Evidence map›Paper›PMID 36361267›Full record

ArticleInternational journal of environmental research and public health2022

Infant Death Clustering in the Quarter of a Century in India: A Decomposition Analysis.

Mukesh Ranjan, Laxmi Kant Dwivedi, Shivalingappa Halli

Open access · goldAbstract read
In one paragraph

Article in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.4field-weighted citation impact, top 34% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. Neighborhood Sanitation and Infant Mortality.American economic journal. Applied economics · 2018
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 3 institutions in 2 countries.

Mukesh RanjanDepartment of Statistics, Mizoram University, Pachhunga University College Campus, Aizawl 796001, Mizoram, India.ORCID 0000-0002-5369-8081
Laxmi Kant DwivediDepartment of Survey Research & Data Analytics, International Institute for Population Sciences, Govandi Station Road, Deonar 400088, Mumbai, India.
Shivalingappa HalliDepartment of Community Health Sciences, Institute for Global Public Health, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB R3E 0T6, Canada.
International Institute for Population Sciences · INMizoram University · INUniversity of Manitoba · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The study aims to examine the clustering of infant deaths in India and the relative contribution of infant death clustering after accounting for the socio-economic and biodemographic factors that explain the decline in infant deaths. The study utilized 10 years of birth history data from three rounds of the National Family Health Survey (NFHS). The random effects dynamic probit model was used to decompose the decline in infant deaths into the contributions by the socio-economic and demographic factors, including the lagged independent variable, the previous infant death measuring the clustering of infant deaths in families. The study found that there has been a decline in the clustering of infant deaths among families during the past two and half decades. The simulation result shows that if the clustering of infant deaths in families in India was completely removed, there would be a decline of nearly 30 percent in the infant mortality rate (IMR). A decomposition analysis based on the dynamic probit model shows that for NFHS-1 and NFHS-3, in the total change of the probability of infant deaths, the rate of change for a given population composition contributed around 45 percent, and about 44 percent was explained by a compositional shift. Between NFHS-3 and NFHS-4, the rate of change for a given population composition contributed 86%, and the population composition for a given rate contributed 10% to the total change in the probability of infant deaths. Within this rate, the contribution of a previous infant was 0.8% and the mother's age was 10%; nearly 31% was contributed by the region of residence, 69% by the mother's education, and around 20% was contributed by the wealth index and around 8.7% by the sex of the child. The mother's unobserved factors contributed more than 50 percent to the variability of infant deaths in all the survey rounds and was also statistically significant (

Indexed as

Infant DeathInfant MortalityCluster AnalysisEducational StatusFemaleHumansIndiaInfant, NewbornMaternal AgeMothersSocioeconomic Factorsdecomposition analysisinfant death clusteringinfant mortality ratenational family health surveyrandom effects dynamic probit model

Identifiers

PMID36361267
PMCPMC9653878
OpenAlexW4308206541

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.