Time trends and projections in the prevalence of gestational diabetes mellitus in Queensland, Australia, 2009-2030: Evidence from the Queensland Perinatal Data Collection

BACKGROUND

Gestational diabetes mellitus (GDM) is the fastest-growing type of diabetes in Australia. We aimed to assess the time trends during 2009-2018 and projections of GDM in Queensland, Australia up to 2030.

MATERIALS AND METHODS

The study data were from the Queensland Perinatal Data Collection (QPDC) and included data on 606 662 birth events with the births reported from at least 20 weeks gestational age or birth weight at least 400 g. Bayesian regression model was used to assess the trends in the prevalence of GDM.

RESULTS

The prevalence of GDM increased from 5.47 to 13.62% from 2009 to 2018 (average annual rate of change, AARC = +10.71%). If the trend remains the same, the projected prevalence will increase to 42.04% (95% uncertainty interval = 34.77-48.96) by 2030. Observing AARC across different subpopulations, we found that the trend of GDM increased markedly among women living in inner regional areas (AARC = +12.49%), were non-Indigenous (AARC = +10.93%), most disadvantaged (AARC = +11.84%), aged either of two age groups (AARC = +18.45% and + 15.17% for <20 years and 20-24 years, respectively), were with obesity (AARC = +11.05%) and smoked during pregnancy (AARC = +12.26%).

CONCLUSIONS

Overall, the prevalence of GDM has sharply increased in Queensland, and if this trend continues, about 42% of pregnant women will experience GDM by 2030. The trends vary across different subpopulations. Therefore, targeting the most vulnerable subpopulations is vital to prevent the development of GDM.

The association of general obesity, central obesity and visceral body fat with the risk of gestational diabetes mellitus: Evidence from a systematic review and meta-analysis

BACKGROUND

Studies consistently reported that general obesity predicts gestational diabetes mellitus (GDM). However, whether other phenotypes of obesity such as central obesity and visceral adiposity might have differential associations as risk factors of GDM are less known. The objective of this study was to investigate the association of all these obesity phenotypes in developing GDM.

METHODS

PubMed, CINHAL, Embase, Scopus, Google Scholar and Web of Science were searched. Full-text research articles published in English from 1985 to February 2020 with cohort and cross-sectional studies design and reported an association between obesity and GDM were included. Case-control studies, case reports, conference abstract, women with previous metabolic disorders and articles considered general obesity only were excluded. A bias adjusted-quality effect meta-analysis was conducted to evaluate the association of these obesity phenotypes and GDM risk.

RESULTS

Twenty studies met the inclusion criteria representing data of ∼50 thousand women at the reproductive age with ∼7% prevalence of GDM. Meta-analysis of 14 datasets revealed that the three types of obesity were significantly associated with an increased risk of GDM. In addition, visceral adiposity was a stronger risk factor for GDM than other obesity phenotypes (odd ratio = 3.25, 95% confidence interval = 2.01-5.26) versus (odd ratio = 2.73, 95% confidence interval = 2.20-3.38) for general obesity and (odd ratio = 2.53, 95% confidence interval = 2.04-3.14) for central obesity.

CONCLUSION

The findings of this study suggest that general obesity, central obesity and visceral body fat were associated with an increased risk of GDM. Furthermore, the association with maternal visceral adiposity was more robust compared to general obesity and central obesity.