Evidence map›Paper›PMID 39203976›Full record

ArticleVaccines2024

Inequality in Childhood Immunization Coverage: A Scoping Review of Data Sources, Analyses, and Reporting Methods.

Carrie Lyons, Devaki Nambiar, Nicole E Johns, Adrien Allorant, Nicole Bergen, Ahmad Reza Hosseinpoor

Abstract readScoping Review
In one paragraph

Article in Vaccines, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 2 pooled it
–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

17 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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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

6 authors.

Carrie LyonsDepartment of Data and Analytics, World Health Organization, 20 Avenue Appia, 1211 Geneva, Switzerland.
Devaki NambiarDepartment of Data and Analytics, World Health Organization, 20 Avenue Appia, 1211 Geneva, Switzerland.ORCID 0000-0001-5682-6109
Nicole E JohnsDepartment of Data and Analytics, World Health Organization, 20 Avenue Appia, 1211 Geneva, Switzerland.ORCID 0000-0003-4513-4582
Adrien AllorantDepartment of Data and Analytics, World Health Organization, 20 Avenue Appia, 1211 Geneva, Switzerland.
Nicole BergenDepartment of Data and Analytics, World Health Organization, 20 Avenue Appia, 1211 Geneva, Switzerland.ORCID 0000-0002-8161-2599
Ahmad Reza HosseinpoorDepartment of Data and Analytics, World Health Organization, 20 Avenue Appia, 1211 Geneva, Switzerland.ORCID 0000-0001-7322-672X

Funding

World Health Organization 001
6 · The paper itself

Abstract

Immunization through vaccines among children has contributed to improved childhood survival and health outcomes globally. However, vaccine coverage among children is unevenly distributed across settings and populations. The measurement of inequalities is essential for understanding gaps in vaccine coverage affecting certain sub-populations and monitoring progress towards achieving equity. Our study aimed to characterize the methods of reporting inequalities in childhood vaccine coverage, inclusive of the settings, data source types, analytical methods, and reporting modalities used to quantify and communicate inequality. We conducted a scoping review of publications in academic journals which included analyses of inequalities in vaccination among children. Literature searches were conducted in PubMed and Web of Science and included relevant articles published between 8 December 2013 and 7 December 2023. Overall, 242 publications were identified, including 204 assessing inequalities in a single country and 38 assessing inequalities across more than one country. We observed that analyses on inequalities in childhood vaccine coverage rely heavily on Demographic Health Survey (DHS) or Multiple Indicator Cluster Surveys (MICS) data (39.3%), and papers leveraging these data had increased in the last decade. Additionally, about half of the single-country studies were conducted in low- and middle-income countries. We found that few studies analyzed and reported inequalities using summary measures of health inequality and largely used the odds ratio resulting from logistic regression models for analyses. The most analyzed dimensions of inequality were economic status and maternal education, and the most common vaccine outcome indicator was full vaccination with the recommended vaccine schedule. However, the definition and construction of both dimensions of inequality and vaccine coverage measures varied across studies, and a variety of approaches were used to study inequalities in vaccine coverage across contexts. Overall, harmonizing methods for selecting and categorizing dimensions of inequalities as well as methods for analyzing and reporting inequalities can improve our ability to assess the magnitude and patterns of inequality in vaccine coverage and compare those inequalities across settings and time.

Indexed as

health inequalitiesimmunizationinfant and child healthscoping reviewvaccination

Identifiers

PMID39203976
PMCPMC11360733

What OpenQuestion holds

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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.