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Socioeconomic Inequalities and Factors Contributing to Under-Five Mortality in Uttar Pradesh: A Decomposition Analysis

Abstract

Neha Mishra* and Sheela Mishra

Background: Childhood mortality in India has declined substantially in during last three decades (1992-2021) from 119 to 42 per 1000 live births. However, this decline does not necessarily imply reduction in the inequalities which remains both in accesses to quality care and health outcomes among under-five children in Uttar Pradesh (India).

Objective: To estimate and quantify the prevailing socio-economic inequalities contributing to Under-five mortality in Uttar Pradesh along with the temporal trends over 2005–2021.

Methods: The last three rounds of National Family Health Survey (NFHS) were used to estimate and quantify the socioeconomic inequalities and factors contributing in the under-five mortalities by using concentration indexes (CI), concentration curves (CCs) and decomposition analysis.

Results: It was observed that during the period 2019-21 and 2015-16, high concentration of socio-economic inequalities for U5MR among women of age 35 years or more, had primary education, and belonged to Scheduled caste/tribe and Hindus. While during the period 2005-06, high concentration of inequalities was found among women of age 25-34 years, belonged to SC/ST and OBC caste groups, and among Hindus. Overall, mother’s education and place of residence mostly explained the U5MR inequality in all three time periods. Conclusion: The findings suggest that more efforts are needed in the state of Uttar Pradesh to narrow the income related U5MR inequalities. An effective way to reduce inequality is not only to reduce the gap of income but also focus should be made on increasing the level of education of mothers as educational attainment is critical in imparting the feelings of self-worth and confidence which are critical in bringing the changes in health-related behaviour.

Descargo de responsabilidad: este resumen se tradujo utilizando herramientas de inteligencia artificial y aún no ha sido revisado ni verificado

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