A Bayesian Spatial Hierarchical Analysis of Cervical Cancer Screening Uptake in Ethiopia
Abstract:
Cervical cancer is the fourth most common cancer among women globally, with the highest burden in sub-Saharan Africa, where screening coverage remains far below the World Health Organization's 70% elimination target. Evidence on screening uptake in Ethiopia has been limited to small, facility-based studies unable to characterise national geographic patterns. This study aimed to identify individual-level and geographic determinants of cervical cancer screening uptake among Ethiopian women using a spatial Bayesian approach. Data were drawn from the 2024–25 Ethiopia Demographic and Health Survey (N = 20,864 women aged 15–49). A Bayesian hierarchical logistic regression model with a Besag–York–Mollié (BYM2) spatial random effect and a cluster random effect was fitted via integrated nested Laplace approximation, with fits compared across four nested specifications using the Watanabe–Akaike Information Criterion. Weighted national screening prevalence was 5.89%. Uptake rose with household wealth, education, and mass media exposure, and was higher among currently (aOR = 2.66) and formerly (aOR = 2.50) married women than never-married women. Region and cluster jointly explained 11.3% of residual variance, but only 23.2% of the regional component was spatially structured. Most of the more than 50-fold disparity between Addis Ababa (16.4%) and Somali (0.3%) reflected population composition rather than a residual regional effect, though a smaller, genuine geographic disparity persisted after adjustment. Screening uptake in Ethiopia is shaped jointly by individual-level disadvantage and geographic disparities not fully explained by population composition. Closing this gap will likely require expanded individual-level access, direct health-system investment in underserved regions such as Somali, and spatially explicit, subnational monitoring to ensure progress reaches the communities currently furthest behind.References:
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