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Updated: Jul 7, 2025

Author Spotlight: Assessing the Cardiovascular Profile of Patients with Metabolic Syndrome
Published on: September 27, 2024
The prevalence and clustering of metabolic syndrome risk components in Chinese population: a cross-sectional study
Xu Zhao1, Cihang Lu1, Bo Song1
1The Department of Endocrinology and Metabolism, Institute of Endocrinology, National Health Commission Key Laboratory of Diagnosis and Treatment of Thyroid Diseases, The First Hospital of China Medical University, Shenyang, Liaoning, China.
Objective:
The metabolic syndrome (MetS) is diagnosed upon the manifestation of ≥ 3 out of 5 specific components. The present study evaluated the epidemiological characteristics of the MetS components and their clustering condition among Chinese adults.
Methods:
68383 participants aged 18-80 years from TIDE were scored on a six-point (0-5) MetS severity score (MSSS), which quantified their cumulative amount of MetS risk components. We evaluated the epidemiological characteristics of these components and their clustering conditions. Additionally, we examined the relation of age with the prevalence of different MSSSs or specific MetS components using restricted cubic splines.
Results:
Among 68383 participants, 26113 men and 24582 women had abnormal MetS components. There were significant differences in most epidemiological characteristics between the 6 MSSS groups. The top three prevalence of abnormal metabolic components were high systolic blood pressure (SBP) (9.41%, n=6568), high waist circumference (WC) (8.13%, n=6120), and the cooccurrence of high SBP and high WC (6.33%, n=4622). Participants were more likely to have all five MetS components when HDL-C was low. Restricted cubic splines showed that when the MSSS ≥3, the MetS prevalence of male peaked and that of the female population increased most rapidly at 40-60 age group.
Conclusion:
The 40-60 age group can be regarded as the high-risk period of MetS, and elderly women have a higher risk of multiple metabolic disorders than men. The top three clustering of abnormal metabolic components were high SBP, high WC, and their combination. Multiple components aggregation was more likely to occur when HDL-C decreased.
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