Evidence map›Paper›PMID 35698030›Full record

ArticleBMC pregnancy and childbirth2022

Does dropout from school matter in taking antenatal care visits among women in Bangladesh? An application of marginalized poisson-poisson mixture model.

M Ershadul Haque, Taslim Sazzad Mallick, Wasimul Bari

Open access · goldAbstract read
In one paragraph

Article in BMC pregnancy and childbirth, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.4field-weighted citation impact, top 17% 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

2 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. 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 1 institution in 1 country.

M Ershadul HaqueDepartment of Statistics, University of Dhaka, Dhaka, 1000, Bangladesh. ershad_sbi@du.ac.bd.
Taslim Sazzad MallickDepartment of Statistics, University of Dhaka, Dhaka, 1000, Bangladesh.
Wasimul BariDepartment of Statistics, University of Dhaka, Dhaka, 1000, Bangladesh.
University of Dhaka · BD

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThere exists a lack of research in explaining the link between dropout from school and antenatal care (ANC) visits of women during pregnancy in Bangladesh. The aim of this study is to investigate how the drop out from school influences the ANC visits after controlling the relevant covariates using an appropriate count regression model.

methodsThe association between the explanatory variables and the outcome of interest, ANC visits, have been performed using one-way analysis of variance/independent sample t-test. To examine the adjusted effects of covariates on the marginal mean of count data, Marginalized Poison-Poisson mixture regression model has been fitted.

resultsThe estimated incidence rate of antenatal care visits was 10.6% lower for the mothers who were not continued their education after marriage but had at least 10 years of schooling (p-value <0.01) and 20.2% lower for the drop-outed mothers (p-value <0.01) than the mothers who got continued their education after marriage.

conclusionsTo ensure the WHO recommended 8+ ANC visits for the pregnant women of Bangladesh, it is essential to promote maternal education so that at least ten years of schooling should be completed by a woman and dropout from school after marriage should be prevented.

Indexed as

Pregnant PeoplePrenatal CareBangladeshEducational StatusFemaleHumansPatient Acceptance of Health CarePregnancySchoolsAntenatal careBDHSCount modelDropoutMarginalizedMixture

Identifiers

PMID35698030
PMCPMC9190147
OpenAlexW4282594476

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.