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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.

Suggested Citation

  • 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.
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    1. Sözmen, Kaan & Ünal, Belgin, 2016. "Explaining inequalities in Health Care Utilization among Turkish adults: Findings from Health Survey 2008," Health Policy, Elsevier, vol. 120(1), pages 100-110.
    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.
    3. Toshiaki Aizawa, 2019. "Transition of the BMI distribution in India: evidence from a distributional decomposition analysis," Journal of Bioeconomics, Springer, vol. 21(1), pages 3-36, April.
    4. Joko Mulyanto & Dionne S Kringos & Anton E Kunst, 2019. "The evolution of income-related inequalities in healthcare utilisation in Indonesia, 1993–2014," PLOS ONE, Public Library of Science, vol. 14(6), pages 1-15, June.
    5. Lee, Jinkook & McGovern, Mark E. & Bloom, David E. & Arokiasamy, P. & Risbud, Arun & O’Brien, Jennifer & Kale, Varsha & Hu, Peifeng, 2015. "Education, gender, and state-level disparities in the health of older Indians: Evidence from biomarker data," Economics & Human Biology, Elsevier, vol. 19(C), pages 145-156.
    6. McGovern, Mark E., 2014. "Comparing the relationship between stature and later life health in six low and middle income countries," The Journal of the Economics of Ageing, Elsevier, vol. 4(C), pages 128-148.
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    8. Mulcahy, Patrick & Mahal, Ajay & McPake, Barbara & Kane, Sumit & Ghosh, Prabir Kumar & Lee, John Tayu, 2021. "Is there an association between public spending on health and choice of healthcare providers across socioeconomic groups in India? - Evidence from a national sample," Social Science & Medicine, Elsevier, vol. 285(C).
    9. John Tayu Lee & Fozia Hamid & Sanghamitra Pati & Rifat Atun & Christopher Millett, 2015. "Impact of Noncommunicable Disease Multimorbidity on Healthcare Utilisation and Out-Of-Pocket Expenditures in Middle-Income Countries: Cross Sectional Analysis," PLOS ONE, Public Library of Science, vol. 10(7), pages 1-18, July.
    10. Tuhin Biswas & Md Saimul Islam & Natalie Linton & Lal B Rawal, 2016. "Socio-Economic Inequality of Chronic Non-Communicable Diseases in Bangladesh," PLOS ONE, Public Library of Science, vol. 11(11), pages 1-12, November.
    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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