{"title":"Metabolic score and its components are associated with carotid plaque prevalence in young adults.","authors":"Jingwen Fan, Yongli Yang, Xiaocan Jia, Yuping Wang, Chenyu Zhao, Nana Wang, Suying Ding, Xuezhong Shi","doi":"10.1007/s12020-024-03903-3","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose: </strong>No study has comprehensively assessed the relationship of metabolic factors including insulin resistance, hypertension, hyperuricemia, and hypercholesterolemia with the development of carotid plaque. Therefore, we constructed metabolic scores based on the above metabolic factors and examined its association with carotid plaque in young and older Chinese adults.</p><p><strong>Methods: </strong>This study included 17,396 participants who underwent carotid ultrasound examinations, including 14,173 young adults (<65 years) and 3,223 older adults (≥65 years). Individual metabolic score was calculated using triglyceride-glucose (TyG) index, mean arterial pressure (MAP), uric acid, and total cholesterol (TC). Logistic regression models were conducted to examine the role of metabolic score and its components in the prevalence of carotid plaque. The nonlinear relationship was examined using restricted cubic spline regression. Meanwhile, subgroup, interaction, and sensitivity analyses were conducted.</p><p><strong>Results: </strong>The multivariate logistic regression analysis showed that TyG (OR: 1.088; 95%CI: 1.046-1.132), MAP (OR: 1.121; 95%CI: 1.077-1.168), TC (OR: 1.137; 95%CI: 1.094-1.182) and metabolic score (OR: 1.064; 95%CI: 1.046-1.082) were associated with carotid plaque prevalence in young adults rather than older adults. The nonlinear association was not observed for metabolic scores and carotid plaque. Subgroup analyses showed significant associations between metabolic scores and carotid plaque prevalence in men, women, normal-weight, and overweight young adults. No interaction of metabolic score with sex and BMI were observed.</p><p><strong>Conclusions: </strong>The results support that control of TyG, MAP, TC, and metabolic scores is a key point in preventing the prevalence of carotid plaque in the young adults.</p>","PeriodicalId":49211,"journal":{"name":"Endocrine","volume":" ","pages":"592-599"},"PeriodicalIF":3.0000,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Endocrine","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s12020-024-03903-3","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/6/7 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"ENDOCRINOLOGY & METABOLISM","Score":null,"Total":0}
引用次数: 0
Abstract
Purpose: No study has comprehensively assessed the relationship of metabolic factors including insulin resistance, hypertension, hyperuricemia, and hypercholesterolemia with the development of carotid plaque. Therefore, we constructed metabolic scores based on the above metabolic factors and examined its association with carotid plaque in young and older Chinese adults.
Methods: This study included 17,396 participants who underwent carotid ultrasound examinations, including 14,173 young adults (<65 years) and 3,223 older adults (≥65 years). Individual metabolic score was calculated using triglyceride-glucose (TyG) index, mean arterial pressure (MAP), uric acid, and total cholesterol (TC). Logistic regression models were conducted to examine the role of metabolic score and its components in the prevalence of carotid plaque. The nonlinear relationship was examined using restricted cubic spline regression. Meanwhile, subgroup, interaction, and sensitivity analyses were conducted.
Results: The multivariate logistic regression analysis showed that TyG (OR: 1.088; 95%CI: 1.046-1.132), MAP (OR: 1.121; 95%CI: 1.077-1.168), TC (OR: 1.137; 95%CI: 1.094-1.182) and metabolic score (OR: 1.064; 95%CI: 1.046-1.082) were associated with carotid plaque prevalence in young adults rather than older adults. The nonlinear association was not observed for metabolic scores and carotid plaque. Subgroup analyses showed significant associations between metabolic scores and carotid plaque prevalence in men, women, normal-weight, and overweight young adults. No interaction of metabolic score with sex and BMI were observed.
Conclusions: The results support that control of TyG, MAP, TC, and metabolic scores is a key point in preventing the prevalence of carotid plaque in the young adults.
期刊介绍:
Well-established as a major journal in today’s rapidly advancing experimental and clinical research areas, Endocrine publishes original articles devoted to basic (including molecular, cellular and physiological studies), translational and clinical research in all the different fields of endocrinology and metabolism. Articles will be accepted based on peer-reviews, priority, and editorial decision. Invited reviews, mini-reviews and viewpoints on relevant pathophysiological and clinical topics, as well as Editorials on articles appearing in the Journal, are published. Unsolicited Editorials will be evaluated by the editorial team. Outcomes of scientific meetings, as well as guidelines and position statements, may be submitted. The Journal also considers special feature articles in the field of endocrine genetics and epigenetics, as well as articles devoted to novel methods and techniques in endocrinology.
Endocrine covers controversial, clinical endocrine issues. Meta-analyses on endocrine and metabolic topics are also accepted. Descriptions of single clinical cases and/or small patients studies are not published unless of exceptional interest. However, reports of novel imaging studies and endocrine side effects in single patients may be considered. Research letters and letters to the editor related or unrelated to recently published articles can be submitted.
Endocrine covers leading topics in endocrinology such as neuroendocrinology, pituitary and hypothalamic peptides, thyroid physiological and clinical aspects, bone and mineral metabolism and osteoporosis, obesity, lipid and energy metabolism and food intake control, insulin, Type 1 and Type 2 diabetes, hormones of male and female reproduction, adrenal diseases pediatric and geriatric endocrinology, endocrine hypertension and endocrine oncology.