Time to first antenatal care visit among pregnant women in Ethiopia: secondary analysis of EDHS 2016; application of AFT shared frailty models

Abstract Background The survival of pregnant women is one of great interest of the world and especially to a developing country like Ethiopia which had the highest maternal mortality ratios in the world due to low utilization of maternal health services including antenatal care (ANC). Survival analy...

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Autores principales:	Kenaw Derebe Fentaw, Setegn Muche Fenta, Hailegebrael Birhan Biresaw, Solomon Sisay Mulugeta
Formato:	article
Lenguaje:	EN
Publicado:	BMC 2021
Materias:	Acceleration failure time Frailty Inverse Gaussian shared frailty ANC Visit Public aspects of medicine RA1-1270
Acceso en línea:	https://doaj.org/article/be8b158ab0b44aa9bd22fb29b9575a18
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spelling	oai:doaj.org-article:be8b158ab0b44aa9bd22fb29b9575a182021-11-14T12:15:02ZTime to first antenatal care visit among pregnant women in Ethiopia: secondary analysis of EDHS 2016; application of AFT shared frailty models10.1186/s13690-021-00720-22049-3258https://doaj.org/article/be8b158ab0b44aa9bd22fb29b9575a182021-11-01T00:00:00Zhttps://doi.org/10.1186/s13690-021-00720-2https://doaj.org/toc/2049-3258Abstract Background The survival of pregnant women is one of great interest of the world and especially to a developing country like Ethiopia which had the highest maternal mortality ratios in the world due to low utilization of maternal health services including antenatal care (ANC). Survival analysis is a statistical method for data analysis where the outcome variable of interest is the time to occurrence of an event. This study demonstrates the applications of the Accelerated Failure Time (AFT) model with gamma and inverse Gaussian frailty distributions to estimate the effect of different factors on time to first ANC visit of pregnant women in Ethiopia. Methods This study was conducted by using 2016 EDHS data about factors associated with the time to first ANC visit of pregnant women in Ethiopia. A total of 4328 women from nine regions and two city administrations whose age group between 15 and 49 years were included in the study AFT models with gamma and inverse Gaussian frailty distributions have been compared using Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) to select the best model. Results The factors residence, media exposure, wealth index, education level of women, education level of husband and husband occupation are found to be statistically significant (P-value < 0.05) for the survival time of time to first ANC visit of pregnant women in Ethiopia. Inverse Gaussian shared frailty model with Weibull as baseline distribution is found to be the best model for the time to first ANC visit of pregnant women in Ethiopia. The model also reflected there is strong evidence of the high degree of heterogeneity between regions of pregnant women for the time to first ANC visit. Conclusion The median time of the first ANC visit for pregnant women was 5 months. From different candidate models, Inverse Gaussian shared frailty model with Weibull baseline is an appropriate approach for analyzing time to first ANC visit of pregnant women data than without frailty model. It is essential that maternal and child health policies and strategies better target women’s development and design and implement interventions aimed at increasing the timely activation of prenatal care by pregnant women. The researchers also recommend using more powerful designs (such as cohorts) for the research to establish timeliness and reduce death.Kenaw Derebe FentawSetegn Muche FentaHailegebrael Birhan BiresawSolomon Sisay MulugetaBMCarticleAcceleration failure timeFrailtyInverse Gaussian shared frailtyANCVisitPublic aspects of medicineRA1-1270ENArchives of Public Health, Vol 79, Iss 1, Pp 1-14 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Acceleration failure time Frailty Inverse Gaussian shared frailty ANC Visit Public aspects of medicine RA1-1270
spellingShingle	Acceleration failure time Frailty Inverse Gaussian shared frailty ANC Visit Public aspects of medicine RA1-1270 Kenaw Derebe Fentaw Setegn Muche Fenta Hailegebrael Birhan Biresaw Solomon Sisay Mulugeta Time to first antenatal care visit among pregnant women in Ethiopia: secondary analysis of EDHS 2016; application of AFT shared frailty models
description	Abstract Background The survival of pregnant women is one of great interest of the world and especially to a developing country like Ethiopia which had the highest maternal mortality ratios in the world due to low utilization of maternal health services including antenatal care (ANC). Survival analysis is a statistical method for data analysis where the outcome variable of interest is the time to occurrence of an event. This study demonstrates the applications of the Accelerated Failure Time (AFT) model with gamma and inverse Gaussian frailty distributions to estimate the effect of different factors on time to first ANC visit of pregnant women in Ethiopia. Methods This study was conducted by using 2016 EDHS data about factors associated with the time to first ANC visit of pregnant women in Ethiopia. A total of 4328 women from nine regions and two city administrations whose age group between 15 and 49 years were included in the study AFT models with gamma and inverse Gaussian frailty distributions have been compared using Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) to select the best model. Results The factors residence, media exposure, wealth index, education level of women, education level of husband and husband occupation are found to be statistically significant (P-value < 0.05) for the survival time of time to first ANC visit of pregnant women in Ethiopia. Inverse Gaussian shared frailty model with Weibull as baseline distribution is found to be the best model for the time to first ANC visit of pregnant women in Ethiopia. The model also reflected there is strong evidence of the high degree of heterogeneity between regions of pregnant women for the time to first ANC visit. Conclusion The median time of the first ANC visit for pregnant women was 5 months. From different candidate models, Inverse Gaussian shared frailty model with Weibull baseline is an appropriate approach for analyzing time to first ANC visit of pregnant women data than without frailty model. It is essential that maternal and child health policies and strategies better target women’s development and design and implement interventions aimed at increasing the timely activation of prenatal care by pregnant women. The researchers also recommend using more powerful designs (such as cohorts) for the research to establish timeliness and reduce death.
format	article
author	Kenaw Derebe Fentaw Setegn Muche Fenta Hailegebrael Birhan Biresaw Solomon Sisay Mulugeta
author_facet	Kenaw Derebe Fentaw Setegn Muche Fenta Hailegebrael Birhan Biresaw Solomon Sisay Mulugeta
author_sort	Kenaw Derebe Fentaw
title	Time to first antenatal care visit among pregnant women in Ethiopia: secondary analysis of EDHS 2016; application of AFT shared frailty models
title_short	Time to first antenatal care visit among pregnant women in Ethiopia: secondary analysis of EDHS 2016; application of AFT shared frailty models
title_full	Time to first antenatal care visit among pregnant women in Ethiopia: secondary analysis of EDHS 2016; application of AFT shared frailty models
title_fullStr	Time to first antenatal care visit among pregnant women in Ethiopia: secondary analysis of EDHS 2016; application of AFT shared frailty models
title_full_unstemmed	Time to first antenatal care visit among pregnant women in Ethiopia: secondary analysis of EDHS 2016; application of AFT shared frailty models
title_sort	time to first antenatal care visit among pregnant women in ethiopia: secondary analysis of edhs 2016; application of aft shared frailty models
publisher	BMC
publishDate	2021
url	https://doaj.org/article/be8b158ab0b44aa9bd22fb29b9575a18
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_version_	1718429370675101696

Time to first antenatal care visit among pregnant women in Ethiopia: secondary analysis of EDHS 2016; application of AFT shared frailty models

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