Researchers uncover a consistent global link between antenatal depression and gestational diabetes, highlighting how early emotional support and screening could protect both maternal and newborn health.
Study: The impact of maternal depression during pregnancy on the risk of gestational diabetes mellitus: a meta-analysis. Image credit: Supagrit Ninkaesorn/Shutterstock.com
In a recent study published in the Frontiers in Endocrinology, a group of researchers quantified the association between depression in pregnancy and the subsequent risk of gestational diabetes mellitus using a meta-analysis of observational studies.
Background
About one in seven pregnancies faces gestational diabetes mellitus, yet the risk does not fall evenly across mothers. Depression in pregnancy is common and can alter biology through the hypothalamic-pituitary-adrenal (HPA) axis, raising cortisol and inflammation, impairing insulin action. In addition, depression is often linked with lifestyle factors such as reduced physical activity, poorer diet, and disrupted sleep, which may further contribute to metabolic dysregulation during pregnancy.
Families feel the effects: more clinic visits, tighter budgets, and anxiety about delivery and infant health. Screening tools such as the Edinburgh Postnatal Depression Scale (EPDS), the Self-Rating Depression Scale (SDS), and the Hospital Anxiety and Depression (HAD) scale flag women needing support. There are still uncertainties about how depression in pregnancy is associated with gestational diabetes mellitus; further research should close this gap.
About the study
The researchers systematically searched PubMed, Embase, the Cochrane Library, and Wanfang from inception to June 12, 2025, for observational studies linking depression in pregnancy with gestational diabetes mellitus. Eligible designs were cohort, case-control, or cross-sectional studies enrolling pregnant women, with exposure defined as depression during pregnancy and outcome as incident gestational diabetes mellitus.
They independently screened records and extracted study and participant characteristics. Depression was measured using EPDS, SDS, HAD, Center for Epidemiologic Studies Depression Scale-10 item version (CESD-10), or International Classification of Diseases, Ninth Revision (ICD-9) codes.
Gestational diabetes diagnosis followed study-specific criteria, often confirmed with an oral glucose tolerance test (OGTT). Study quality was appraised using the Newcastle-Ottawa Scale (NOS), with scores of six or more treated as high quality. Pooled odds ratios (ORs) with 95% confidence intervals (CIs) were calculated via a random-effects model; heterogeneity was assessed using Cochran’s Q and the I² statistic.
Subgroup analyses considered country, depression tool, and design; sensitivity analyses omitted influential studies; publication bias was tested with funnel plots and Egger’s and Begg’s tests. All analyses were conducted using STATA version 12.0, with statistical significance set at p < 0.05.
Study results
Eight studies met the inclusion criteria, covering the period 2013 to 2021 and totaling 125,451 pregnant women. The designs included five prospective cohort studies, one retrospective cohort study, and one case-control study, with participants drawn from the United States, Australia, and China.
Depression was assessed with standardized instruments like EPDS, SDS, HAD, and CESD-10 item version, or with ICD-9 diagnostic codes. Gestational diabetes mellitus was defined by study-level criteria and frequently verified by an oral glucose tolerance test. Most included studies were rated high quality on the NOS.
The pooled random-effects analysis showed that depression in pregnancy was associated with higher odds of gestational diabetes mellitus, with a summary OR of 1.37 and a 95% CI from 1.20 to 1.54. Between-study heterogeneity was low (I² = 9%), indicating consistency in direction and magnitude across settings.
Subgroup analyses supported accuracy: estimates were directionally similar when stratified by country, study design, and depression measure. Sensitivity analyses that excluded the largest study and the study with the widest confidence interval produced nearly identical results, confirming the stability of the association.
Publication bias appeared unlikely, as visual inspection of the funnel plot was symmetrical. Formal tests were negative, with Egger’s test p = 0.509 and Begg’s test p = 0.138. These checks suggest that a single influential study or selective reporting does not drive the association.
Descriptive data revealed important practical gaps. Most studies did not report whether participants received antidepressant treatment during pregnancy, limiting the ability to distinguish the effects of depression from potential medication-related metabolic effects. Covariate adjustment also varied across studies. Some cohorts controlled for age, body mass index, parity, smoking, and socioeconomic indicators, while others adjusted for fewer factors; despite this variability, the direction of the association was consistent.
The authors noted that previous meta-analyses had included fewer studies and lacked subgroup or sensitivity analyses, which limited earlier conclusions. By incorporating newer data and conducting these checks, the present analyses strengthened the evidence base for a reproducible link between antenatal depression and gestational diabetes.
Clinically, the meta-analytic signal indicates that depressive symptoms during pregnancy mark a group at elevated metabolic risk. While causation cannot be inferred from observational designs, the consistency of the OR across instruments and countries implies that routine mental-health assessment could help identify candidates for earlier glucose evaluation and timely lifestyle support. Early depression screening (for example, using the EPDS in the first trimester) might enable preventive counselling or earlier oral glucose tolerance testing for those at higher risk.
Overall, the analysis highlighted a consistent and reproducible link between depression during pregnancy and gestational diabetes mellitus, observed across multiple assessment tools and healthcare settings. These findings were stable across multiple sensitivity checks performed.
Conclusions
This meta-analysis indicates that depression in pregnancy is associated with a higher risk of gestational diabetes mellitus, with a summary OR of 1.37 and narrow confidence limits. Because most included data were observational, residual confounding cannot be excluded; however, the signal was consistent across countries, study designs, and depression measures, with low heterogeneity and no evident publication bias.
The authors recommend that prenatal care integrate validated mental-health screening alongside metabolic risk evaluation, as addressing psychological factors may help improve both mental and physical outcomes for mothers and infants. Integrating validated mental-health screening into routine prenatal care, earlier oral glucose tolerance testing, and supportive lifestyle counseling for those at risk may help improve maternal and neonatal outcomes.
Download your PDF copy now!
Scientists test whether chaya leaves can lower blood sugar in diabetes