Determinants of antenatal care and skilled birth attendance in sub-Saharan Africa: A multilevel analysis

Health Serv Res. 2019 Oct;54(5):1110-1118. doi: 10.1111/1475-6773.13163. Epub 2019 May 15.

Abstract

Objective: To determine individual- and country-level determinants of utilization of key maternal health services in sub-Saharan Africa (SSA).

Study setting: We used the most recent standard demographic and health survey data from the period of 2005 to 2015 for 34 SSA countries. Predictors of key maternal health service indicators were determined using a sample of 245 178 women who had at least one live birth 5 years preceding the survey.

Study design: We used a two-level hierarchical model, considering individual predictors at level one and country factors at level two of the hierarchy.

Principal findings: While the skilled birth attendance (SBA) utilization rate reached 53 percent during the study period, the recommended four or more antenatal care (ANC) coverage was commonly low with less significant differences among different groups of women and countries. Being in a middle-income country increased the individual-level association between ANC and SBA (OR = 2.34, 95% CI: 1.24, 4.44). Less privileged women with lower education level were less likely to receive maternal health services.

Conclusions: This study reveals the existence of wide gaps between ANC and SBA coverage in SSA. Urgent policy attention is required to improve access, utilization, and quality of maternal health services.

Keywords: antenatal care; multilevel analysis; skilled birth attendance; sub-Saharan Africa.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Africa South of the Sahara
  • Birthing Centers / statistics & numerical data*
  • Female
  • Health Care Surveys / statistics & numerical data*
  • Humans
  • Maternal Health Services / statistics & numerical data*
  • Multilevel Analysis
  • Patient Acceptance of Health Care / statistics & numerical data*
  • Pregnancy
  • Prenatal Care / statistics & numerical data*
  • Socioeconomic Factors