Evidence map›Paper›PMID 39531459›Full record

ArticlePloS one2024

Mapping the prevalence and covariates associated with home delivery in Bangladesh: A multilevel regression analysis.

Rakhi Dey, Susmita Rani Dey, Meem Haque, Anushuya Binta Rahman, Satyajit Kundu, Sarmistha Paul Setu, U K Majumder

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Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Rakhi DeyStatistics Discipline, Khulna University, Khulna, Bangladesh.ORCID 0000-0001-9729-2828
Susmita Rani DeyStatistics Discipline, Khulna University, Khulna, Bangladesh.
Meem HaqueStatistics Discipline, Khulna University, Khulna, Bangladesh.
Anushuya Binta RahmanStatistics Discipline, Khulna University, Khulna, Bangladesh.
Satyajit KunduSchool of Medicine and Dentistry, Griffith University, Gold Coast, Australia.ORCID 0000-0001-9610-1479
Sarmistha Paul SetuStatistics Discipline, Khulna University, Khulna, Bangladesh.ORCID 0000-0001-7650-1125
U K MajumderStatistics Discipline, Khulna University, Khulna, Bangladesh.ORCID 0000-0002-1036-4815

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionBangladesh has made an intense effort to improve maternal healthcare facilities including facility delivery, but the number of home deliveries is still very high. Therefore, this study aims to find out district-wise prevalence and determine the individual and community-level predictors of home delivery among women in Bangladesh.

methodsData were derived from the Multiple Indicator Cluster Survey (MICS) 2019, a nationwide cross-sectional survey in Bangladesh. A final sample of 9,166 (weighted) women who gave birth in the two years preceding the survey were included in this study. Considering the two-stage cluster sampling strategy adopted by MICS, we used multilevel (2-level) logistic regression analysis to find out the correlates of home delivery.

resultsThe overall weighted prevalence of home delivery was 46.41% (95% confidence interval [CI]: 45.39-47.43). The highest prevalence was observed in Bandarban district (84.58%), while the lowest was found in Meherpur district (6.95%). The intercept-only regression model demonstrates that the likelihood of women from various clusters having home delivery varied significantly (variance: 1.47, standard error [SE]: 0.117), indicating the applicability of multilevel regression modeling. The multilevel regression analysis showed that women with higher education, wealth status and ANC visit, and those aged >18 years at first marriage/union were associated with lower odds of delivering child at home compared to their counterparts. While women from age group of 35-49 years, whose last pregnancy was unintended were more likely to deliver child at home. In addition, those respondents belonging to a community that had higher wealth status, women's education level, and exposure to media showed lower odds of having delivery at home.

conclusionsThe finding indicates that delivery at home is still high in Bangladesh. Targeted interventions to reduce home delivery are urgently needed in Bangladesh to tackle adversities during deliveries and save mothers from the consequences.

Indexed as

Home ChildbirthMultilevel AnalysisAdolescentAdultBangladeshCross-Sectional StudiesDelivery, ObstetricFemaleHumansLogistic ModelsMaternal Health ServicesMiddle AgedPregnancyPrenatal CarePrevalenceRegression Analysis

Identifiers

PMID39531459
PMCPMC11556713

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