Article: Prevalence and factors which influence early antenatal booking among women of reproductive age in Tanzania: An analysis of data from the 2015-16 Tanzania Demographic Health Survey and Malaria Indicators Survey

Background: Early initiation of the antenatal clinic is vital as it allows early detection, management, and prevention of problems that may occur during pregnancy time. The analysis aimed to determine the prevalence and factors which influence early antenatal booking among women of reproductive age in Tanzania.

Method: The study used data from the 2015-16 Tanzania Demographic and Health Survey and Malaria Indicators Survey (2015-16 TDHS-MIS). A total of 6924 women of active reproductive age from 15 to 49 were included in the analysis. Both univariate and multiple regression analyses were used to determine predictors of early antenatal booking.

Results: Only 1586 (22.9%) of pregnant women had early antenatal booking. After adjusted for the confounders, factors which influenced early antenatal booking were age of a woman [20 to 34 years, Adjusted Odds Ratio (AOR) = 1.554 at 95% Confidence Interval (CI) = 1.213-1.993, and more than 34 years, AOR = 1.758 at 95% CI = 1.306-2.368]; wealth status [rich, AOR = 1.520 at 95% CI = 1.282-1.802]; education level [higher education, AOR = 2.355 at 95% CI = 1.36-4.079]; parity [Para 2 to 3, AOR = 0.85 at 95% CI = 0.727-0.994 and Para 5+, AOR = 0.577 at 95%CI = 0.465-0.715]; zones [Unguja, AOR = 0.433 at 95% CI = 0.284-0.658 and Pemba, AOR = 0.392 at 95% CI = 0.236-0.649].

Conclusion: Early antenatal booking in Tanzania is extremely low. Women who were more likely to initiate antenatal visits within the first 12 weeks are those from well-off families, those with higher education, primiparity women, and those from Tanzania mainland urban. The innovative interventional study is highly recommended to come up with an effective strategy to improve timing for antenatal booking.

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Prevalence and Factors Which Influence Early Antenatal Booking Among Women of Reproductive Age in Tanzania: An Analysis of Data from the 2015-16 Tanzania Demographic Health Survey and Malaria Indicators Survey