Factors Determining Early Antenatal Care Utilization in Uganda

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Research ID 7NKJ2

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Abstract

Antenatal care utilization is a success story in Uganda (at least 90% of expectant mother received ANC), however, accessing first antenatal within the first three months of pregnancy is vital, a period for essential interventions like identification and management of obstetric complications. This study aimed at establishing factors contributing to early antenatal care service utilization in Uganda. The 2016 Uganda Demographic and Health Survey data was used. Andersen's Behavior model was used in determining the predictors while the binary logistic model was used to analyze the relationship between early antenatal care on age, highest maternal education level, marital status, wealth quintile, distance to health facility, cost of service, availability of health worker in community, exposure to media, nature of pregnancy and parity. Mothers who are age 19-35, completed primary seven, where distance is not a problem, with readily available community health workers and having no complicated pregnancy had relatively increased odds of early antenatal care utilization. Furthermore, mother aged 15-18, did not complete secondary level, not married, travel long distance to health facility, with cost of service being problematic, and parity were associated with reduced odds of early antenatal care utilization. The study recommends that policy makers should promote female education to primary seven completion hence delaying child marriages, reduction on costs of utilizing antenatal care by passing the insurance bill and encouraging pregnancy centering and sensitizing the public on benefits of early antenatal care utilization leading to improved maternal and newborn outcome during pregnancy.

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Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

Not applicable

Data Availability

The datasets used in this study are openly available at [repository link] and the source code is available on GitHub at [GitHub link].

Funding

This work did not receive any external funding.

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  • Classification

    NLMC CODE: WQ 200

  • Version of record

    v1.0

  • Issue date

    24 March 2021

  • Language

    English

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