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Migration and interbirth transition rate using Benin Demographic and Health Survey data: Does episode-splitting matter?

BACKGROUND: The relationship between migration and fertility has vexed demographers for years. One issue missing in the literature is the lack of careful temporal consideration of when women migrate and specifically, the extent to which they do either before or after live births. OBJECTIVE: Here, we...

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Autores principales: Banougnin, Boladé Hamed, Somefun, Oluwaseyi Dolapo, Olakunle, Abibatou Agbéké
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8535178/
https://www.ncbi.nlm.nih.gov/pubmed/34679108
http://dx.doi.org/10.1371/journal.pone.0258297
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author Banougnin, Boladé Hamed
Somefun, Oluwaseyi Dolapo
Olakunle, Abibatou Agbéké
author_facet Banougnin, Boladé Hamed
Somefun, Oluwaseyi Dolapo
Olakunle, Abibatou Agbéké
author_sort Banougnin, Boladé Hamed
collection PubMed
description BACKGROUND: The relationship between migration and fertility has vexed demographers for years. One issue missing in the literature is the lack of careful temporal consideration of when women migrate and specifically, the extent to which they do either before or after live births. OBJECTIVE: Here, we opt for a more appropriate methodological approach to help remedy the complexity of the temporal aspect of migration and childbirth processes: regression models using the episode-splitting method. METHODS: This paper applies a rarely used methodological approach (episode-splitting) in the literature of migration-fertility relationship to investigate how internal in-migration is associated with inter-birth intervals among women in Cotonou, the largest city of Benin. Data comes from the 2017–2018 Benin Demographic and Health Survey (DHS) of women aged 15–49. Estimates from exponential regression models with episode-splitting were compared to estimates from exponential regression models without episode-splitting approach. Sensitivity analysis was also conducted to determine the robustness of the comparison between the two methods. Akaike Information Criteria (AIC) and Bayesian Information Criteria (BIC) were used to identify the method that provides models with best fit. RESULTS: The results from (standard) exponential regression models without episode-splitting show that there is no significant association between migration and interbirth transition rate. However, significant associations between migration and interbirth transition rate emerge after applying the episode splitting method. The hazard ratios (HR) of the transition to the next live birth are higher among migrant women than among nonmigrant women. This trend is persistent even after 10 years spent in Cotonou by migrant women. CONCLUSION: Exponential regression models with episode-splitting were of better fit than exponential regression models without episode-splitting. Sensitivity analysis conducted seems to confirm that models with episode-splitting produce estimates that are accurate, reliable and superior to models without episode-splitting. The results suggest a long-run process adaptation of migrants to lower fertility behaviours in Cotonou and are therefore consistent with the socialization hypothesis.
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spelling pubmed-85351782021-10-23 Migration and interbirth transition rate using Benin Demographic and Health Survey data: Does episode-splitting matter? Banougnin, Boladé Hamed Somefun, Oluwaseyi Dolapo Olakunle, Abibatou Agbéké PLoS One Research Article BACKGROUND: The relationship between migration and fertility has vexed demographers for years. One issue missing in the literature is the lack of careful temporal consideration of when women migrate and specifically, the extent to which they do either before or after live births. OBJECTIVE: Here, we opt for a more appropriate methodological approach to help remedy the complexity of the temporal aspect of migration and childbirth processes: regression models using the episode-splitting method. METHODS: This paper applies a rarely used methodological approach (episode-splitting) in the literature of migration-fertility relationship to investigate how internal in-migration is associated with inter-birth intervals among women in Cotonou, the largest city of Benin. Data comes from the 2017–2018 Benin Demographic and Health Survey (DHS) of women aged 15–49. Estimates from exponential regression models with episode-splitting were compared to estimates from exponential regression models without episode-splitting approach. Sensitivity analysis was also conducted to determine the robustness of the comparison between the two methods. Akaike Information Criteria (AIC) and Bayesian Information Criteria (BIC) were used to identify the method that provides models with best fit. RESULTS: The results from (standard) exponential regression models without episode-splitting show that there is no significant association between migration and interbirth transition rate. However, significant associations between migration and interbirth transition rate emerge after applying the episode splitting method. The hazard ratios (HR) of the transition to the next live birth are higher among migrant women than among nonmigrant women. This trend is persistent even after 10 years spent in Cotonou by migrant women. CONCLUSION: Exponential regression models with episode-splitting were of better fit than exponential regression models without episode-splitting. Sensitivity analysis conducted seems to confirm that models with episode-splitting produce estimates that are accurate, reliable and superior to models without episode-splitting. The results suggest a long-run process adaptation of migrants to lower fertility behaviours in Cotonou and are therefore consistent with the socialization hypothesis. Public Library of Science 2021-10-22 /pmc/articles/PMC8535178/ /pubmed/34679108 http://dx.doi.org/10.1371/journal.pone.0258297 Text en © 2021 Banougnin et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://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
Banougnin, Boladé Hamed
Somefun, Oluwaseyi Dolapo
Olakunle, Abibatou Agbéké
Migration and interbirth transition rate using Benin Demographic and Health Survey data: Does episode-splitting matter?
title Migration and interbirth transition rate using Benin Demographic and Health Survey data: Does episode-splitting matter?
title_full Migration and interbirth transition rate using Benin Demographic and Health Survey data: Does episode-splitting matter?
title_fullStr Migration and interbirth transition rate using Benin Demographic and Health Survey data: Does episode-splitting matter?
title_full_unstemmed Migration and interbirth transition rate using Benin Demographic and Health Survey data: Does episode-splitting matter?
title_short Migration and interbirth transition rate using Benin Demographic and Health Survey data: Does episode-splitting matter?
title_sort migration and interbirth transition rate using benin demographic and health survey data: does episode-splitting matter?
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8535178/
https://www.ncbi.nlm.nih.gov/pubmed/34679108
http://dx.doi.org/10.1371/journal.pone.0258297
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