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Rural–urban differentials in the influences of individual and geospatial preparedness on institutional childbirth: a cross-sectional study in Bangladesh

OBJECTIVE: This study aims to explore the rural–urban differentials in the influences of individual and geospatial preparedness on institutional childbirth in Bangladesh. A related aim of this paper is to derive estimates to measure geospatial preparedness for institutional births, through statistic...

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Autores principales: Rahman, Md Mahabubur, Ara, Tasnim, Aninda, M H Hasib Mahmud Khan, Nurul, Alam, Haider, M Moinuddin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9445825/
https://www.ncbi.nlm.nih.gov/pubmed/36691141
http://dx.doi.org/10.1136/bmjopen-2021-060718
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author Rahman, Md Mahabubur
Ara, Tasnim
Aninda, M H Hasib Mahmud Khan
Nurul, Alam
Haider, M Moinuddin
author_facet Rahman, Md Mahabubur
Ara, Tasnim
Aninda, M H Hasib Mahmud Khan
Nurul, Alam
Haider, M Moinuddin
author_sort Rahman, Md Mahabubur
collection PubMed
description OBJECTIVE: This study aims to explore the rural–urban differentials in the influences of individual and geospatial preparedness on institutional childbirth in Bangladesh. A related aim of this paper is to derive estimates to measure geospatial preparedness for institutional births, through statistical modelling, when no data are available for measuring this areal indicator. DESIGN, SETTINGS AND PARTICIPANTS: The paper used data from a large-scale nationally representative Bangladesh Multiple Indicator Cluster Survey 2019. The analytical sample included 9203 currently married women of reproductive age who had a live birth in the 2 years preceding the survey. METHODS: Mixed effect logistic regression models were employed to explore the rural–urban differentials in influences of individual and geospatial preparedness on institutional childbirth. The district-level random effect estimation was done to measure geospatial preparedness. The conditional autoregressive model was used to examine the association of geospatial preparedness with areal variation in institutional births. RESULTS: In rural settings, women who gave birth to a female newborn were 18% less likely to have facility births compared with women who gave birth to a male newborn. Also, women from households in the highest wealth quintile were twice as likely to have facility births compared with those from households in the poorest wealth quintile. In contrast, in urban areas, facility births did not vary by sex of the fetus or by households’ socioeconomic status. The geospatial preparedness explained 8% and 9% of the variability in institutional births in rural and urban areas, respectively. Geospatial mapping revealed low preparedness in the hill tracts. Findings identified geospatial preparedness as a potential source of areal variation in facility births. CONCLUSION: Findings suggest improving district-level preparedness and developing differential programme strategies for urban and rural areas to increase the national prevalence and more equitable use of institutional childbirth in Bangladesh.
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spelling pubmed-94458252022-09-14 Rural–urban differentials in the influences of individual and geospatial preparedness on institutional childbirth: a cross-sectional study in Bangladesh Rahman, Md Mahabubur Ara, Tasnim Aninda, M H Hasib Mahmud Khan Nurul, Alam Haider, M Moinuddin BMJ Open Health Services Research OBJECTIVE: This study aims to explore the rural–urban differentials in the influences of individual and geospatial preparedness on institutional childbirth in Bangladesh. A related aim of this paper is to derive estimates to measure geospatial preparedness for institutional births, through statistical modelling, when no data are available for measuring this areal indicator. DESIGN, SETTINGS AND PARTICIPANTS: The paper used data from a large-scale nationally representative Bangladesh Multiple Indicator Cluster Survey 2019. The analytical sample included 9203 currently married women of reproductive age who had a live birth in the 2 years preceding the survey. METHODS: Mixed effect logistic regression models were employed to explore the rural–urban differentials in influences of individual and geospatial preparedness on institutional childbirth. The district-level random effect estimation was done to measure geospatial preparedness. The conditional autoregressive model was used to examine the association of geospatial preparedness with areal variation in institutional births. RESULTS: In rural settings, women who gave birth to a female newborn were 18% less likely to have facility births compared with women who gave birth to a male newborn. Also, women from households in the highest wealth quintile were twice as likely to have facility births compared with those from households in the poorest wealth quintile. In contrast, in urban areas, facility births did not vary by sex of the fetus or by households’ socioeconomic status. The geospatial preparedness explained 8% and 9% of the variability in institutional births in rural and urban areas, respectively. Geospatial mapping revealed low preparedness in the hill tracts. Findings identified geospatial preparedness as a potential source of areal variation in facility births. CONCLUSION: Findings suggest improving district-level preparedness and developing differential programme strategies for urban and rural areas to increase the national prevalence and more equitable use of institutional childbirth in Bangladesh. BMJ Publishing Group 2022-09-05 /pmc/articles/PMC9445825/ /pubmed/36691141 http://dx.doi.org/10.1136/bmjopen-2021-060718 Text en © Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) .
spellingShingle Health Services Research
Rahman, Md Mahabubur
Ara, Tasnim
Aninda, M H Hasib Mahmud Khan
Nurul, Alam
Haider, M Moinuddin
Rural–urban differentials in the influences of individual and geospatial preparedness on institutional childbirth: a cross-sectional study in Bangladesh
title Rural–urban differentials in the influences of individual and geospatial preparedness on institutional childbirth: a cross-sectional study in Bangladesh
title_full Rural–urban differentials in the influences of individual and geospatial preparedness on institutional childbirth: a cross-sectional study in Bangladesh
title_fullStr Rural–urban differentials in the influences of individual and geospatial preparedness on institutional childbirth: a cross-sectional study in Bangladesh
title_full_unstemmed Rural–urban differentials in the influences of individual and geospatial preparedness on institutional childbirth: a cross-sectional study in Bangladesh
title_short Rural–urban differentials in the influences of individual and geospatial preparedness on institutional childbirth: a cross-sectional study in Bangladesh
title_sort rural–urban differentials in the influences of individual and geospatial preparedness on institutional childbirth: a cross-sectional study in bangladesh
topic Health Services Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9445825/
https://www.ncbi.nlm.nih.gov/pubmed/36691141
http://dx.doi.org/10.1136/bmjopen-2021-060718
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