Estimating the impact of change in pre-pregnancy body mass index on development of Gestational Diabetes Mellitus: An Australian population-based cohort

Incident Diabetes in Women With Patterns of Gestational Diabetes Occurrences Across 2 Pregnancies

Importance

Gestational diabetes is a type 2 diabetes risk indicator, and recurrence further augments risk. In women with a single occurrence across 2 pregnancies, it is unclear whether first- vs second-pregnancy gestational diabetes differ in terms of risk.

Objective

To compare the hazards of incident diabetes among those with gestational diabetes in the first, in the second, and in both pregnancies with women without gestational diabetes in either.

Design, Setting, and Participants

This was a retrospective cohort study with cohort inception from April 1, 1990, to December 31, 2012. Follow-up was April 1, 1990, to April 1, 2019. Participants were mothers with 2 singleton deliveries between April 1, 1990, and December 31, 2012, without diabetes before or between pregnancies, who were listed in public health care insurance administrative databases and birth, stillbirth, and death registries in Quebec, Canada. Data were analyzed from July to December 2023.

Exposure

Gestational diabetes occurrence(s) across 2 pregnancies.

Main outcomes and measures

Incident diabetes from the second delivery until a third pregnancy, death, or the end of the follow-up period, whichever occurred first.

Results

The 431 980 women with 2 singleton deliveries studied had a mean (SD) age of 30.1 (4.5) years at second delivery, with a mean (SD) of 2.8 (1.5) years elapsed between deliveries; 373 415 (86.4%) were of European background, and 78 770 (18.2%) were at the highest quintile of material deprivation. Overall, 10 920 women (2.5%) had gestational diabetes in their first pregnancy, 16 145 (3.7%) in their second, and 8255 (1.9%) in both (12 205 incident diabetes events; median [IQR] follow-up 11.5 [5.3-19.4] years). First pregnancy-only gestational diabetes increased hazards 4.35-fold (95% CI, 4.06-4.67), second pregnancy-only increased hazards 7.68-fold (95% CI, 7.31-8.07), and gestational diabetes in both pregnancies increased hazards 15.8-fold (95% CI, 15.0-16.6). Compared with first pregnancy-only gestational diabetes, second pregnancy-only gestational diabetes increased hazards by 76% (95% CI, 1.63-1.91), while gestational diabetes in both pregnancies increased it 3.63-fold (95% CI, 3.36-3.93).

Conclusions and relevance

In this retrospective cohort study of nearly half a million women with 2 singleton pregnancies, both the number and ordinal pregnancy of any gestational diabetes occurrence increased diabetes risk. These considerations offer greater nuance than an ever or never gestational diabetes dichotomy.

Maternal body mass index and risk of fetal overgrowth in women with gestational diabetes Mellitus in Southeast China: a retrospective cohort study

BACKGROUND

To investigate the relationship between body mass index (BMI) changes and large for gestational age (LGA) in women with gestational diabetes mellitus (GDM).

METHODS

A retrospective cohort study including 10,486 women with GDM was conducted. A dose‒response analysis of BMI changes and the occurrence of LGA was performed. Binary logistic regressions were performed to assess crude and adjusted odds ratios (ORs) and 95% confidence intervals (CIs). Receiver operating characteristic (ROC) curves and areas under the curve (AUCs) were used to assess the ability of BMI changes to predict LGA.

RESULTS

The probability of LGA increased with increasing BMI. The risk of LGA increased across the BMI change quartiles. The BMI change remained positively associated with the risk of LGAafter stratification analysis. The AUC was 0.570 (95% CI: 0.557 ~ 0.584)in the entire study population, and the best optimal predictive cut-off value was 4.922, with a sensitivity of 0.622 and a specificity of 0.486. The best optimal predictive cut-off value decreased from the underweight group to the overweight and obese group.

CONCLUSIONS

BMI changes are related to the risk of LGA and may be a useful predictor of the incidence of LGA in singleton pregnant women with GDM.

Efficacy of dietary supplements targeting gut microbiota in the prevention and treatment of gestational diabetes mellitus

Gestational diabetes mellitus (GDM) is a kind of metabolic disease occurring during gestation period, which often leads to adverse pregnancy outcomes and seriously harms the health of mothers and infants. The pathogenesis of GDM may be bound up with the abnormal gut microbiota composition in pregnant women. Previous studies have clarified that dietary supplements can regulate the gut microbiota to play a role. Therefore, using dietary supplements, such as probiotics, prebiotics, and synbiotics to target the gut microbiota to regulate the disordered gut microbiota would become a potential method that benefits for preventing and treating GDM. This paper reviews a series of clinical trials in recent years, expounds on the clinical effects of dietary supplements such as probiotics on GDM, and discusses the intervention effects of dietary supplements on GDM related risk factors, including overweight, obesity, and type 2 diabetes mellitus (T2DM). In addition, the relationship of GDM and gut microbiota is also discussed, and the possible mechanisms of dietary supplements are summarized. This review will help to promote the further development of dietary supplements targeting gut microbiota and provide more knowledge support for clinical application in the prevention and treatment of various diseases.

Simulation of 3D Body Shapes for Pregnant and Postpartum Women

Several studies have reported that pre-pregnant women’s body mass index (BMI) affects women’s weight gain with complications during pregnancy and the postpartum weight retention. It is important to control the BMI before, during and after pregnancy. Our objectives are to develop a technique that can compute and visualize 3D body shapes of women during pregnancy and postpartum in various gestational ages, BMI, and postpartum durations. Body changes data from 98 pregnant and 83 postpartum women were collected, tracked for six months, and analyzed to create 3D model shapes. This study allows users to simulate their 3D body shapes in real-time and online, based on weight, height, and gestational age, using multiple linear regression and morphing techniques. To evaluate the results, precision tests were performed on simulated 3D pregnant and postpartum women’s shapes. Additionally, a satisfaction test on the application was conducted on new 149 mothers. The accuracy of the simulation was tested on 75 pregnant and 74 postpartum volunteers in terms of relationships between statistical calculation, simulated 3D models and actual tape measurement of chest, waist, hip, and inseam. Our results can predict accurately the body proportions of pregnant and postpartum women.