期刊
ENDOCRINE
卷 77, 期 2, 页码 231-241出版社
SPRINGER
DOI: 10.1007/s12020-022-03087-8
关键词
Occupational medicine; Working-age subjects; Cardiometabolic risk; Cardiometabolic indexes; Insulin resistance indexes
The aim of this study was to evaluate insulin resistance and cardiometabolic risk indexes in a population of overweight or obese workers. The results showed higher prevalence of insulin resistance and cardiometabolic risk among males, and varying percentages of workers identified as insulin resistant or at higher cardiometabolic risk depending on the index used. It was concluded that a combination of biomarkers and anthropometric measures can be used to calculate different indexes for personalized evaluation of insulin resistance and cardiometabolic risk.
Purpose The aim of the study was to evaluate indexes of insulin resistance and cardiometabolic risk in a large population of workers with overweight or obesity, in order to identify a possible efficient, cheap and simple strategy to apply in workers' health surveillance. Methods The evaluation of IR and cardiometabolic risk indexes (HOMA, QUICKI, Ty/HDLC, TyG, insuTAG, Castelli risk indexes 1 and 2, non-HDLC, TRL-C, AIP, and VAI) was performed in a population of 1195 working-age subjects with overweight or obesity (322 males, mean age 49 +/- 11 years). Results The prevalence of IR and cardiometabolic risk was higher among males for all indexes. Aging, waist circumference, BMI, blood pressure, glucose, CRP, fibrinogen and uric acid were correlated more frequently with IR/cardiometabolic indexes in women, homocysteine in men. The percentage of the workers identified as insulin resistant (IR+) or at higher cardiometabolic risk greatly vary according to the different index used. Conclusion With a small group of biomarkers and anthropometric measures (fasting glucose and insulin, lipid profile, BMI and waist circumference) is possible to calculate a number of IR/cardiometabolic indexes, which, likely reflecting different pathophysiological aspects also related to gender, might help in a personalized evaluation of IR and cardiometabolic risk. [GRAPHICS] .
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