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

8 Pages Posted: 8 May 2015

See all articles by Sukumar Vellakkal

Sukumar Vellakkal

Public Health foundation of India (PHFI)

Christopher Millett

Imperial College London

Sanjay Basu

Stanford University - Center for Primary Care and Outcomes Research and Center for Population Health Sciences; Harvard University - Center for Primary Care

Zaky Khan

Public Health Foundation of India

Amina Aitsi-Selmi

University College London - Department of Epidemiology and Public Health

David Stuckler

University of Cambridge - Faculty of Human, Social, and Political Science

Shah Ebrahim

Public Health Foundation of India

Date Written: March 15, 2015

Abstract

Background The 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.

Methods Using 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.

Results SES 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.

Conclusions Socioeconomic 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.

Keywords: low-and-middle income countries, non-communicable diseases, self-reported diagnoses, symptoms-based measures, socio-economic inequality

JEL Classification: I10, I12, I18

Suggested Citation

Vellakkal, Sukumar and Millett, Christopher and Basu, Sanjay and Khan, Zaky and Aitsi-Selmi, Amina and Stuckler, David and Ebrahim, Shah, 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 (March 15, 2015). Available at SSRN: https://ssrn.com/abstract=2603197 or http://dx.doi.org/10.2139/ssrn.2603197

Sukumar Vellakkal (Contact Author)

Public Health foundation of India (PHFI) ( email )

4 Institutional Area
Vasant Kunj
New Delhi, Delhi 110070
India

HOME PAGE: http://www.phfi.org

Christopher Millett

Imperial College London ( email )

South Kensington Campus
Exhibition Road
London, Greater London SW7 2AZ
United Kingdom

Sanjay Basu

Stanford University - Center for Primary Care and Outcomes Research and Center for Population Health Sciences ( email )

1070 Arastradero Road Office 282
Palo Alto, CA 94304
United States

Harvard University - Center for Primary Care ( email )

Cambridge, MA
United States

Zaky Khan

Public Health Foundation of India ( email )

4 Institutional Area
Vasant Kunj
New Delhi, Delhi 110070
India

Amina Aitsi-Selmi

University College London - Department of Epidemiology and Public Health ( email )

London, FL WC1E 6BT
United Kingdom

David Stuckler

University of Cambridge - Faculty of Human, Social, and Political Science ( email )

Cambridge, CB3 9DD
United Kingdom

Shah Ebrahim

Public Health Foundation of India ( email )

4 Institutional Area
Vasant Kunj
New Delhi, Delhi 110070
India

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