Geospatial Distribution and Predictors of Unmet Need for Contraception Among Women in Zaria LGA, Kaduna State,...

Despite the global increase in contraceptive use, millions of women in developing countries still wish to delay or avoid pregnancy but are not using any method of contraception for various reasons. This gap contributes to unintended pregnancies, thereby increasing the risk of unsafe abortions, as well as maternal and neonatal morbidity and mortality. This study aimed to assess the geospatial distribution and predictors of unmet need for contraception among married women in Zaria LGA.

A community-based cross-sectional study was conducted among 2,880 women selected from 90 enumeration areas using a two-stage stratified cluster sampling technique. Data were collected using two adapted standardized questionnaires. Spatial analysis and binary logistic regression were performed to identify spatial distribution and predictors of unmet need for contraception, with statistical analysis conducted using Stata version 17 and ArcGIS Pro version 3.1.

The overall prevalence of unmet need for contraception was 25.7%, comprising 15.2% for spacing and 10.5% for limiting. Spatial analysis revealed significant clustering of unmet need for contraception, with hotspot areas predominantly located in the rural parts of the LGA. Significant predictors of unmet need included women in the second wealth quintile (aOR = 1.370, 95% CI: 1.025-1.831), women who had ever born 1-2 children (aOR = 0.530, 95% CI: 0.301-0.792), and women whose most recent childbirth occurred 1-2 years prior to the survey (aOR = 1.530, 95% CI: 1.178-1.987).

Unmet need for contraception remains high in Zaria LGA. Spatial clustering and hotspot areas were predominantly observed in rural settings, highlighting persistent geographic inequities in access to and utilization of family planning services. Scaling up area-specific, community-based family planning interventions in identified hotspot areas may help reduce the burden of unmet need for contraception.