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Examining the influence of correlates on different quantile survival times: infant mortality in Bangladesh

BACKGROUND: Several studies have identified factors influencing infant mortality, but, to the best of knowledge, no studies assessed the factors considering unequal effects on different survival times of infant mortality in Bangladesh. In this study, it was examined how a set of covariates behaves o...

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Autores principales: Jamee, Ahsan Rahman, Sen, Kanchan Kumar, Bari, Wasimul
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9617317/
https://www.ncbi.nlm.nih.gov/pubmed/36307785
http://dx.doi.org/10.1186/s12889-022-14396-y
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author Jamee, Ahsan Rahman
Sen, Kanchan Kumar
Bari, Wasimul
author_facet Jamee, Ahsan Rahman
Sen, Kanchan Kumar
Bari, Wasimul
author_sort Jamee, Ahsan Rahman
collection PubMed
description BACKGROUND: Several studies have identified factors influencing infant mortality, but, to the best of knowledge, no studies assessed the factors considering unequal effects on different survival times of infant mortality in Bangladesh. In this study, it was examined how a set of covariates behaves on different quantile survival times related with the infant mortality. METHODS: Data obtained from Bangladesh multiple indicator cluster survey (BMICS), 2019 have been used for purpose of the study. A total of 9,183 reproductive women were included in the study who gave their most recent live births within two years preceding the survey. Kaplan–Meier product limit approach has been applied to find the survival probabilities for the infant mortality, and the log-rank test has also been used to observe the unadjusted association between infant mortality and selected covariates. To examine the unequal effects of the covariates on different quantile survival time of infant mortality, the Laplace survival regression model has been fitted. The results obtained from this model have also been compared with the results obtained from the classical accelerated failure time (AFT) and Cox proportional hazard (Cox PH) models. RESULTS: The infant mortality in Bangladesh is still high which is around 28 per 1000 live births. In all the selected survival regression models, the directions of regression coefficients were similar, but the heterogenous effects of covariates on survival time were observed in quantile survival model. Several correlates such as maternal age, education, gender of index child, previous birth interval, skilled antenatal care provider, immediate breastfeeding etc. were identified as potential factors having higher impact on initial survival times. CONCLUSION: Infant mortality was significantly influenced by the factors more in the beginning of the infant's life period than at later stages, suggesting that receiving proper care at an early age will raise the likelihood of survival. Policy-making interventions are required to reduce the infant deaths, and the study findings may assist policy makers to revise the programs so that the sustainable development goal 3.2 can be achieved in Bangladesh.
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spelling pubmed-96173172022-10-30 Examining the influence of correlates on different quantile survival times: infant mortality in Bangladesh Jamee, Ahsan Rahman Sen, Kanchan Kumar Bari, Wasimul BMC Public Health Research BACKGROUND: Several studies have identified factors influencing infant mortality, but, to the best of knowledge, no studies assessed the factors considering unequal effects on different survival times of infant mortality in Bangladesh. In this study, it was examined how a set of covariates behaves on different quantile survival times related with the infant mortality. METHODS: Data obtained from Bangladesh multiple indicator cluster survey (BMICS), 2019 have been used for purpose of the study. A total of 9,183 reproductive women were included in the study who gave their most recent live births within two years preceding the survey. Kaplan–Meier product limit approach has been applied to find the survival probabilities for the infant mortality, and the log-rank test has also been used to observe the unadjusted association between infant mortality and selected covariates. To examine the unequal effects of the covariates on different quantile survival time of infant mortality, the Laplace survival regression model has been fitted. The results obtained from this model have also been compared with the results obtained from the classical accelerated failure time (AFT) and Cox proportional hazard (Cox PH) models. RESULTS: The infant mortality in Bangladesh is still high which is around 28 per 1000 live births. In all the selected survival regression models, the directions of regression coefficients were similar, but the heterogenous effects of covariates on survival time were observed in quantile survival model. Several correlates such as maternal age, education, gender of index child, previous birth interval, skilled antenatal care provider, immediate breastfeeding etc. were identified as potential factors having higher impact on initial survival times. CONCLUSION: Infant mortality was significantly influenced by the factors more in the beginning of the infant's life period than at later stages, suggesting that receiving proper care at an early age will raise the likelihood of survival. Policy-making interventions are required to reduce the infant deaths, and the study findings may assist policy makers to revise the programs so that the sustainable development goal 3.2 can be achieved in Bangladesh. BioMed Central 2022-10-28 /pmc/articles/PMC9617317/ /pubmed/36307785 http://dx.doi.org/10.1186/s12889-022-14396-y Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Jamee, Ahsan Rahman
Sen, Kanchan Kumar
Bari, Wasimul
Examining the influence of correlates on different quantile survival times: infant mortality in Bangladesh
title Examining the influence of correlates on different quantile survival times: infant mortality in Bangladesh
title_full Examining the influence of correlates on different quantile survival times: infant mortality in Bangladesh
title_fullStr Examining the influence of correlates on different quantile survival times: infant mortality in Bangladesh
title_full_unstemmed Examining the influence of correlates on different quantile survival times: infant mortality in Bangladesh
title_short Examining the influence of correlates on different quantile survival times: infant mortality in Bangladesh
title_sort examining the influence of correlates on different quantile survival times: infant mortality in bangladesh
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9617317/
https://www.ncbi.nlm.nih.gov/pubmed/36307785
http://dx.doi.org/10.1186/s12889-022-14396-y
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