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A multilevel analysis of the predictors of health facility delivery in Ghana: Evidence from the 2014 Demographic and Health Survey

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  • Justice Moses K Aheto
  • Tracy Gates
  • Isaac Tetteh
  • Rahmatu Babah

Abstract

Health facility delivery has the potential to improve birth and general health outcomes for both newborns and mothers. Regrettably, not all mothers, especially in low-and-middle income countries like Ghana deliver at health facilities, and mostly under unhygienic conditions. Using data from the 2014 Ghana Demographic and Health Survey, we fitted both weighted single-level and random intercept multilevel binary logistic regression models to analyse predictors of a health facility delivery among mothers aged 15–49 years and to quantify unobserved household and community differences in the likelihood of health facility delivery. We analysed data on 4202 mothers residing in 3936 households and 427 communities. Of the 4202 mothers who delivered, 3031 (75.3%—weighted and 72.1%—unweighted) delivered at the health facility. Substantial unobserved household only (Median Odds Ratio (MOR) = 5.1) and household conditional on community (MOR = 4.7) level differences in the likelihood of health facility delivery were found. Mothers aged 25–34 (aOR = 1.4, 95%CI: 1.0–2.1) and 35–44 (aOR = 2.9, 95%CI: 1.7–4.8), mothers with at least a secondary education (aOR = 2.7, 95%CI: 1.7–4.1), with health insurance coverage (aOR = 1.6, 95%CI: 1.2–2.2) and from richer/richest households (aOR = 8.3, 95%CI: 3.6–19.1) and with piped water (aOR = 1.5, 95%CI: 1.1–2.1) had increased odds of health facility delivery. Mothers residing in rural areas (aOR = 0.3, 95%CI: 0.2–0.5) and with no religion (aOR = 0.5, 95%CI: 0.3–1.0) and traditional religion (aOR = 0.2, 95%CI: 0.1–0.6), who reported not wanting to go to health facilities alone as a big problem (aOR = 0.5, 95%CI: 0.3–0.8) and having a parity of 2 (aOR = 0.4, 95%CI: 0.3–0.7), 3 (aOR = 0.3, 95%CI: 0.2–0.6) and ≥4 (aOR = 0.3, 95%CI: 0.1–0.5) had reduced odds of health facility delivery. Our predictive model showed outstanding predictive power of 96%. The study highlights the need for improved healthcare seeking behaviours, maternal education and household wealth, and bridge the urban-rural gaps to improve maternal and newborn health outcomes.

Suggested Citation

  • Justice Moses K Aheto & Tracy Gates & Isaac Tetteh & Rahmatu Babah, 2024. "A multilevel analysis of the predictors of health facility delivery in Ghana: Evidence from the 2014 Demographic and Health Survey," PLOS Global Public Health, Public Library of Science, vol. 4(3), pages 1-17, March.
    • Handle: RePEc:plo:pgph00:0001254
    DOI: 10.1371/journal.pgph.0001254
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