Bridging data gaps in pregnancy outcomes: a four-year review of gestational Age records and delivery trends in Kilimanjaro region, Tanzania

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Introduction: Accurate gestational age (GA) documentation and reliable delivery data are essential for guiding clinical decision-making, classifying preterm and term births, and informing maternal health planning. In Tanzania, inconsistent GA recording and variable facility-based delivery patterns hinder effective monitoring of maternal and newborn outcomes. This study reviewed four years of delivery data to assess the completeness of GA documentation and explore delivery trends across urban and rural facilities in the Kilimanjaro Region. Methods: A retrospective cross-sectional trend analysis was conducted using delivery records from 2019 to 2022 across five health facilities. Maternal demographics, GA at delivery, and delivery outcomes were extracted. Completeness of GA documentation was assessed, and logistic regression was used to examine factors associated with (1) complete GA documentation and (2) delivery outcomes (preterm vs. term). Results: A total of 1,656 delivery records were reviewed. GA was documented in 78.4% of records, with higher completeness in urban (82.6%) than rural (69.8%) facilities. Institutional deliveries increased over the four years in both settings. Preterm births accounted for 12.3% of all deliveries, with higher prevalence in rural areas. In adjusted analyses, GA completeness was significantly associated with urban facility type (aOR = 1.74; 95% CI: 1.32-2.29), higher parity (aOR = 1.41; 95% CI: 1.05-1.90), and year of delivery (aOR = 1.26 per year; 95% CI: 1.11-1.43). Preterm birth was significantly associated with incomplete GA documentation (aOR = 2.08; 95% CI: 1.32-3.27). Conclusion: Delivery rates increased over time, but persistent gaps in GA documentation limit the accuracy of pregnancy classification and reporting. Improving documentation practices-particularly in rural facilities-is essential to strengthen maternal health data systems and inform evidence-based decision-making.

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