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Modelling the number of antenatal care visits in Bangladesh to determine the risk factors for reduced antenatal care attendance

The existence of excess zeros in the distribution of antenatal care (ANC) visits in Bangladesh raises the research question of whether there are two separate generating processes in taking ANC and the frequency of ANC. Thus the main objective of this study is to identify a proper count regression mo...

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Autores principales: Bhowmik, Kakoli Rani, Das, Sumonkanti, Islam, Md. Atiqul
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6980537/
https://www.ncbi.nlm.nih.gov/pubmed/31978200
http://dx.doi.org/10.1371/journal.pone.0228215
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author Bhowmik, Kakoli Rani
Das, Sumonkanti
Islam, Md. Atiqul
author_facet Bhowmik, Kakoli Rani
Das, Sumonkanti
Islam, Md. Atiqul
author_sort Bhowmik, Kakoli Rani
collection PubMed
description The existence of excess zeros in the distribution of antenatal care (ANC) visits in Bangladesh raises the research question of whether there are two separate generating processes in taking ANC and the frequency of ANC. Thus the main objective of this study is to identify a proper count regression model for the number of ANC visits by pregnant women in Bangladesh covering the issues of overdispersion, zero-inflation, and intra-cluster correlation with an additional objective of determining risk factors for ANC use and its frequency. The data have been extracted from the nationally representative 2014 Bangladesh Demographic and Health Survey, where 22% of the total 4493 women did not take any ANC during pregnancy. Since these zero ANC visits can be either structural or sampling zeros, two-part zero-inflated and hurdle regression models are investigated along with the standard one-part count regression models. Correlation among response values has been accounted for by incorporating cluster-specific random effects in the models. The hurdle negative binomial regression model with cluster-specific random intercepts in both the zero and the count part is found to be the best model according to various diagnostic tools including likelihood ratio and uniformity tests. The results show that women who have poor education, live in poor households, have less access to mass media, or belong to the Sylhet and Chittagong regions are less likely to use ANC and also have fewer ANC visits. Additionally, women who live in rural areas, depend on family members’ decisions to take health care, and have unintended pregnancies had fewer ANC visits. The findings recommend taking both cluster-specific random effects and overdispersion and zero-inflation into account in modelling the ANC data of Bangladesh. Moreover, safe motherhood programmes still need to pay particular attention to disadvantaged and vulnerable subgroups of women.
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spelling pubmed-69805372020-02-04 Modelling the number of antenatal care visits in Bangladesh to determine the risk factors for reduced antenatal care attendance Bhowmik, Kakoli Rani Das, Sumonkanti Islam, Md. Atiqul PLoS One Research Article The existence of excess zeros in the distribution of antenatal care (ANC) visits in Bangladesh raises the research question of whether there are two separate generating processes in taking ANC and the frequency of ANC. Thus the main objective of this study is to identify a proper count regression model for the number of ANC visits by pregnant women in Bangladesh covering the issues of overdispersion, zero-inflation, and intra-cluster correlation with an additional objective of determining risk factors for ANC use and its frequency. The data have been extracted from the nationally representative 2014 Bangladesh Demographic and Health Survey, where 22% of the total 4493 women did not take any ANC during pregnancy. Since these zero ANC visits can be either structural or sampling zeros, two-part zero-inflated and hurdle regression models are investigated along with the standard one-part count regression models. Correlation among response values has been accounted for by incorporating cluster-specific random effects in the models. The hurdle negative binomial regression model with cluster-specific random intercepts in both the zero and the count part is found to be the best model according to various diagnostic tools including likelihood ratio and uniformity tests. The results show that women who have poor education, live in poor households, have less access to mass media, or belong to the Sylhet and Chittagong regions are less likely to use ANC and also have fewer ANC visits. Additionally, women who live in rural areas, depend on family members’ decisions to take health care, and have unintended pregnancies had fewer ANC visits. The findings recommend taking both cluster-specific random effects and overdispersion and zero-inflation into account in modelling the ANC data of Bangladesh. Moreover, safe motherhood programmes still need to pay particular attention to disadvantaged and vulnerable subgroups of women. Public Library of Science 2020-01-24 /pmc/articles/PMC6980537/ /pubmed/31978200 http://dx.doi.org/10.1371/journal.pone.0228215 Text en © 2020 Bhowmik et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Bhowmik, Kakoli Rani
Das, Sumonkanti
Islam, Md. Atiqul
Modelling the number of antenatal care visits in Bangladesh to determine the risk factors for reduced antenatal care attendance
title Modelling the number of antenatal care visits in Bangladesh to determine the risk factors for reduced antenatal care attendance
title_full Modelling the number of antenatal care visits in Bangladesh to determine the risk factors for reduced antenatal care attendance
title_fullStr Modelling the number of antenatal care visits in Bangladesh to determine the risk factors for reduced antenatal care attendance
title_full_unstemmed Modelling the number of antenatal care visits in Bangladesh to determine the risk factors for reduced antenatal care attendance
title_short Modelling the number of antenatal care visits in Bangladesh to determine the risk factors for reduced antenatal care attendance
title_sort modelling the number of antenatal care visits in bangladesh to determine the risk factors for reduced antenatal care attendance
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6980537/
https://www.ncbi.nlm.nih.gov/pubmed/31978200
http://dx.doi.org/10.1371/journal.pone.0228215
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