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Title

Physical activity affects dysthyreosis by thyroid hormones sensitivity: a population-based study.

Authors

Zhang, Shu-yang; Hu, Xue-qing; Xiang, Cheng; Xiang, Tao; Guo, Song-xue; Zhi, Fei-hu; Zhao, Ping; Zhu, Jia-yan; Zhang, Chen-yang

Abstract

Objective: Physical activity (PA) plays an important role in human health. However, the relationship between the PA and dysthyreosis was not clear. This study aimed to explore this question. Methods: We performed a population-based study on the basis of the participant's information that was collected from the National Health and Nutrition Examination Survey (NHANES) database. The association of the thyroid hormone and total PA metabolic equivalent task (MET) were assessed via linear regression analysis with adjusting for different covariates. Moreover, we also used path analysis to explore the causality between PA, thyroid hormone index, and dysthyreosis. The restricted cubic spline analysis was used to explore the non-linear relationship between the thyroid hormone index and the PA total MET. Results: A total of 2118 participants aged≥20, including 969 females and 1149 males, were collected from NHANES. The linear regression with multivariate adjustment suggested a linear relationship between the PA total MET and Thyroid-Stimulating Hormone Index (TSHI), and Thyroid Feedback Quantile-Based Index (TFQI), respectively. And TFQI and dysthyresis occurrence were significantly correlated (P<0.05). The path analysis showed that the PA total MET affected dysthyreosis occurrence by TFQI. In addition, we found a non-linear relationship between the total PA met and dysthyreosis via restricted cubic spline analysis. Conclusions: PA was significantly correlated with dysthyreosis via thyroid hormone sensitivity. Therefore, it can be considered to prevent the occurrence of dysthyreosis by regulating thyroid hormone sensitivity through PA in daily life.

Subjects

HYPOTHALAMIC-pituitary-thyroid axis; NATIONAL Health & Nutrition Examination Survey; METABOLIC equivalent; THYROID hormones; PATH analysis (Statistics)

Publication

Frontiers in Endocrinology, 2024, p1

ISSN

1664-2392

Publication type

Academic Journal

DOI

10.3389/fendo.2024.1418766

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