Association of serum thyroid-stimulating hormone and bone mineral density in Chinese adults with normal thyroid function.

IF 3.9 2区医学 Q2 NUTRITION & DIETETICS

Nutrition & Metabolism Pub Date : 2024-08-07 DOI:10.1186/s12986-024-00841-9

Jia Chen, Lidong Hu, Ning Li, Wei Deng, Xiaojie Xu, Ling Wang, Kaiping Zhao, Shuai Lu, Xuejiao Liu, Xiaoguang Cheng, Xieyuan Jiang

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Abstract

Purpose: This study aims to investigate the association of serum TSH with BMD in Chinese adults with normal thyroid function.

Methods: These participants were divided into tertiles based on serum TSH levels. Linear regression model and multinomial logistic regression models were used to analyze the associations of continuous BMD and categorical BMD with serum TSH, respectively.

Results: In women younger than 60 years, BMD decreased with the increase of TSH at normal level, while in women older than 60 years, BMD increased with the increase of TSH at normal level; besides, the BMD of women younger than 60 years old was significantly higher than that of women over 60 years old (156.05 ± 39.34 mg/cm³ vs. 86.95 ± 29.51 mg/cm³, P < 0.001). Linear regression results showed negative associations of BMD and normal TSH level in women with age younger than 60 years (β=-4.34, P < 0.001), but this inverse trend was observed in women over 60 years old (β = 2.04, P = 0.041). Both in men younger than 60 years and over 60 years old, BMD decreased with the increase of TSH at normal levels; besides, the BMD of men younger than 60 years was significantly higher than those over 60 years old (143.08 ± 32.76 mg/cm³ vs. 108.13 ± 31.99 mg/cm³, P < 0.001).

Conclusions: The results demonstrated an opposite trend in BMD at normal TSH levels in younger and elder females, that is, in females younger than 60 years, BMD decreased with the increase of TSH, which indicated that TSH might play a different role in younger and elder females. However, this trend was not significant in males.

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甲状腺功能正常的中国成年人血清促甲状腺激素与骨矿物质密度的关系

目的：本研究旨在调查甲状腺功能正常的中国成年人血清促甲状腺激素与 BMD 的关系：方法：根据血清促甲状腺激素水平将参与者分为三组。方法：根据血清促甲状腺激素水平将参与者分为三等分，分别采用线性回归模型和多项式逻辑回归模型分析连续BMD和分类BMD与血清促甲状腺激素的关系：结果：在正常水平下，60 岁以下女性的 BMD 随 TSH 的升高而降低，而在正常水平下，60 岁以上女性的 BMD 随 TSH 的升高而升高；此外，60 岁以下女性的 BMD 显著高于 60 岁以上女性（156.05 ± 39.34 mg/cm3 vs. 86.95 ± 29.51 mg/cm3，P 3 vs. 108.13 ± 31.99 mg/cm3，P 结论：在正常水平下，60 岁以下女性的 BMD 随 TSH 的升高而降低，而 60 岁以上女性的 BMD 随 TSH 的升高而升高；在正常水平下，60 岁以下女性的 BMD 随 TSH 的升高而降低，而 60 岁以上女性的 BMD 随 TSH 的升高而升高：结果表明，在 TSH 水平正常的情况下，年轻女性和老年女性的 BMD 呈相反趋势，即在 60 岁以下的女性中，BMD 随 TSH 的升高而降低，这表明 TSH 在年轻女性和老年女性中可能起着不同的作用。然而，这一趋势在男性中并不显著。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Nutrition & Metabolism 医学-营养学

CiteScore

8.40

自引率

0.00%

发文量

审稿时长

4-8 weeks

期刊介绍： Nutrition & Metabolism publishes studies with a clear focus on nutrition and metabolism with applications ranging from nutrition needs, exercise physiology, clinical and population studies, as well as the underlying mechanisms in these aspects. The areas of interest for Nutrition & Metabolism encompass studies in molecular nutrition in the context of obesity, diabetes, lipedemias, metabolic syndrome and exercise physiology. Manuscripts related to molecular, cellular and human metabolism, nutrient sensing and nutrient–gene interactions are also in interest, as are submissions that have employed new and innovative strategies like metabolomics/lipidomics or other omic-based biomarkers to predict nutritional status and metabolic diseases. Key areas we wish to encourage submissions from include: -how diet and specific nutrients interact with genes, proteins or metabolites to influence metabolic phenotypes and disease outcomes; -the role of epigenetic factors and the microbiome in the pathogenesis of metabolic diseases and their influence on metabolic responses to diet and food components; -how diet and other environmental factors affect epigenetics and microbiota; the extent to which genetic and nongenetic factors modify personal metabolic responses to diet and food compositions and the mechanisms involved; -how specific biologic networks and nutrient sensing mechanisms attribute to metabolic variability.