08) were used in this study. In multiple regression analysis explanatory variable such as underdevelopment is measured by the non-working population, and income inequality , quantified as the proportion of households in the bottom wealth quintile. While, the trickle-down effect of education is measured by female literacy, and investment in health, as reflected by neonatal care facilities in primary health centres. RESULTS: A high spatial autocorrelation of district infant mortality rates was observed, and ecological factors were found to have a significant impact on district infant mortality rates. The result also revealed that non-working population and income inequality were found to have a negative effect on the district infant mortality rate. Additionally, female literacy and newborn care facilities were found to have an inverse association with the infant mortality rate. CONCLUSIONS: Interventions at the community level can reduce district infant mortality rates.
CITATION STYLE
Ladusingh, L., Gupta, A. K., & Yadav, A. (2016). Ecological context of infant mortality in high-focus states of India. Epidemiology and Health, 38, e2016006. https://doi.org/10.4178/epih.e2016006
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