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Exploiting the Bayesian approach to derive counts of married women of reproductive age across Cameroon for healthcare planning, 2000–2030
Estimates of married women of reproductive age (MWRA) are needed for policy decisions to enhance reproductive health. Given the unavailability in Cameroon, this study aimed to derive MWRA counts by regions and divisions from 2000 to 2030. Data included 1976, 1987, and 2005 censuses with 606,542 wome...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9613669/ https://www.ncbi.nlm.nih.gov/pubmed/36302837 http://dx.doi.org/10.1038/s41598-022-23089-w |
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author | Nsashiyi, Raïssa Shiyghan Rahman, Md Mizanur Ndam, Lawrence Monah Hashizume, Masahiro |
author_facet | Nsashiyi, Raïssa Shiyghan Rahman, Md Mizanur Ndam, Lawrence Monah Hashizume, Masahiro |
author_sort | Nsashiyi, Raïssa Shiyghan |
collection | PubMed |
description | Estimates of married women of reproductive age (MWRA) are needed for policy decisions to enhance reproductive health. Given the unavailability in Cameroon, this study aimed to derive MWRA counts by regions and divisions from 2000 to 2030. Data included 1976, 1987, and 2005 censuses with 606,542 women, five Demographic and Health Surveys from 1991 to 2018 with 48,981 women, and United Nations World Population Prospects from 1976 to 2030. Bayesian models were used in estimating fertility rates, net-migration, and finally, MWRA counts. The total MWRA population in Cameroon was estimated to increase from 2,260,665 (2,198,569–2,352,934) to 6,124,480 (5,862,854–6,482,921), reflecting a 5.7 (5.2–6.2) percentage points (%p) annual rise from 2000–2030. The Centre and Far North regions host the largest numbers, projected to reach 1,264,514 (1,099,373–1,470,021) and 1,069,814 (985,315–1,185,523), respectively, in 2030. The highest divisional-level increases are expected in Mfoundi [14.6%p (11.2–18.8)] and Bénoué [14.9%p (11.1–20.09). This study’s findings, showing varied regional- and divisional-level estimates of and trends in MWRA counts should set a baseline for determining the demand for programmes such as family planning, and the scaling of relevant resources sub-nationally. |
format | Online Article Text |
id | pubmed-9613669 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-96136692022-10-29 Exploiting the Bayesian approach to derive counts of married women of reproductive age across Cameroon for healthcare planning, 2000–2030 Nsashiyi, Raïssa Shiyghan Rahman, Md Mizanur Ndam, Lawrence Monah Hashizume, Masahiro Sci Rep Article Estimates of married women of reproductive age (MWRA) are needed for policy decisions to enhance reproductive health. Given the unavailability in Cameroon, this study aimed to derive MWRA counts by regions and divisions from 2000 to 2030. Data included 1976, 1987, and 2005 censuses with 606,542 women, five Demographic and Health Surveys from 1991 to 2018 with 48,981 women, and United Nations World Population Prospects from 1976 to 2030. Bayesian models were used in estimating fertility rates, net-migration, and finally, MWRA counts. The total MWRA population in Cameroon was estimated to increase from 2,260,665 (2,198,569–2,352,934) to 6,124,480 (5,862,854–6,482,921), reflecting a 5.7 (5.2–6.2) percentage points (%p) annual rise from 2000–2030. The Centre and Far North regions host the largest numbers, projected to reach 1,264,514 (1,099,373–1,470,021) and 1,069,814 (985,315–1,185,523), respectively, in 2030. The highest divisional-level increases are expected in Mfoundi [14.6%p (11.2–18.8)] and Bénoué [14.9%p (11.1–20.09). This study’s findings, showing varied regional- and divisional-level estimates of and trends in MWRA counts should set a baseline for determining the demand for programmes such as family planning, and the scaling of relevant resources sub-nationally. Nature Publishing Group UK 2022-10-27 /pmc/articles/PMC9613669/ /pubmed/36302837 http://dx.doi.org/10.1038/s41598-022-23089-w Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Nsashiyi, Raïssa Shiyghan Rahman, Md Mizanur Ndam, Lawrence Monah Hashizume, Masahiro Exploiting the Bayesian approach to derive counts of married women of reproductive age across Cameroon for healthcare planning, 2000–2030 |
title | Exploiting the Bayesian approach to derive counts of married women of reproductive age across Cameroon for healthcare planning, 2000–2030 |
title_full | Exploiting the Bayesian approach to derive counts of married women of reproductive age across Cameroon for healthcare planning, 2000–2030 |
title_fullStr | Exploiting the Bayesian approach to derive counts of married women of reproductive age across Cameroon for healthcare planning, 2000–2030 |
title_full_unstemmed | Exploiting the Bayesian approach to derive counts of married women of reproductive age across Cameroon for healthcare planning, 2000–2030 |
title_short | Exploiting the Bayesian approach to derive counts of married women of reproductive age across Cameroon for healthcare planning, 2000–2030 |
title_sort | exploiting the bayesian approach to derive counts of married women of reproductive age across cameroon for healthcare planning, 2000–2030 |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9613669/ https://www.ncbi.nlm.nih.gov/pubmed/36302837 http://dx.doi.org/10.1038/s41598-022-23089-w |
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