Abstract
OBJECTIVE: To explore associations of combined exposure to metabolic/inflammatory indicators with thyroid nodules. METHODS: We reviewed personal data for health screenings from 2020 to 2021. A propensity score matching method was used to match 931 adults recently diagnosed with thyroid nodules in a 1 : 4 ratio based on age and gender. Conditional logistic regression and Bayesian kernel machine regression (BKMR) were used to explore the associations of single metabolic/inflammatory indicators and the mixture with thyroid nodules, respectively. RESULTS: In the adjusted models, five indicators (OR(Q4 vs. Q1): 1.30, 95% CI: 1.07-1.58 for fasting blood glucose; OR(Q4 vs. Q1): 1.30, 95% CI: 1.08-1.57 for systolic blood pressure; OR(Q4 vs. Q1): 1.26, 95% CI: 1.04-1.53 for diastolic blood pressure; OR(Q4 vs. Q1): 1.23, 95% CI: 1.02-1.48 for white blood cell; OR(Q4 vs. Q1): 1.28, 95% CI: 1.07-1.55 for neutrophil) were positively associated with the risk of thyroid nodules, while high-density lipoproteins (OR(Q3 vs. Q1): 0.75, 95% CI: 0.61-0.91) were negatively associated with the risk of thyroid nodules. Univariate exposure-response functions from BKMR models showed similar results. Moreover, the metabolic and inflammatory mixture exhibited a significant positive association with thyroid nodules in a dose-response pattern, with systolic blood pressure being the greatest contributor within the mixture (conditional posterior inclusion probability of 0.82). No interaction effects were found among the five indicators. These associations were more prominent in males, participants with higher age (≥40 years old), and individuals with abnormal body mass index status. CONCLUSIONS: Levels of the metabolic and inflammatory mixture have a linear dose-response relationship with the risk of developing thyroid nodules, with systolic blood pressure levels being the most important contributor.