Trends and Determinants of Caesarean Section among Reproductive-age Women (2004/05-2022): A Multilevel Analysis of Demographic and Health Survey

BackgroundCaesarean section (CS) rates have risen significantly worldwide, including Tanzania, reflecting improved but uneven access to this life-saving intervention. These increasing rates in Sub-Saharan Africa call for studies to examine trends with the presence of increased maternal morbidity and mortality. We aimed to investigate the trends and determinants of CS among reproductive-age women using Tanzania Demographic and Health Survey (TDHS) data. MethodsAn analytical cross-sectional study using pooled data from multiple TDHS spanning from 2004/05 to 2022 was conducted. The study included 24,213 women of reproductive age, selected through a two-stage sampling method. Multilevel logistic regression, accounting for the complex survey design, was used to identify individual and community-level determinants of CS. Analyses were conducted using Stata 18.5. Adjusted odds ratio (AOR) with 95% confidence intervals (CI) were reported, and statistical significance was set at p < 0.05. ResultsThe overall prevalence of CS was 6.8% (95% CI: 6.3-7.3), showing a significant increasing trend from 4.0% in 2004/05 to 10.7% in 2022 (p<0.001). At the individual level, older age, primary and secondary education, attending more than four antenatal care (ANC) visits, and belonging to higher wealth quintiles were associated with a higher likelihood of CS delivery. Conversely, ever being married or cohabiting was associated with lower odds of CS delivery. At the community level, women in poor communities had a lower likelihood of CS delivery, while geographical zones also showed significant variations in CS delivery likelihood. ConclusionThe rising trend of CS in Tanzania, coupled with the identified individual and community-level determinants, underscores the importance of addressing disparities in access and utilization. Policies and interventions should focus on ensuring equitable access to CS based on need, considering both individual vulnerabilities and community contexts across different geographical zones.