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Unraveling the complexity of selected adverse neonatal outcomes in India: a multilevel analysis using data from a nationally representative sample survey
Unraveling the complexity of selected adverse neonatal outcomes in India: a multilevel analysis using data from a nationally representative sample survey
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Unraveling the complexity of selected adverse neonatal outcomes in India: a multilevel analysis using data from a nationally representative sample survey
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Unraveling the complexity of selected adverse neonatal outcomes in India: a multilevel analysis using data from a nationally representative sample survey
Unraveling the complexity of selected adverse neonatal outcomes in India: a multilevel analysis using data from a nationally representative sample survey

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Unraveling the complexity of selected adverse neonatal outcomes in India: a multilevel analysis using data from a nationally representative sample survey
Unraveling the complexity of selected adverse neonatal outcomes in India: a multilevel analysis using data from a nationally representative sample survey
Journal Article

Unraveling the complexity of selected adverse neonatal outcomes in India: a multilevel analysis using data from a nationally representative sample survey

2025
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Overview
Introduction The burden of adverse neonatal outcomes (ANOs), encompassing preterm birth(PTB), low birth weight(LBW), and early neonatal deaths, remain significant public health challenge globally, particularly in developing countries. The study aims to provide estimates of adverse birth outcomes and examine their correlates by using a multi-level model analysis at individual/household/community level. Methodology The study has chosen three ANOs such as preterm birth(PTB), low birth weight(LBW), and early neonatal deaths (based on available data) for constructing a combined indicator which is calculated by the presence of any one of these variables. We used National-Family-Health-Survey India data(2019–21). Multilevel(three-level) logistic regression model was used to find the probability of binary adverse neonatal outcomes with the effects of individual/household/community level variables among the recently delivered women. Result Between 2019–21, a total of 26.5% ANOs were reported from 1.7 million pregnant women surveyed, a rate that has increased since 2005–06 (20%). Final multilevel model asserts that women having higher education [OR 0.92, 95%CI 0.88, 0.96), and those registered for antenatal checkups (OR 0.95, 95%CI OR 0.9, 0.99) and know all components of birth-preparedness-and-complication-readiness (OR 0.88, 95%CI 0.84, 0.92) have a higher protective odd of having adverse outcomes. Difficulty in seeking medical help (OR 1.2, 95%CI 1.15, 1.25) and belonging to poor wealth status and no intention to become pregnant (OR 1.11 95% CI 1.05, 1.18) acts as a risk factor. Multilevel model with household, community and district level variables added to the null model showed a decline in the ICC values to 4.7%, 18.8% and 30.9% respectively across district, community, and household levels. Conclusion The study underscores that specific ANOs in India has shown an increase, prompting significant concern. There is need to institute a mechanism for generating knowledge amongst women to protect them from unwanted pregnancies and later adverse outcomes.