AI Uncovers Why Somali Women Choose to Stop Having Children

Machine‑learning on 9,000 surveys pins age, birth history, and clinic access as top drivers of fertility choices in world’s highest‑birth‑rate nation.

A groundbreaking Somali‑led AI study analyzes 9,000 women’s survey responses to predict fertility preferences with 81% accuracy—revealing age, number of children, and distance to health facilities as the strongest predictors. Learn how these insights can transform targeted family‑planning and maternal‑health programs across Somalia.

Somalia’s first AI‑driven fertility study marks a sea change in understanding why women choose more—or fewer—children. By applying a Random Forest model to nearly 9,000 survey responses, researchers predicted women’s desire for additional births with 81% accuracy. They then used SHAP values to reveal the three strongest drivers: age, number of living children, and distance to health care.

Age proved paramount. Women aged 45–49 were over five times more likely to want no more kids than teens aged 15–19. Childbirth history was next: those with seven or more children were three times likelier to stop childbearing than women with none. Finally, access to clinics shaped choices: women for whom distance was “not a big problem” were 1.5 times more likely to seek another child.

Regional divides and education gaps also loom large. Lower Juba women were nearly three times more inclined to end childbearing than their peers in Awdal. Meanwhile, 83% of participants had no formal schooling—a shortfall that tightens the link between proximity to care and fertility decisions.

These findings offer a laser‑sharp roadmap for action. Mobile clinics could bridge the access gap. Outreach in rural districts should target older mothers with large families. And long‑term, scaling girls’ education will reshape fertility norms.

In a country with the world’s highest birth rate, this AI study delivers clarity: targeted, data‑backed interventions can slow population growth, improve maternal health, and fuel sustainable development in even Somalia’s most remote corners.