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 pre-pregnancy fasting blood glucose, glycated hemoglobin and lipid profiles as blood biomarkers for gestational diabetes mellitus: evidence from a multigenerational cohort study.

BACKGROUND: Early prevention of gestational diabetes mellitus (GDM) is important to reduce the risk of adverse pregnancy outcomes and post-pregnancy cardiometabolic risk in women and offspring over the life course. This study aimed to investigate some blood biomarkers before pregnancy as GDM predictors. METHODS: We investigated the prospective association of blood biomarkers before pregnancy and GDM risk among women from the Mater-University of Queensland Study of Pregnancy (MUSP) cohort. A multiple logistic regression model was applied to estimate the odds of experiencing GDM by blood biomarkers. RESULTS: Out of 525 women included in this study, the prevalence of GDM was 7.43%. There was an increased risk of experiencing GDM among women who experienced obesity (Odds ratio = OR 2.4; 95% confidence interval = CI 1.6-3.7), had high fasting blood glucose (OR = 2.2; 95% CI = 1.3-3.8), high insulin (OR = 1.1; 95% CI = 1.0-1.2), high insulin resistance (OR = 1.2; 95% CI = 1.0-1.3) and low high-density lipoprotein (OR = 0.2; 95% CI = 0.1-0.7) before pregnancy. Adjustment for potential confounders, such as age, marital status, and BMI did not attenuate these associations substantially. CONCLUSION: The pre-pregnancy fasting blood glucose, insulin, and insulin resistance were independent predictors of GDM. They may be used as early markers for predicting the incidence of GDM.

Triceps skinfold thickness and body mass index and the risk of gestational diabetes mellitus: Evidence from a multigenerational cohort study.

BACKGROUND: Pre-pregnancy obesity is a well-recognized risk factor for gestational diabetes mellitus (GDM). There is a continuity of obesity from childhood to adolescence and then adulthood. However, it is unknown whether early childhood obesity predicts GDM. METHODS: We investigated the prospective association of childhood triceps skinfold thickness and body mass index (BMI) with GDM risk among women from the Mater-University of Queensland Study of Pregnancy (MUSP), a multigenerational cohort study. A multiple logistic regression model was applied to estimate the odds of experiencing GDM by childhood skinfold thickness and BMI. RESULTS: Out of 552 women in the study for whom data were available on triceps skinfold thickness and BMI at average age 5 (range 3-7) years old, 52 (9.42%) developed GDM by average age 30 (range 28-33) years. We found that the risk of developing GDM was greater among women who had greater skinfold thickness but not greater BMI at age 5 years. Women who were classified as overweight or obese based on skinfold thickness at age 5 years had an increased odds ratio of GDM compared to women who had normal skinfold thickness. This association remained significant after adjustment for the potential confounders (OR 2.74; 95% confidence interval=1.28-5.86). CONCLUSION: The risk of developing GDM was associated with higher skinfold thickness at age 5 years.

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.