# Effect of myo-inositol on the prevention of gestational diabetes in high-risk pregnant women: An RCT

## TL;DR

This study found that myo-inositol may help reduce the risk of gestational diabetes in high-risk pregnant women.

## Contribution

The novel contribution is evidence that myo-inositol supplementation reduces gestational diabetes risk in a randomized controlled trial.

## Key findings

- Myo-inositol treatment was associated with a significant reduction in gestational diabetes mellitus (aRR: 0.58, 0.36, 0.91, p = 0.020).
- No significant differences were observed in other pregnancy outcomes or glycemia levels between the groups.
- The study suggests myo-inositol could be a preventive intervention for GDM, though more research is needed.

## Abstract

Gestational diabetes mellitus (GDM) is a rising problem which, if not diagnosed and treated in time, can lead to maternal, fetal, and neonatal complications. Therefore, it is very important to consider predisposing factors and prevention of GDM.

This study aims to investigate the effect of myo-inositol (MI) on the prevention of GDM and other pregnancy outcomes.

This randomized controlled trial was conducted at the Arash Women's hospital and Yas hospital Complex, Tehran, Iran between November 2019 and May 2020 and included 150 women; the study was divided into 2 groups (n = 75/each). Women received 4000 mg of MI plus 400 mg of folic acid daily in the MI group and 400 mg of folic acid in the placebo group from 11–14 gestational weeks for 14 wk. Participants underwent 75 gr oral glucose tolerance test at 24–28 wk and were followed up until delivery.

After adjustment for confounding factors, MI treatment was associated with a significant reduction of GDM (aRR: 0.58, 0.36, 0.91, p = 0.020). However, no significant difference was observed between the 2 groups in cases of other pregnancy outcomes and glycemia at each step of oral glucose tolerance test values.

Our results showed that MI significantly reduced GDM. With insufficient evidences, more studies with an appropriate sample size are recommended.