Xin-Yi Zhu, Xing-Chen Meng, Bei-Jing Cheng, Chun Wang, Jia Wang, Tian-Lin Li, Hui Li, Ke Meng, Ran Liu
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In the adjusted models, five indicators (OR<sub>Q4 vs. Q1</sub>: 1.30, 95% CI: 1.07–1.58 for fasting blood glucose; OR<sub>Q4 vs. Q1</sub>: 1.30, 95% CI: 1.08–1.57 for systolic blood pressure; OR<sub>Q4 vs. Q1</sub>: 1.26, 95% CI: 1.04–1.53 for diastolic blood pressure; OR<sub>Q4 vs. Q1</sub>: 1.23, 95% CI: 1.02–1.48 for white blood cell; OR<sub>Q4 vs. Q1</sub>: 1.28, 95% CI: 1.07–1.55 for neutrophil) were positively associated with the risk of thyroid nodules, while high-density lipoproteins (OR<sub>Q3 vs. Q1</sub>: 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. <i>Conclusions</i>. 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.","PeriodicalId":13966,"journal":{"name":"International Journal of Endocrinology","volume":"43 1","pages":""},"PeriodicalIF":2.3000,"publicationDate":"2024-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Associations of Combined Exposure to Metabolic and Inflammatory Indicators with Thyroid Nodules in Adults: A Nested Case-Control Study\",\"authors\":\"Xin-Yi Zhu, Xing-Chen Meng, Bei-Jing Cheng, Chun Wang, Jia Wang, Tian-Lin Li, Hui Li, Ke Meng, Ran Liu\",\"doi\":\"10.1155/2024/3950894\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<i>Objective</i>. To explore associations of combined exposure to metabolic/inflammatory indicators with thyroid nodules. <i>Methods</i>. 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. <i>Results</i>. In the adjusted models, five indicators (OR<sub>Q4 vs. Q1</sub>: 1.30, 95% CI: 1.07–1.58 for fasting blood glucose; OR<sub>Q4 vs. Q1</sub>: 1.30, 95% CI: 1.08–1.57 for systolic blood pressure; OR<sub>Q4 vs. Q1</sub>: 1.26, 95% CI: 1.04–1.53 for diastolic blood pressure; OR<sub>Q4 vs. Q1</sub>: 1.23, 95% CI: 1.02–1.48 for white blood cell; OR<sub>Q4 vs. Q1</sub>: 1.28, 95% CI: 1.07–1.55 for neutrophil) were positively associated with the risk of thyroid nodules, while high-density lipoproteins (OR<sub>Q3 vs. Q1</sub>: 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. <i>Conclusions</i>. 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.\",\"PeriodicalId\":13966,\"journal\":{\"name\":\"International Journal of Endocrinology\",\"volume\":\"43 1\",\"pages\":\"\"},\"PeriodicalIF\":2.3000,\"publicationDate\":\"2024-03-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Endocrinology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1155/2024/3950894\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENDOCRINOLOGY & METABOLISM\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Endocrinology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1155/2024/3950894","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENDOCRINOLOGY & METABOLISM","Score":null,"Total":0}
引用次数: 0
摘要
目的探讨代谢/炎症指标的综合暴露与甲状腺结节的关系。方法。我们回顾了 2020 年至 2021 年健康检查的个人数据。采用倾向得分匹配法,根据年龄和性别以 1 :4 的比例进行匹配。条件逻辑回归和贝叶斯核机器回归(BKMR)分别用于探讨单一代谢/炎症指标和混合指标与甲状腺结节的关系。结果显示在调整模型中,五个指标(空腹血糖 ORQ4 vs. Q1:1.30,95% CI:1.07-1.58;收缩压 ORQ4 vs. Q1:1.30,95% CI:1.08-1.57;舒张压 ORQ4 vs. Q1:1.26,95% CI:1.04-1.53;白细胞 ORQ4 vs. Q1:1.23,95% CI:1.02-1.而高密度脂蛋白(ORQ3 vs. Q1:0.75,95% CI:0.61-0.91)与甲状腺结节风险呈负相关。BKMR模型的单变量暴露-反应函数显示了类似的结果。此外,代谢和炎症混合物与甲状腺结节呈显著正相关,呈剂量-反应模式,收缩压是混合物中的最大贡献者(条件后纳入概率为 0.82)。五个指标之间没有发现交互效应。这些关联在男性、年龄较大(≥40 岁)的参与者和体重指数异常的个体中更为突出。结论代谢和炎症混合物的水平与甲状腺结节的发病风险呈线性剂量反应关系,其中收缩压水平是最重要的影响因素。
Associations of Combined Exposure to Metabolic and Inflammatory Indicators with Thyroid Nodules in Adults: A Nested Case-Control Study
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 (ORQ4 vs. Q1: 1.30, 95% CI: 1.07–1.58 for fasting blood glucose; ORQ4 vs. Q1: 1.30, 95% CI: 1.08–1.57 for systolic blood pressure; ORQ4 vs. Q1: 1.26, 95% CI: 1.04–1.53 for diastolic blood pressure; ORQ4 vs. Q1: 1.23, 95% CI: 1.02–1.48 for white blood cell; ORQ4 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 (ORQ3 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.
期刊介绍:
International Journal of Endocrinology is a peer-reviewed, Open Access journal that provides a forum for scientists and clinicians working in basic and translational research. The journal publishes original research articles, review articles, and clinical studies that provide insights into the endocrine system and its associated diseases at a genomic, molecular, biochemical and cellular level.