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Metabolic score and its components are associated with carotid plaque prevalence in young adults.
Fan, Jingwen; Yang, Yongli; Jia, Xiaocan; Wang, Yuping; Zhao, Chenyu; Wang, Nana; Ding, Suying; Shi, Xuezhong.
Affiliation
  • Fan J; Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China.
  • Yang Y; Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China.
  • Jia X; Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China.
  • Wang Y; Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China.
  • Zhao C; Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China.
  • Wang N; Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China.
  • Ding S; Health Management Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China. fccdingsy@zzu.edu.cn.
  • Shi X; Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China. xzshi@zzu.edu.cn.
Endocrine ; 2024 Jun 07.
Article in En | MEDLINE | ID: mdl-38849645
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.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Endocrine Year: 2024 Document type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Endocrine Year: 2024 Document type: Article