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

Abstract

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.

Keywords:

• Gestational diabetes mellitus
• blood glucose
• lipid profile
• insulin resistance

Acknowledgments

We would like to thank The University of Queensland library for providing free access for a wide range of databases. We gratefully acknowledge the commitment of the Australian Government and the University of Queensland, Brisbane, QLD, Australia, to their research efforts. To undertake the Ph.D. degree, S.M.A is supported by the “Research Training Program” scholarship jointly funded by the Commonwealth Government of Australia and the University of Queensland, Brisbane, QLD, Australia.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.