Lara Jung1, Jan-Walter De Neve1, Simiao Chen1, Jennifer Manne-Goehler2, Lindsay M Jaacks3, Daniel J Corsi4, Ashish Awasthi5, S V Subramanian6, Sebastian Vollmer7, Till Bärnighausen8, Pascal Geldsetzer9. 1. Heidelberg Institute of Global Health, Heidelberg University, Heidelberg, Germany. 2. Division of Infectious Diseases, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA. 3. Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Public Health Foundation of India, New Delhi, Delhi NCR, India. 4. Ottawa Hospital Research Institute, Ottawa, ON, Canada; School of Epidemiology and Public Health, University of Ottawa, Ottawa, ON, Canada. 5. Public Health Foundation of India, New Delhi, Delhi NCR, India. 6. Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Boston, MA, USA. 7. Department of Economics & Centre for Modern Indian Studies, University of Goettingen, Göttingen, Germany. 8. Heidelberg Institute of Global Health, Heidelberg University, Heidelberg, Germany; Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Africa Health Research Institute, Somkhele, KwaZulu-Natal, South Africa. 9. Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA, USA. Electronic address: pgeldsetzer@mail.harvard.edu.
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.
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.
Authors: Lara Jung; Jan-Walter De Neve; Simiao Chen; Jennifer Manne-Goehler; Lindsay M Jaacks; Daniel J Corsi; Ashish Awasthi; S V Subramanian; Sebastian Vollmer; Till Bärnighausen; Pascal Geldsetzer Journal: Data Brief Date: 2019-09-13
Authors: Mónica Mazariegos; Amy H Auchincloss; Ariela Braverman-Bronstein; María F Kroker-Lobos; Manuel Ramírez-Zea; Philipp Hessel; J Jaime Miranda; Carolina Pérez-Ferrer Journal: Public Health Nutr Date: 2021-06-25 Impact factor: 4.539