BMJ Open. 2026 Sep 22;16(9):e119640. doi: 10.1136/bmjopen-2026-119640.
ABSTRACT
OBJECTIVES: This study aimed to accurately assess the risk of gestational diabetes mellitus (GDM) and examine the interactive effects of first-trimester glycolipid metabolism and inflammatory factors on GDM development among women in southeastern China.
DESIGN: A case-control study.
SETTING: A primary and comprehensive hospital in rural Shanghai, China.
PARTICIPANTS: Participants were recruited from the electronic medical record database of Shanghai University of Medicine & Health Sciences Affiliated Zhoupu Hospital in 2019. A total of 678 participants with complete medical records were enrolled. Women were included if they (1) were registered Shanghai residents with no plans to move out of Shanghai within the following 2 years, (2) attended their first prenatal visit before the 20th week of gestation, (3) planned to give birth at Zhoupu Hospital and (4) had complete medical history and laboratory data as well as regular prenatal visits (≥6) before delivery. Women were excluded if they met any of the following criteria: (1) type I or II diabetes mellitus, (2) chronic hypertension, (3) prior drug treatment for dyslipidaemia, (4) cardiovascular diseases or (5) other diseases contraindicating pregnancy. We retrospectively collected data from the electronic health records of 2255 participants at the hospital in 2019. Ultimately, 678 pregnant women, including 133 with GDM and 545 with normal glucose tolerance, were included in the final analysis.
RESULTS: C-reactive protein (CRP), triglycerides (TG), lymphocyte count and glycated haemoglobin (HbA1c) were all associated with an increased risk of GDM (P trend<0.01). Conversely, high-density lipoprotein cholesterol (HDL-C) was associated with a reduced risk of GDM (P trend<0.01). Interaction analyses showed that CRP, TG, lymphocyte count and HbA1c exhibited significant multiplicative interactions with age in relation to GDM risk (all interaction p<0.01). No significant interactions were observed between HDL-C and age or body mass index (BMI) in relation to GDM risk (age, interaction p=0.339; pre-pregnancy BMI, interaction p=0.189). The Bayesian network model suggested that age, BMI, HDL-C, TG and lymphocyte count indirectly influenced GDM risk through intermediate pathways.
CONCLUSIONS: Elevated maternal glycolipid metabolism and altered inflammatory marker levels during early pregnancy may increase the risk of GDM in the rural area in Shanghai, China. The interactions among CRP, TG, lymphocyte count, HbA1c and age/BMI may contribute to GDM development. Future external validation studies are needed to confirm these findings in larger cohorts and more diverse populations.
PMID:42772864 | DOI:10.1136/bmjopen-2026-119640