ABSTRACT
Background & objectives: The ambiguity and variability in existing literature on the magnitude of socio-economic inequality in self-reported morbidities makes it difficult to set priorities in health policy. This study examined three critical research questions: first, how far self-reporting affects measuring socio-economic inequalities in case of obstetric morbidities. Second, does using simple bivariate variations mislead in estimating socio-economic differentials in prevalence of obstetric morbidities? Finally, whether use of sophisticated regression based decomposition results can overcome such problems. Methods: The data from National Family Health Survey (NFHS-3; 2005-06) were used, and analyzed by statistical tools such as bivariate estimates and regression based decomposition analysis. Results: Bivariate results revealed that self-reported obstetric morbidity data were misleading in measurement of socio-economic differentials, as these failed to show existing socio-economic variations in obstetric morbidities by socio-economic standing of women. However, decomposition analysis showed that the prevalence of obstetric complications was greater among socioeconomically disadvantaged groups. Interpretation & conclusions: Based on our findings on measurement of socio-economic inequality in self-reported obstetric morbidity, we conclude that the use of regression based inequality decomposition estimates not only overcomes the problems of measuring socio-economic inequality based on self-reported morbidities, but also increases the validity of such measures.