Pooled prevalence of induced abortion and associated factors among reproductive age women in sub-Saharan Africa: a Bayesian multilevel approach
Fenta, Setegn Muche; Fenta, Haile Mekonnen; Yilema, Seyifemickael Amare; Mekie, Maru; Belay, Denekew Bitew; Mekonin, Amsalu Worku; Chen, Ding-Geng (2025-06-18)
Fenta, Setegn Muche
Fenta, Haile Mekonnen
Yilema, Seyifemickael Amare
Mekie, Maru
Belay, Denekew Bitew
Mekonin, Amsalu Worku
Chen, Ding-Geng
Springer
18.06.2025
Fenta, S.M., Fenta, H.M., Yilema, S.A. et al. Pooled prevalence of induced abortion and associated factors among reproductive age women in sub-Saharan Africa: a Bayesian multilevel approach. Arch Public Health 83, 159 (2025). https://doi.org/10.1186/s13690-025-01656-7
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© The Author(s) 2025. Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, 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 you modifed the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. 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-nc-nd/4.0/
https://creativecommons.org/licenses/by-nc-nd/4.0/
© The Author(s) 2025. Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, 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 you modifed the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. 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-nc-nd/4.0/
https://creativecommons.org/licenses/by-nc-nd/4.0/
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:oulu-202506234878
https://urn.fi/URN:NBN:fi:oulu-202506234878
Tiivistelmä
Abstract
Background
Abortion is one of the leading causes of maternal death in developing countries, particularly in sub-Saharan Africa (sSA,). In this region, abortion is responsible for 38,000 maternal deaths, making the area with the highest rate of abortion-related mortality in the world. This study aimed to examine the prevalence and associated factors of induced abortion in 33 countries in the region.
Method
We used data from the most current Demographic and Health Surveys (DHS) conducted in 33 sSA countries between 2012 and 2022. A total 367,881 of women were included in the analysis. The Bayesian multilevel logistic regression model was used to determine the factors associated to induced abortion because of the hierarchical nature of the DHS data.
Results
The overall prevalence of induced abortion was 16.50% in sSA. The random effects model revealed that about 75% of the variation in the induced abortion was caused by community and individual-level factors. Based on the Bayesian multilevel logistic regression model, women who smoke cigarettes(AOR = 1.044; 95%CI: 1.020, 1.070), 24-month and above birth interval(AOR = 5.747; 95%CI: 5.595, 5.889), rich women(AOR = 1.470, 95%CI: 1.436, 1.510), secondary and above-educated women (AOR = 2.640, 95%CI: 2.567, 2.707), being exposed to the media (AOR = 1.099, 95%CI: 1.083, 1.115), rural women (AOR = 1.025, 95%CI: 1.004, 1.047) and having pregnancy complications (AOR = 1.095, 95%CI: 1.067, 1.124) were associated with higher odds of induced abortion. But, the odds of an induced abortion were lower for women 35–49 years of age(AOR = 0.019, 95% CI: 0.018, 0.019), having 2–3 birth history(AOR = 0.105, 95%CI: 0.102, 0.107), having family size of 4–6 (AOR = 0.747; 95%CI: 0.735, 0.760), using contraception (AOR = 0.747; 95%CI: 0.735, 0.760), being married (AOR = 0.642; 95%CI: 0.628, 0.654), and being a working woman(AOR = 0.673; 95%CI: 0.658, 0.687).
Conclusion
The prevalence of induced abortion was high in the sSA countries with a significant country-specific variations. Therefore, public health programs shall focus on sexual and reproductive health education for young women, rural women, unmarried women, and rich women, in order to address this problem. Furthermore, it is crucial to formulate policies and initiatives that consider regional disparities in the prevalence of induced abortion and to actively pursue their implementation.
Background
Abortion is one of the leading causes of maternal death in developing countries, particularly in sub-Saharan Africa (sSA,). In this region, abortion is responsible for 38,000 maternal deaths, making the area with the highest rate of abortion-related mortality in the world. This study aimed to examine the prevalence and associated factors of induced abortion in 33 countries in the region.
Method
We used data from the most current Demographic and Health Surveys (DHS) conducted in 33 sSA countries between 2012 and 2022. A total 367,881 of women were included in the analysis. The Bayesian multilevel logistic regression model was used to determine the factors associated to induced abortion because of the hierarchical nature of the DHS data.
Results
The overall prevalence of induced abortion was 16.50% in sSA. The random effects model revealed that about 75% of the variation in the induced abortion was caused by community and individual-level factors. Based on the Bayesian multilevel logistic regression model, women who smoke cigarettes(AOR = 1.044; 95%CI: 1.020, 1.070), 24-month and above birth interval(AOR = 5.747; 95%CI: 5.595, 5.889), rich women(AOR = 1.470, 95%CI: 1.436, 1.510), secondary and above-educated women (AOR = 2.640, 95%CI: 2.567, 2.707), being exposed to the media (AOR = 1.099, 95%CI: 1.083, 1.115), rural women (AOR = 1.025, 95%CI: 1.004, 1.047) and having pregnancy complications (AOR = 1.095, 95%CI: 1.067, 1.124) were associated with higher odds of induced abortion. But, the odds of an induced abortion were lower for women 35–49 years of age(AOR = 0.019, 95% CI: 0.018, 0.019), having 2–3 birth history(AOR = 0.105, 95%CI: 0.102, 0.107), having family size of 4–6 (AOR = 0.747; 95%CI: 0.735, 0.760), using contraception (AOR = 0.747; 95%CI: 0.735, 0.760), being married (AOR = 0.642; 95%CI: 0.628, 0.654), and being a working woman(AOR = 0.673; 95%CI: 0.658, 0.687).
Conclusion
The prevalence of induced abortion was high in the sSA countries with a significant country-specific variations. Therefore, public health programs shall focus on sexual and reproductive health education for young women, rural women, unmarried women, and rich women, in order to address this problem. Furthermore, it is crucial to formulate policies and initiatives that consider regional disparities in the prevalence of induced abortion and to actively pursue their implementation.
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