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Background: Gestational Diabetes Mellitus (GDM) is associated with several maternal and perinatal complications. Early detection and treatment can improve pregnancy outcomes. Objectives: To determine the prevalence, risk factors and predictors of GDM in early pregnancy at the University of Port Harcourt Teaching Hospital, (UPTH), Port Harcourt Nigeria. Methods: A cohort of 235 mothers who registered for antenatal care between 15 - 18 weeks of gestation at UPTH was prospectively studied. Their socio-demographic data, examination findings, anthropometric measurements, fasting blood sugar at booking and OGTT results at 28 weeks gestation were collated and entered into PC with SPSS for windows version 21.0 which was also used for the analysis. Variables were expressed as absolute numbers, percentages or means with standard deviations and significant differences determined using chi square test or the student “t” test as appropriate. The level of significance was set at P < 0.05. Results: Of the 235 participants, 35 (14.9%) developed GDM. Women who had GDM were significantly older (P = 0.001), had higher weight (t = 2.95, P = 0.01), BMI (t = 2.29, P = 0.02), abdominal skin fold thickness (t = 4.15, P = 0.001), blood pressure (t = 3.38, P = 0.001) compared to women who did not. Previous history of GDM was significantly different between two groups as χ2 = 93.56 and P = 0.001. Abdominal skin fold thickness and prior GDM history were found to be independent predictors of GDM on application of multiple logistic regression analysis. Conclusion: The prevalence of GDM in Port Harcourt is 14.9% and major risk factors are obesity, previous GDM history, advanced age and hypertension. Abdominal skin fold thickness ≥ 20 mm is an independent predictor. The risk of developing GDM can be predicted in early second trimester using algorithm incorporating risk factor screening and anterior abdominal wall skin fold thickness estimation.

Prediction of Gestational Diabetes Mellitus in Early Pregnancy: Is Abdominal Skin Fold Thickness 20 mm or More an Independent Risk Predictor?