Published in PLOS One on 2026-01-20, this study is presented as an attributed evidence briefing. The excerpts below are the original researchers’ words, reproduced under their Creative Commons Attribution licence. Health Signal has selected the abstract and, where needed, opening background paragraphs; the complete methods, results, limitations and references remain in the linked paper.
Original authors: Abraham Keffale Mengistu, Kerebih Getinet, Sefefe Birhanu Tizie, Mengistu Abebe Messelu, Ashagrie Anteneh, Meron Asmamaw Alemayehu, Andualem Enyew Gedefaw
Source: PLOS One • DOI 10.1371/journal.pone.0330960
Read the complete primary study ↗ · Creative Commons Attribution licence
From the researchers
Abstract
Long-acting reversible contraceptives (LARCs) are critical for reducing maternal mortality and unintended pregnancies, yet adoption remains low in Sub-Saharan Africa (SSA) due to systemic inequities, cultural barriers, and fragmented healthcare access. Despite global advancements, only 8% of women in SSA use LARCs, underscoring the need for data-driven insights to address this gap. This study applies machine learning (ML) to identify key predictors of LARC use and guide interventions.
Nationally representative data from 14,275 women across nine SSA countries were analyzed. Preprocessing included k-NN imputation and advanced class balancing (SMOTEENN). Feature engineering derived interaction terms (age×household size, education×media exposure) with SHAP-driven selection. Eight ML models were trained and hyperparameter-tuned using stratified cross-validation.
After hyperparameter tuning and class balancing, Random Forest achieved excellent discriminative performance (AUC-ROC: 1.00). Key predictors were household size (SHAP = 0.464), age at first contraceptive use (0.396), and current age (0.376). Socio-cultural factors (religion, marital status) showed negligible impact and were excluded. LARC uptake remained critically low (3.3%) with persistent rural-urban disparities.
The model’s key predictors directly inform policy; we recommend: 1) Mobile clinics for young women in large households, targeting the two strongest negative predictors (young age and large household size), 2) Media campaigns tailored to educated populations, leveraging the significant interaction between education and media exposure, and 3) Adolescent-focused education on contraceptive timing, addressing the critical predictor of age at first use.
Introduction
Family planning is a cornerstone of global health, directly influencing maternal and child survival, economic stability, and gender equality [1,2]. Access to modern contraceptives, as reported by the United Nations Population Fund (UNFPA), has empowered millions of women to exercise reproductive autonomy, reducing unintended pregnancies and maternal mortality by 44% since 1990 [3]. LARCs, such as intrauterine devices (IUDs) and implants, have emerged as critical tools in this effort. Their efficacy (>99%), reversibility, and low maintenance have driven a 15% global increase in adoption over the past decade [4–6]. Despite this progress, disparities persist: only 28% of women in low- and middle-income countries (LMICs) use modern contraceptives, compared to 68% in high-income nations [7,8]. These gaps reflect systemic inequities in healthcare access, education, and sociocultural norms that disproportionately affect marginalized populations.
SSA faces a unique reproductive health crisis. With the world’s highest fertility rate (4.7 births per woman) and a population projected to double by 2050, the region contends with strained healthcare systems, intergenerational poverty, and unmet contraceptive needs [9,10]. While initiatives like FP2020 improved contraceptive prevalence from 13% to 28% between 2012 and 2020, LARC adoption remains stagnant at 8% [11]. While international and regional efforts, such as the Family Planning 2020 (FP2020) initiative, have made progress in increasing contraceptive prevalence, the adoption of long-term methods remains disproportionately low. An estimated 24% of women in SSA report unmet family planning needs, driven by fragmented supply chains, provider shortages, and misconceptions about LARCs [12–14].
Reading this evidence
Use the full paper to check the study design, participant selection, comparator and outcome definitions before drawing a practical conclusion. An association does not by itself show cause and effect. A reported performance measure needs its denominator and uncertainty. A finding from a particular facility, sample or time period should retain that scope when it is discussed elsewhere.
This briefing makes the source accessible within the wider technology & industry desk. It does not assess an individual patient or certify a product. When considering relevance to another health system, examine the original authors’ account of context and limitations, then seek local implementation evidence. The related reporting below provides other studies to read alongside this one; it is a topic connection, rather than a claim that their results are directly comparable.
© 2026 Abraham Keffale Mengistu, Kerebih Getinet, Sefefe Birhanu Tizie, Mengistu Abebe Messelu, Ashagrie Anteneh, Meron Asmamaw Alemayehu, Andualem Enyew Gedefaw. Excerpts reproduced under CC BY. Selection, formatting and contextual notes by Health Signal. The researchers are the authors of the source study, not members of Health Signal’s staff.
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