Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Nsashiyi, Raïssa Shiyghan, Rahman, Md Mizanur, Ndam, Lawrence Monah, Hashizume, Masahiro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
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
_version_ 1784820026309607424
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
work_keys_str_mv AT nsashiyiraissashiyghan exploitingthebayesianapproachtoderivecountsofmarriedwomenofreproductiveageacrosscameroonforhealthcareplanning20002030
AT rahmanmdmizanur exploitingthebayesianapproachtoderivecountsofmarriedwomenofreproductiveageacrosscameroonforhealthcareplanning20002030
AT ndamlawrencemonah exploitingthebayesianapproachtoderivecountsofmarriedwomenofreproductiveageacrosscameroonforhealthcareplanning20002030
AT hashizumemasahiro exploitingthebayesianapproachtoderivecountsofmarriedwomenofreproductiveageacrosscameroonforhealthcareplanning20002030