Evidence map›Paper›PMID 38594693›Full record

ArticleBMC public health2024

Survival among children under-five in India: a parametric multilevel survival approach.

Ajit Kumar Jaiswal, Manoj Alagarajan, Wahengbam Bigyananda Meitei

Abstract read
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Article in BMC public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Ajit Kumar Jaiswal, Mumbai, India. ajitjaiswal20@gmail.com.
Manoj AlagarajanDepartment of Fertility and Social demography, International Institute for Population Sciences, Mumbai, India.
Wahengbam Bigyananda MeiteiDepartment of Public Health and Mortality Studies, International Institute for Population Sciences, Mumbai, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMany studies have been conducted on under-five mortality in India and most of them focused on the associations between individual-level factors and under-five mortality risks. On the contrary, only a scarce number of literatures talked about contextual level effect on under-five mortality. Hence, it is very important to have thorough study of under-five mortality at various levels. This can be done by applying multilevel analysis, a method that assesses both fixed and random effects in a single model. The multilevel analysis allows extracting the influence of individual and community characteristics on under-five mortality. Hence, this study would contribute substantially in understanding the under-five mortality from a different perspective.

methodThe study used data from the Demographic and Health Survey (DHS) acquired in India, i.e., the fourth round of National Family and Health Survey (2015-16). It is a nationally representative repeated cross-sectional data. Multilevel Parametric Survival Model (MPSM) was employed to assess the influence of contextual correlates on the outcome. The assumption behind this study is that 'individuals' (i.e., level-1) are nested within 'districts' (i.e., level-2), and districts are enclosed within 'states' (i.e., level-3). This suggests that people have varying health conditions, residing in dissimilar communities with different characteristics.

resultsHighest under-five mortality i.e., 3.85% are happening among those women whose birth interval is less than two years. In case of parity, around 4% under-five mortality is among women with Third and above order parity. Further, findings from the full model is that ICC values of 1.17 and 0.65% are the correlation of the likelihood of having under-five mortality risk among people residing in the state and district communities, respectively. Besides, the risk of dying was increased alarmingly in the first year of life and slowly to aged 3 years and then it remains steady.

conclusionThis study has revealed that both aspects viz. individual and contextual effect of the community are necessary to address the importance variations in under-five mortality in India. In order to ensure substantial reduction in under-five mortality, findings of the study support some policy initiatives that involves the need to think beyond individual level effects and considering contextual characteristics.

Indexed as

Child MortalityInfant MortalityBirth IntervalsChildCross-Sectional StudiesFemaleHumansIndiaPregnancyIndiaIntra-class CorrelationParametricSurvival analysisUnder-five Mortality

Identifiers

PMID38594693
PMCPMC11003003

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.