Socioeconomic and residence-based inequalities in adolescent fertility in 39 African countries
Ahinkorah, Bright Opoku, Aboagye, Richard Gyan, Mohammed, Aliu, Duodu, Precious Adade, Adnani, Qorinah Estiningtyas Sakilah, and Seidu, Abdul-Aziz (2024) Socioeconomic and residence-based inequalities in adolescent fertility in 39 African countries. Reproductive Health, 21. 72.
|
PDF (Published Version)
- Published Version
Available under License Creative Commons Attribution. Download (1MB) | Preview |
Abstract
Introduction: Despite the advancement in sexual and reproductive healthcare services and several public health measures aimed at controlling fertility rates, countries in sub-Saharan Africa (SSA) still experience higher adolescent fertility rates than other low-and middle-income countries. This study examined the disparities in adolescent fertility in 39 countries in SSA, focusing on socioeconomic and residence-based dimensions.
Methods: This study involved a secondary analysis of data obtained from 39 recent Demographic and Health Surveys conducted in SSA. The measures of difference (D), ratio (R), population attributable fraction (PAF), and population attributable risk (PAR) were estimated using the Health Equity Assessment Tool (HEAT) software version 3.1 developed by the World Health Organization. The measures: D, R, PAF, and PAR were used to examine the inequalities in adolescent fertility across the socioeconomic and residence-based dimensions.
Results: Out of the 39 countries included in the study, Guinea (D=27.70), Niger (D=27.50), Nigeria (D=23.90), and Côte d’Ivoire (D=23.60) exhibited the most significant residence-based inequalities in the rate of adolescent fertility, with the higher rate observed among adolescents in rural areas. Rwanda was the sole country that showed a slight inclination towards rural inequality in terms of the rate of adolescent fertility, with a value of D = -0.80. The burden of adolescent fertility was disproportionately higher among young women with low economic status across all the countries, exacerbating wealth-based inequities. The countries with the largest absolute discrepancies were Nigeria (D=44.70), Madagascar (D=41.10), Guinea (D=41.00), and Cameroon (D=40.20). We found significant disparities in educational attainment contributing to unequal inequalities in adolescent fertility, particularly among young women who lack access to formal education. Countries such as Madagascar (D=59.50), Chad (D=55.30), Cameroon (D=54.60), and Zimbabwe (D=50.30) had the most significant absolute disparities.
Conclusion: This study revealed that young women residing in rural areas, those in households with low economic status and those with limited educational opportunities experience a disproportionately high burden of adolescent fertility across the 39 countries in SSA. The current findings offer valuable information to governmental entities at all levels regarding the need to ensure the provision of equitable, accessible, and dependable sexual and reproductive health services to the populace, particularly for young women. Therefore, the various stakeholders need to enhance the effectiveness of health policies and legislation pertaining to adolescent women living in rural areas, those from economically disadvantaged households, and those with limited or no access to formal education. Such interventions could potentially reduce adolescent fertility rates and mitigate the adverse maternal and child outcomes associated with high adolescent fertility in SSA.
Item ID: | 85203 |
---|---|
Item Type: | Article (Research - C1) |
ISSN: | 1742-4755 |
Copyright Information: | © The Author(s) 2024. Open Access This 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/. The Creative Commons Public Domain Dedication waiver (http://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 |
Date Deposited: | 23 Apr 2025 00:33 |
FoR Codes: | 42 HEALTH SCIENCES > 4206 Public health > 420606 Social determinants of health @ 100% |
SEO Codes: | 20 HEALTH > 2002 Evaluation of health and support services > 200201 Determinants of health @ 100% |
More Statistics |