Measures of socioeconomic status for child health research

Comparative results from Bangladesh and Pakistan

Bibliographic Data

ID4590345
AuthorsM S Durkin (0000-0002-4287-8618, Columbia University), Islam (0000-0003-1806-5868), Sheikh Nazrul Islam (0000-0003-1622-8088, University of Dhaka), S Islam (0000-0002-2167-6427), Z M Hasan, Zaki Hasan (Jinnah Postgraduate Medical Center), S Zaman, S S Zaman (0009-0003-6989-599X)
Year1994
Volume38
Issue9
Pages1289-1297
Publication date1994-05-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueSocial Science & Medicine (JOURNAL)
Journal identifiersISSN: 0277-9536 • E-ISSN: 1873-5347
PublisherElsevier BV (PUBLISHER)
DOI10.1016/0277-9536(94)90192-9
PMID8016692
OpenAlexW2082569286
LanguageEN
Citations received19
References cited28

This paper examines the reliability and validity of several hypothesized indicators of socioeconomic status for use in epidemiologic research, particularly in studies of child health in the less developed world. Population-based surveys of child health and disability were completed in Bangladesh and Pakistan using standard questionnaires designed to measure four domains of household socioeconomic status: wealth, housing, parental education and occupation. Test-retest data indicate moderate to excellent reliability of most of the socioeconomic indicators in both countries. Loadings from factor analyses of the survey data provide further evidence of the reliability of the data, and confirm that the questionnaire measures housing and wealth as distinct domains in both countries. Parental education and occupation are correlated with housing and/or wealth in these data sets. Bivariate logistic regression analyses show that, although 11 of 12 dichotomous indicators of low socioeconomic status constructed from the data are predictive of child death in at least one of the four sub-populations studied (rural and urban Bangladesh, and rural and urban areas of Karachi, Pakistan), no single indicator is predictive of child death in all four sub-populations. These along with multivariate results demonstrate the importance of including multiple measures of distinct domains if the research aims include investigation and/or control of the effects of socioeconomic status on health in diverse populations

Bivariate analysis · Developing country · Economic growth · Economics · Environmental health · Geography · Logistic regression · Population · Public health · Rural area · Socioeconomic status · Socioeconomics · Sociology · Statistics · Demography · Food Security and Health in Diverse Populations · Global Maternal and Child Health · Health disparities and outcomes · Medicine · Psychology · Gerontology