Pandey Anuj Kumar, Thomas Benson M, Gautam Diksha, Balachandran Arun, Widyastari Dyah Anantalia, Sriram Shyamkumar, Neogi Sutapa Bandyopadhyay
Department of Health Systems and Implementation Research, International Institute of Health Management Research New Delhi, Dwarka, India.
Institute for Population and Social Research, Mahidol University, Nakhon Pathom, Thailand.
BMC Pregnancy Childbirth. 2025 Mar 31;25(1):377. doi: 10.1186/s12884-025-07448-9.
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.
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.
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.
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.
不良新生儿结局(ANOs)的负担,包括早产(PTB)、低出生体重(LBW)和早期新生儿死亡,仍然是全球重大的公共卫生挑战,特别是在发展中国家。本研究旨在通过在个体/家庭/社区层面使用多层次模型分析来提供不良出生结局的估计,并检查其相关因素。
本研究选择了三种不良新生儿结局,如早产(PTB)、低出生体重(LBW)和早期新生儿死亡(基于现有数据),以构建一个综合指标,该指标通过这些变量中任何一个的存在来计算。我们使用了印度国家家庭健康调查数据(2019 - 21年)。采用多水平(三级)逻辑回归模型来确定近期分娩妇女中个体/家庭/社区层面变量影响下二元不良新生儿结局的概率。
在2019 - 21年期间,在接受调查的170万孕妇中,共报告了26.5%的不良新生儿结局,这一比例自2005 - 06年(20%)以来有所上升。最终的多水平模型表明,受过高等教育的女性[比值比(OR)0.92,95%置信区间(CI)0.88,0.96]、进行过产前检查登记的女性(OR 0.95,95%CI OR 0.9,0.99)以及了解分娩准备和并发症应对所有组成部分的女性(OR 0.88,95%CI 0.84,0.92)出现不良结局的保护几率更高。寻求医疗帮助困难(OR 1.2,95%CI 1.15,1.25)以及属于贫困财富状况且无意怀孕(OR 1.11,95%CI 1.05,1.18)是风险因素。在空模型中加入家庭、社区和地区层面变量的多水平模型显示,地区、社区和家庭层面的组内相关系数(ICC)值分别降至4.7%、18.8%和30.9%。
该研究强调印度特定的不良新生儿结局有所增加,令人深感担忧。需要建立一种机制,在女性中传播知识,以保护她们免受意外怀孕及随后不良结局的影响。