Evidence map›Paper›PMID 42211096›Full record

ArticleFrontiers in nutrition2026

Analysis of the association between water iodine concentration and TyG-BMI index with thyroid diseases: a cross-sectional study in Shandong province, China.

Chun-Hu Li, Meng Zhao, Tong Zhao, Yu-Hang Liu, Zong-Yu Yue, Zhe-Xu Zhang, Xiang-Kun Zeng, Dian-Jun Sun, Peng Liu

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Article in Frontiers in nutrition, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Chun-Hu LiCenter for Endemic Disease Control, Harbin Medical University, Harbin, Heilongjiang, China.
Meng ZhaoCenter for Endemic Disease Control, Harbin Medical University, Harbin, Heilongjiang, China.
Tong ZhaoCenter for Endemic Disease Control, Harbin Medical University, Harbin, Heilongjiang, China.
Yu-Hang LiuCenter for Endemic Disease Control, Harbin Medical University, Harbin, Heilongjiang, China.
Zong-Yu YueCenter for Endemic Disease Control, Harbin Medical University, Harbin, Heilongjiang, China.
Zhe-Xu ZhangCenter for Endemic Disease Control, Harbin Medical University, Harbin, Heilongjiang, China.
Xiang-Kun ZengCenter for Endemic Disease Control, Harbin Medical University, Harbin, Heilongjiang, China.
Dian-Jun SunCenter for Endemic Disease Control, Harbin Medical University, Harbin, Heilongjiang, China.
Peng LiuCenter for Endemic Disease Control, Harbin Medical University, Harbin, Heilongjiang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Water iodine (WI) is a key factor influencing human thyroid function, and the TyG-BMI index, as a new metabolic indicator, can more comprehensively reflect an individual's metabolic status. This study aims to investigate the correlation between two potential influencing factors with thyroid diseases. Methods: To explore the associations between WI and TyG-BMI index with thyroid diseases, binary logistic regression analysis, interaction and mediation analyses were adopted to analyze linear associations. Restricted cubic spline regression was used to analyze nonlinear associations. Receiver Operating Characteristic curves and the Area Under the Curve (AUC) were utilized to evaluate the predictive accuracy of WI and TyG-BMI index for thyroid diseases. Results: In this study, among the 1,301 participants, the prevalence of thyroid diseases was significantly higher in females than in males. After adjusting for covariates, excessive WI, compared to adequate levels, was associated with higher odds of thyroiditis (OR = 1.76, 95% CI = 1.01-3.08), thyroid nodules (OR = 1.73, 95% CI = 1.16-2.58), hypothyroidism (OR = 1.94, 95% CI = 1.06-3.54), and multiple thyroid diseases (OR = 2.66, 95% CI = 1.50-4.71). Besides, TyG-BMI index in the fourth quartile (Q4) was also identified as a risk factor for thyroiditis (OR = 2.06, 95% CI = 1.13-3.76). Nonlinear analyses showed that WI and TyG-BMI had significant nonlinear correlation with thyroid nodules ( Conclusion: This study identified significant associations between WI and TyG-BMI with the prevalence of thyroid diseases. Therefore, for the prevention and control of thyroid diseases, it should be taken that targeted comprehensive measures from environmental (WI) and individual (TyG-BMI) perspectives.

Indexed as

interaction effectnonlinear correlationthyroid diseasesTyG-BMIwater iodine

Identifiers

PMID42211096
PMCPMC13212242

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