1. Optimal Threshold of Homeostasis Model Assessment of Insulin Resistance to Identify Metabolic Syndrome in a Chinese Population Aged 45 Years or Younger
- Author
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Szu-Yu Lin, Wen-Cheng Li, Ting-An Yang, Yi-Chuan Chen, Wei Yu, Hsiung-Ying Huang, Xue-Jie Xiong, and Jau-Yuan Chen
- Subjects
Adult ,Blood Glucose ,Male ,Metabolic Syndrome ,China ,Endocrinology, Diabetes and Metabolism ,Cardiometabolic Risk Factors ,Fasting ,RC648-665 ,HOMA-IR ,Diseases of the endocrine glands. Clinical endocrinology ,cardiovascular diseases ,metabolic syndromes ,Cross-Sectional Studies ,Endocrinology ,Asian People ,insulin resistance ,diabetes mellitus ,Humans ,Insulin ,Female ,Original Research - Abstract
BackgroundMetabolic syndrome (MetS) is regarded as a major risk factor for diabetes mellitus and cardiovascular disease (CVD). The optimal threshold of the homeostasis model assessment of insulin resistance (HOMA-IR) has been established for predicting MetS in diverse populations and for different ages. This study assessed the serum HOMA-IR level in a healthy Chinese population aged ≤45 years to determine its relationship with metabolic abnormalities.MethodsCross-sectional study data were collected from health checkup records of Chinese adults aged ≥18 years between 2013 and 2016 at Xiamen Chang Gung Hospital. Participants completed a standardized questionnaire, which was followed by a health examination and blood sample collection. Exclusion criteria were as follows: history of known CVDs; liver, kidney, or endocrine diseases or recent acute illness; hypertension; hyperlipidemia; and pregnancy or lactation.ResultsThe clinical and laboratory characteristics of 5954 men and 4185 women were analyzed. Significant differences were observed in all assessed variables (all P < 0.05). The optimal cutoff point of HOMA-IR for predicting MetS was 1.7 in men and 1.78 in women.ConclusionsWe aimed to determine the optimal cutoff point of HOMA-IR for predicting MetS in a healthy Chinese population aged ≤45 years. The findings of this study would provide an evidence-based threshold for evaluating metabolic syndromes and further implementing primary prevention programs, such as lifestyle changes in the target population.
- Published
- 2022