Single and Joint Associations Between Blood Cell-Based Inflammatory Indicator in Early Pregnancy and Risk of Gestational Diabetes Mellitus (GDM): A Prospective Cohort Study.

PROBLEM

This study aims to introduce the Bayesian kernel machine regression (BKMR) model to explore the single and joint associations between exposure to blood cell-based inflammatory in early pregnant women and gestational diabetes mellitus (GDM).

METHOD OF STUDY

The study included 536 singleton pregnant women from the Zunyi Birth Cohort. Logistic regression, restricted cubic spline regression, and BKMR were used to investigate single, nonlinear, and combined associations.

RESULTS

In this study, the adjusted odds ratio (OR) of white blood cell (WBC), neutrophil (NEUT), monocyte (MONO), platelet (PLT), neutrophil-to-lymphocyte ratio (NLR), and systemic immune inflammation index (SII) were 2.20 (95% confidence interval [CI]: 1.43-3.37), 2.27 (95% CI: 1.48-3.48), 1.67 (95% CI: 1.09-2.57), 1.66 (95% CI: 1.07-2.58), 1.65 (95% CI: 1.08-2.54), and 1.89 (95% CI: 1.23-2.91), respectively. Nonlinear associations of WBC (cutoff level: 7.91 × 10/L) and NEUT (cutoff level: 5.52 × 10/L) with GDM were also observed. Furthermore, BKMR analysis showed that the risk of GDM was linked with increased levels of blood cell-based inflammatory indicators.

CONCLUSION

In early pregnancy, multiple blood cell-based inflammatory indicators are significantly positively correlated with the risk of GDM. Specifically, WBC and NEUT counts exhibit the most prominent association with GDM risk. Therefore, more attention should be paid to the inflammation levels of early pregnant women.