Evidence map›Paper›PMID 25550454›Full record

ArticleJournal of epidemiology and community health2015

Are estimates of socioeconomic inequalities in chronic disease artefactually narrowed by self-reported measures of prevalence in low-income and middle-income countries? Findings from the WHO-SAGE survey.

Sukumar Vellakkal, Christopher Millett, Sanjay Basu, Zaky Khan, Amina Aitsi-Selmi, David Stuckler, Shah Ebrahim

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Article in Journal of epidemiology and community health, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 55 papers.

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55citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

Who cites it

55 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Sukumar VellakkalPublic Health Foundation of India, New Delhi, India Department of Sociology, Oxford University, Oxford, UK.
Christopher MillettPublic Health Foundation of India, New Delhi, India Department of Primary Care and Public Health, Imperial College London, London, UK.
Sanjay BasuPrevention Research Center, Stanford University, Stanford, Palo Alto, California, USA Department of Public Health and Policy, London School of Hygiene and Tropical Medicine, London, UK.
Zaky KhanPublic Health Foundation of India, New Delhi, India.
Amina Aitsi-SelmiDepartment of Epidemiology & Public Health, University College London, UK.
David StucklerDepartment of Sociology, Oxford University, Oxford, UK Department of Public Health and Policy, London School of Hygiene and Tropical Medicine, London, UK.
Shah EbrahimPublic Health Foundation of India, New Delhi, India Department of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK.

Funding

CORE--PROGRAM DEVELOPMENTP30AG017253 · NIA · STANFORD UNIVERSITY · PI BHATTACHARYA, JAY · 1999 to 2019
$5.8M
NIA NIH HHS P30 AG017253Wellcome Trust 084674Wellcome Trust 100709Wellcome Trust 100709/Z/12/ZWellcome Trust WT084674/Z/08/Z
6 · The paper itself

Abstract

backgroundThe use of self-reported measures of chronic disease may substantially underestimate prevalence in low-income and middle-income country settings, especially in groups with lower socioeconomic status (SES). We sought to determine whether socioeconomic inequalities in the prevalence of non-communicable chronic diseases (NCDs) differ if estimated by using symptom-based or criterion-based measures compared with self-reported physician diagnoses.

methodsUsing population-representative data sets of the WHO Study of Global Ageing and Adult Health (SAGE), 2007-2010 (n=42 464), we calculated wealth-related and education-related concentration indices of self-reported diagnoses and symptom-based measures of angina, hypertension, asthma/chronic lung disease, visual impairment and depression in three 'low-income and lower middle-income countries'-China, Ghana and India-and three 'upper-middle-income countries'-Mexico, Russia and South Africa.

resultsSES gradients in NCD prevalence tended to be positive for self-reported diagnoses compared with symptom-based/criterion-based measures. In China, Ghana and India, SES gradients were positive for hypertension, angina, visual impairment and depression when using self-reported diagnoses, but were attenuated or became negative when using symptom-based/criterion-based measures. In Mexico, Russia and South Africa, this distinction was not observed consistently. For example, concentration index of self-reported versus symptom-based angina were: in China: 0.07 vs. -0.11, Ghana: 0.04 vs. -0.21, India: 0.02 vs. -0.16, Mexico: 0.19 vs. -0.22, Russia: -0.01 vs. -0.02 and South Africa: 0.37 vs. 0.02.

conclusionsSocioeconomic inequalities in NCD prevalence tend to be artefactually positive when using self-report compared with symptom-based or criterion-based diagnostic criteria, with greater bias occurring in low-income countries. Using standardised, symptom-based measures would provide more valid estimates of NCD inequalities.

Indexed as

Self ReportSocial ClassAdolescentAdultBiasChronic DiseaseDeveloped CountriesDeveloping CountriesEducational StatusFemaleHealth SurveysHumansLogistic ModelsMaleMiddle AgedPrevalenceEpidemiology of chronic non communicable diseasesINEQUALITIESPUBLIC HEALTH

Identifiers

PMID25550454
PMCPMC4345525

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.