The interaction between district-level development and individual-level socioeconomic gradients of cardiovascular disease risk factors in India: A cross-sectional study of 2.4 million adults. (October 2019) - Jung, Lara; De Neve, Jan-Walter; Chen, Simiao; Manne-Goehler, Jennifer; Jaacks, Lindsay M.; Corsi, Daniel J.; Awasthi, Ashish; Subramanian, S.V.; Vollmer, Sebastian; Bärnighausen, Till; Geldsetzer, Pascal
Abstract: Background: Diabetes, hypertension, and obesity tend to be positively associated with socio-economic status in low- and middle-income countries (LMICs). It has been hypothesized that these positive socio-economic gradients will reverse as LMICs continue to undergo economic development. We use population-based cross-sectional data in India to examine how a district's economic development is associated with socio-economic differences in cardiovascular disease (CVD) risk factor prevalence between individuals. Methods: We separately analyzed two nationally representative household survey datasets – the NFHS-4 and the DLHS-4/AHS – that are representative at the district level in India. Diabetes was defined based on a capillary blood glucose measurement, hypertension on blood pressure measurements, obesity on measurements of height and weight, and current smoking on self-report. Five different measures of a district's economic development were used. We analyzed the data using district-level regressions (plotting the coefficient comparing high to low socio-economic status against district-level economic development) and multilevel modeling. Results: 757, 655 and 1, 618, 844 adults participated in the NFHS-4 and DLHS-4/AHS, respectively. Higher education and household wealth were associated with a higher probability of having diabetes, hypertension, and obesity, and a lower probability of being a current smoker. For diabetes, hypertension, and obesity, we found that a higher economic development of a district was associated with a less positive (or even negative) association between the CVD risk factor and education. For smoking, the association with education tended to become less negative as districts had a higher level of economic development. In general, these associations did not show clear trends when household wealth quintile was used as the measure of socio-economic status instead of education. Conclusions: While this study provides some evidence for the "reversal hypothesis", large-scale longitudinal studies are needed to determine whether LMICs should expect a likely reversal of current positive socioeconomic gradients in diabetes, hypertension, and obesity as their countries continue to develop economically. Highlights: Education and wealth are associated with diabetes, hypertension, and obesity in India. For education, this association was flatter or reversed in more developed districts. For wealth, there was no clear pattern in how this association changed with development. Longitudinal studies are needed for more conclusive evidence.