Evidence map›Paper›PMID 37063304›Full record

ArticleVaccine: X2023

A multilevel analysis of individual and community-level factors associated with childhood immunisation in Bangladesh: Evidence from a pooled cross-sectional survey.

Md Alamgir Sarder, Ka Yiu Lee, Syed Afroz Keramat, Rubayyat Hashmi, Benojir Ahammed

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In one paragraph

Article in Vaccine: X, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

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3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

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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

5 authors.

Md Alamgir SarderStatistics Discipline, Science, Engineering and Technology (SET) School, Khulna University, Khulna 9208, Bangladesh.
Ka Yiu LeeSwedish Winter Sports Research Centre, Department of Health Sciences, Mid Sweden University, Östersund, Sweden.
Syed Afroz KeramatEconomics Discipline, Social Science School, Khulna University, Khulna 9208, Bangladesh.
Rubayyat HashmiSchool of Business, University of Southern Queensland, Toowoomba, QLD 4350, Australia.
Benojir AhammedStatistics Discipline, Science, Engineering and Technology (SET) School, Khulna University, Khulna 9208, Bangladesh.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Previous studies on childhood vaccinations in Bangladesh relied on single-level analyses and ignored the clustering and hierarchical structure of data collected from people living in different geographical units. This study, therefore, aimed to investigate the association between individual and community-level factors of full childhood immunisation with an improved analytical approach. Methods: Participants were 13,752 children aged 12-59 months. Data were extracted from the Bangladesh Demographic and Health Survey (BDHS) conducted in 2007, 2011, 2014, and 2017-18. A two-level multilevel logistic regression method was used to analyse the data. Results: Approximately 87% of the children were fully immunised. In the fully adjusted model, at the individual level, mothers who had primary and above education (Adjusted odds ratio [AOR] = 1.78; 95% Confidence Interval [CI]: 1.57, 2.01), mass media exposure (AOR = 1.14; 95% CI: 1.00, 1.30), having vaccination cards (AOR = 3.65; 95% CI: 3.23, 4.14), and having at least 4 antenatal care (ANC) visits (AOR = 1.24; 95% CI: 1.06, 1.44) were strongly associated with full childhood immunisation. At community-level, rural residency (AOR = 1.25; 95% CI: 1.08, 1.44), community women's education (AOR = 1.24; 95% CI: 1.07, 1.43), and community ANC utilisation (AOR = 1.38; 95% CI: 1.19, 1.61) were significantly associated with full childhood immunisation. Conclusion: Along with individual-level factors, community-level factors have a significant effect on childhood immunisation. Policymakers should target improving community-level characteristics, such as community poverty, education levels, and the number of community-level ANC visits, to increase the national level of childhood immunisation. Public health intervention programs aiming at increasing awareness of childhood immunisation should include elements at both individual and community levels.

Indexed as

BangladeshChildhood immunisationCommunity-level factorsIndividual-level factorsMultilevel modelling

Identifiers

PMID37063304
PMCPMC10090204

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Registered trials

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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.