Evidence map›Paper›PMID 41369871›Full record

ArticleIndian journal of pediatrics2026

Decomposition of Wealth-Related Inequality in Child Immunization Among Aspirational and Non-Aspirational Districts in India.

Pooja Goel, Cyril Philip, Phanindra Goyari

Abstract read
PubMed Publisher
In one paragraph

Article in Indian journal of pediatrics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Pooja GoelSchool of Economics, University of Hyderabad, Hyderabad, 500046, India. poojagoel869@gmail.com.ORCID 0009-0006-4240-497X
Cyril PhilipSchool of Economics, University of Hyderabad, Hyderabad, 500046, India.
Phanindra GoyariSchool of Economics, University of Hyderabad, Hyderabad, 500046, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo determine the change in inequalities in full immunization coverage among children aged 12-23 mo in aspirational districts (ADs) and non-aspirational districts (NADs) in India from 2015-16 to 2019-2021 and decompose its causes.

methodsThe authors used the National Family Health Survey (NFHS-4 and NFHS-5) data for the analysis. The two-sample proportions test and linear probability model were used. Further, the corrected concentration index (CCI) was used to measure inequality, and Wagstaff’s decomposition analysis was used to decompose the inequality.

resultsFull immunization coverage among Indian children increased from 60.91% (NFHS-4) to 75.97% (NFHS-5) in NADs, and from 57.93% to 74.73% in ADs. The study shows an important finding of convergence of immunization estimates among ADs and NADS during NFHS-5. Inequality in child immunization, measured by CCI, decreased from NFHS-4 to NFHS-5 but remained higher in ADs. Mother’s education, healthcare utilization variables, residence, and region are the key contributors to immunization inequality.

conclusionsThe findings suggest that the focus should be on improving mothers’ education, providing health cards, and antenatal care visits, and reducing the distance to health facilities. Improving the provision of healthcare utilization variables can help mitigate inequalities in full immunization coverage, especially in ADs, thereby reducing inequalities between ADs and NADs.

Indexed as

Healthcare DisparitiesImmunizationVaccination CoverageFemaleHealth SurveysHumansIndiaInfantMaleSocioeconomic Disparities in HealthSocioeconomic FactorsAspirational districtsChild immunizationDecompositionInequalityNon-aspirational districts

Identifiers

What OpenQuestion holds

Textmetadata
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.