BMI as a Survey Test for Metabolic Syndrome: An Israeli Cohort Study

Aim: To assess whether BMI can be used as a simple and reliable survey test for metabolic syndrome.

Methods: Observational, cohort study, performed between 2008-2016 among patients who visited the Rambam Periodic Examinations Institute [RPEI]. We analysed the correlation between obesity indices and presence of metabolic syndrome. Using ROC curves, we aimed to identify the ideal value of BMI for identification of patients at risk for MS. We also described the correlation between different BMI value and its’ negative predictive value for metabolic syndrome.

Results: During study years, 23,993 patients visited the RPEI, 2,996 (12.5%) of them fulfilled the criteria for metabolic syndrome. Women with metabolic syndrome had higher proportion of obesity, when compared to men (89.9% vs 52.6%, p<0.0001). among obesity indices, normal BMI had the highest negative predictive value to rule out metabolic syndrome among men and women (98% and 96% respectively), while waist circumference had the highest positive predictive value (30% in men, 35% in women). Using ROC curve, we found BMI 27 to be the ideal value for identification of metabolic syndrome for the entire cohort (AUC 0.767, 95% CI 0.758-0.775, p<0.0001), for men (AUC 0.726, CI [0.715-0.738], p< 0.0001, sensitivity 77.2%, specificity 55%) and for women (AUC 0.843, CI [0.831-0.855], p< 0.0001, sensitivity 84.7%, specificity 70.1%). BMI below 30, provide negative predictive value of 91.1% to rule out metabolic syndrome.

Conclusions: As BMI offers a very high negative predictive value to rule out metabolic syndrome, it can be the first single survey measurement of obesity.