Evaluating the Adipose Tissue Depth as a Predictor Factor for Gestational Diabetes in Later Pregnancy-A Systematic Review

The increasing prevalence of gestational diabetes mellitus (GDM) requires non-invasive and precise techniques for evaluating the predisposing risk factors such as visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT). According to PRISMA, we developed a systematic review and searched after visceral adipose tissue AND gestational diabetes and identified 221 articles on the MEDLINE and Word of Science databases. After assessing them for inclusion criteria and two researchers screened them, 11 relevant articles were included. Although evidence is conflicting, more studies favor using US-determined VAT in GDM prediction. VAT may be more valuable than body mass index or SAT in predicting GDM. VAT can represent an additive factor to the prediction tool of the risk of developing GDM when used in conjunction with other anthropometric or biological parameters or maternal risk factors. US measurements are heterogeneous given different evaluation techniques, cut-off values and inter-operator variation. A significant limitation is the lack of a gold standard to identify GDM confidently. Pregnant women may benefit from early monitoring and preventive care if classified as high risk for GDM early in the gestational period. US-measured VAT during the first trimester of pregnancy seems a valuable and inexpensive screening approach to predict GDM development later in pregnancy, either by itself or if used in conjunction with other clinical and biological parameters.

Automated summary

The prevalence of gestational diabetes mellitus (GDM) has increased, calling for non-invasive and precise techniques to assess the risk factors such as visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT). A systematic review identified 11 relevant articles that favored using US-determined VAT in predicting GDM. VAT may be more valuable than body mass index or SAT in GDM prediction, and can be utilized in conjunction with other parameters or risk factors. However, US measurements are heterogeneous and the lack of a gold standard for GDM identification poses a limitation.