Spatial distribution and determinants of unmet need for family planning among all reproductive‑age women in Uganda: a multi‑level logistic regression modeling approach and spatial analysis.

Introduction: Unmet need for family planning is defined as the percentage of sexually active and fecund women who want to delay the next birth (birth spacing) or who want to stop childbirth (birth limiting) beyond two years but who are not using any modern or traditional method of contraception. Despite the provision of family planning services, the unmet need of family planning remains a challenge in low- and middle-income countries (LMICs). Thus, this study aimed to assess the spatial distribution and determinant factors of unmet need for family planning among all reproductive‑age women in Uganda.

Methods: A secondary data analysis was done based on 2016 Ugandan Demographic and Health Surveys (UDHS). Total weighted samples of 18,506 women were included. Data processing and analysis were performed using SPSS Version 26, STATA 14.2, ArcGIS 10.8, and SaTScan 10.1.2 software. Spatial autocorrelation and hotspot analysis was made using Global Moran's index (Moran's I) and Gettis-OrdGi*statistics, respectively. Determinants of unmet needs for family planning were identified by multi-level logistic regression analysis. Variables with a p-value < 0.05 were declared statistically significant predictors.

Results: The spatial distribution of unmet need for family planning among women of reproductive age in Uganda was found to be clustered (Global Moran's I = 0.27, Z-score of 12.71, and p-value < 0.0001). In the multivariable multilevel logistic regression analysis; women in West Nile (AOR = 1.86, 95% CI: 1.39, 2.47), aged 25-49 years old (AOR = .84; 95% CI .72, .99), highly educated (AOR = .69; 95% CI .54, .88), Muslim (AOR = 1.20, 95% CI: 1.03, 1.39), high wealth status (AOR = .73, 95% CI: .64, .82), and had five or more living child (AOR = 1.69, 95% CI: 1.51, 1.88) were significant predictors of unmet need for family planning. Significant hotspot areas were identified in West Nile, Acholi, Teso, and Busoga regions.

Conclusion: A significant clustering of unmet need for family planning were found in Uganda. Moreover, age, educational status, religion, wealth status, number of alive children, and region were significant predictors of unmet need for family planning. Therefore, in order to minimize the burdens associated with unmet need, an interventions focusing on promotion of sexual and reproductive health service should be addressed to the identified hotspot areas.