Background: Antenatal care is directed toward ensuring healthy pregnancy outcomes. Quality antenatal care increases the likelihood of receiving an effective intervention to maintain maternal, fetal, and neonatal well-being, while poor quality is linked to poor pregnancy outcomes. However, owing to the complex nature of quality, researchers have followed several approaches to systematically measure it. The evidence from these variable approaches appears inconsistence and poses challenges to programmers and policymakers. Hence, it is imperative to obtain a pooled estimate of the quality of antenatal care. Therefore, considering the scarcity of evidence on the quality of antenatal care, this study aimed to review, synthesize, and bring pooled estimates of accessible evidence.
Objective: This study aimed to estimate the pooled magnitude and predictors of quality of antenatal care services and compare regional disparity.
Method: We conducted a comprehensive systematic three-step approach search of published and unpublished sources from 2002 to 2022. The methodological quality of eligible studies was checked using Joanna Briggs Institute critical appraisal tool for cross-sectional studies. Meta-analysis was carried out using STATA version 16. Statistical heterogeneity was assessed using Cochran's Q test. In the presence of moderate heterogeneity (I2 more than 50%), sensitivity and subgroup analyses were conducted and presented in a forest plot. Effect size was reported using standardized mean difference and its 95% confidence interval. Funnel plots and Egger's regression test were used to measure publication bias at the 5% significance level. A trim-and-fill analysis was conducted to adjust for publication bias. Pooled estimates were computed using random-effects models and weighted using the inverse variance method in the presence of high heterogeneity among studies. A 95% CI and 5% significance level were considered to declare significance variables.
Results: The global pooled poor-quality antenatal care was 64.28% (95% CI: 59.58%-68.98%) (I2 = 99.97%, p = 0.001). The identified pooled predictors of good-quality antenatal care service were: number of antenatal care visits (fourth and above antenatal care visit) (Adjusted odds ratio (AOR) = 2.6, 95% CI: 1.37-3.84), family wealth index (AOR = 2.72, 95% CI: 1.89-3.55), maternal education attainment (AOR = 3.03, 95% CI: 2.24-3.82), residence (urban dwellers) (AOR = 4.06, 95% CI: 0.95-7.17), and confidentiality antenatal care (AOR = 2.23, 95% CI: -0.36 to -4.82).
Conclusions: The study found regional and country-level disparities in the quality of antenatal care services for pregnant women, where poor-quality antenatal care services were provided for more than two-thirds to three-fourths of antenatal care attendants. Therefore, policymakers and health planners should put a great deal of emphasis on addressing the quality of antenatal care services.
Keywords: Antenatal care; pooled prevalence; poor quality; pregnant women.
This study aimed to estimate the magnitude, disparity, and predictors of the quality of antenatal care services. A comprehensive literature search was conducted from August 24/2022 to September 08/2022 found that a total of 76 studies with a sample size of 940,164 were included in the final analysis. The global pooled poor quality of antenatal care service utilization was 64.28%. The study found that nearly two-thirds of pregnant women worldwide received poor-quality antenatal care services, and nearly 3/4th of pregnant women in Ethiopia received poor-quality ANC. This study discovered continental, regional, and country-level disparities in the quality of antenatal care services, with pregnant women in the Asian, African, and South American continents using low-quality antenatal care services compared to those in North America and Europe. The authors strongly recommend providing high-quality antenatal care based on WHO recommendations globally for pregnant women in need of quality services at all levels to provide quality healthcare to the target population.
© The Author(s) 2024.