Prevalence and Predictors of Gestational Diabetes Mellitus in Sub-Saharan Africa: A 10-Year Systematic Review

Abstract

Background: Gestational diabetes mellitus (GDM) remains a global public health problem, which affects the well-being of mothers and their children in sub-Saharan Africa (SSA). Studies conducted in different geographical areas provide varied results on its prevalence and predictors. Understanding the extent and predictors of GDM in SSA is important for developing effective interventions and policies. Thus, this review aimed to investigate the prevalence of GDM and its predictive factors in sub-Saharan Africa.

Methods: We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) standards in this review. An extensive search of the PubMed, Web of Sciences and EMBASE databases was carried out covering papers from 2012 to 2022 to assess the prevalence and predictors of GDM. Microsoft Excel 2019 was utilised for study management. GraphPad Prism Version 8.0 and the MedCalc statistical software were employed for data analysis. The findings were analysed using textual descriptions, tables, forest plots and heat maps.

Results: Using 30 studies with 23,760 participants that satisfied the inclusion criteria, the review found the overall prevalence of GDM in SSA to be 3.05% (1.85%-4.54%). History of preterm delivery, alcohol consumption, family history of diabetes, history of stillbirths, history of macrosomia, overweight or obesity and advanced mother age were all significant predictors of gestational diabetes. Additionally, various biomarkers such as haemoglobin, adiponectin, leptin, resistin, visfatin, vitamin D, triglycerides and dietary intake type were identified as significant predictors of GDM.

Conclusion: In sub-Saharan Africa, there is a high pooled prevalence of gestational diabetes mellitus. In the light of the predictors of GDM identified in this review, it is strongly recommended to implement early screening for women at risk of developing gestational diabetes during their pregnancy. This proactive approach is essential for enhancing the overall well-being of both mothers and children.

Keywords: Ghana; diabetes; predictive factors; prevalence; sub‐Saharan Africa.

FIGURE 1

Schematic diagram of study selection in the review.

FIGURE 2

Prevalence of gestational diabetes mellitus in sub‐Saharan Africa. A forest plot representing the prevalence of gestational diabetes mellitus in sub‐Saharan Africa. The first column shows the names of the studies included, identified by the author's surname and the publication year. The second and third columns show the total study population for each respective study and the corresponding prevalence percentage (%), respectively. The fourth and fifth columns, respectively, present the estimated 95% confidence intervals for the proportions and the weights (expressed as percentages), which indicate the impact of each study on the combined result. The sixth column offers a visual depiction of the study outcomes. The small boxes positioned along the middle of the horizontal lines represent the effect estimates from individual studies, while a diamond shape represents the pooled result. The horizontal lines extending through the boxes illustrate the length of the 95% confidence interval.

FIGURE 3

Sociodemographic and clinical factors associated with gestational diabetes mellitus. AB, abortion; AL, alcohol; AMA, advance maternal age; FHD, family history of diabetes; HM, history of macrosomia; HPD, history of preterm delivery; HSB, history of stillbirth; LPA, low physical activity; O/O, overweight or obese; PHGDM, previous history of gestational diabetes mellitus.

FIGURE 4

Association between metabolic markers, micronutrients and gestational diabetes mellitus. APN, adiponectin; HB, haemoglobin; LTN, leptin; RTN, resistin; TG, triglyceride; VTD, vitamin D; VTN, visfatin.