & Francis Journals, vol. 16(4), pages 549-566, November.
    19. Chipo Mutyambizi & Frederik Booysen & Andrew Stokes & Milena Pavlova & Wim Groot, 2019. "Lifestyle and socio-economic inequalities in diabetes prevalence in South Africa: A decomposition analysis," PLOS ONE, Public Library of Science, vol. 14(1), pages 1-21, January.
    20. Ila Patnaik & Renuka Sane & Ajay Shah & S. V. Subramaniam, 2021. "Distribution of self-reported health in India: The role of income and geography," Working Papers 6, xKDR.
    21. Kangmennaang, Joseph & Onyango, Elizabeth O. & Luginaah, Isaac & Elliott, Susan J., 2018. "The next Sub Saharan African epidemic? A case study of the determinants of cervical cancer knowledge and screening in Kenya," Social Science & Medicine, Elsevier, vol. 197(C), pages 203-212.
    22. Anubha Agarwal & Devraj Jindal & Vamadevan S Ajay & Dimple Kondal & Siddhartha Mandal & Shreeparna Ghosh & Mumtaj Ali & Kavita Singh & Mark D Huffman & Nikhil Tandon & Dorairaj Prabhakaran, 2019. "Association between socioeconomic position and cardiovascular disease risk factors in rural north India: The Solan Surveillance Study," PLOS ONE, Public Library of Science, vol. 14(7), pages 1-16, July.
    23. Ji-Yeon Shin & Jiseun Lim & Myung Ki & Yeong-Jun Song & Heeran Chun & Dongjin Kim, 2018. "An Assessment of Magnitudes and Patterns of Socioeconomic Inequalities across Various Health Problems: A Large National Cross-Sectional Survey in Korea," IJERPH, MDPI, vol. 15(12), pages 1-13, December.

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