Metabolic Age, an Index Based on Basal Metabolic Rate, Can Predict Individuals That are High Risk of Developing Metabolic Syndrome.

INTRODUCTION: Every 10 years, an adult's basal metabolic rate (BMR), independent of their BMI, decreases 1-2% due to skeletal muscle loss, thus decreasing an adult's energy requirement and promoting obesity. Increased obesity augments the risk of developing Metabolic Syndrome (MetS); however, an adult's healthy lifestyle, which increases BMR, can mitigate MetS development. To compare different BMRs for certain ages, Metabolic age (Met-age) was developed. AIM: To assess the association between Met-age and MetS and to determine if Met-age is an indicator of high-risk individuals for MetS. METHODS: Four hundred thirty-five attendees at 2 clinics agreed to participate and gave signed informed consent. MetS risk was assessed by the ESF-I questionnaire. Met-age was determined using a TANITA bio-analyzer. Strengthen of association was determined by calculating Spearman's rho and predictability was evaluated by the area-under-a-receiver-operating characteristic curve (AUC). Difference-in-age (DIA) = [chronological age - Met-age]. RESULTS: There was a difference between the low-risk (n = 155) and the high-risk (n = 280) groups' Met-age (37.8±16.7 v. 62.9±17.3) and DIA (1.3±17.4 v. - 10.5±20.8, p < 0.001). There was a positive correlation between the ESF-I questionnaire and Met-age (rho = - 0.624, p < 0.001) and a negative correlation for DIA (rho = - 0.358, p < 0.001). Met-age was strongly predictive (AUC = 0.84, 95% CI 0.80-0.88), suggesting a 45.5 years cutoff (sensitivity = 83.2%, specificity = 72.3%). DIA was a good predictor (AUC = 0.68, 95% CI 0.63-0.74) with a - 11.5 years cutoff (sensitivity = 52.5%, specificity = 82.8%). CONCLUSION: Met-age highly associated with and is an indicator of high-risk individuals for MetS. This would suggest that increases in Met-age are associated with augmented MetS severity, independent of the individual's chronological age.

Metabolic age correlates better than chronological age with waist-to-height ratio, a cardiovascular risk index.

OBJECTIVES: Chronological age confers an increased risk for cardiovascular disease; however, chronological age does not reflect the subject's current health status. Therefore, we assessed whether Metabolic age (Met-age), based on free fat mass, is a predictor of cardiovascular risk (CVR). METHODS: Subjects attending either IMSS UMF-2 or CUSC-1 were asked to participate. CVR was assessed using the waist-to-height ratio (WHtR), whereas Met-age was determined using the TANITA bio-analyser (model: BC-545F Fitscan). The strengthen of association was determined by calculating Pearson's r and predictability was determined by the area-under-a-receiver-operating characteristic curve (AUC). RESULTS: 284 subjects participated in this study, of which 61.6% had increased CVR. As expected, the chronological age was significantly higher in the CVR(+) group than the CVR(-) group (47.3±14.4 v. 35.2±12.7, respectively, p<.001) as well as Met-age (59.3±15.5 v. 34.3±14.3, respectively, p<.001). There was a strong association between WHtR and Met-age (r=.720, p<.001) and a moderate association for chronological age (r=.407 p<.001); however, the correlation between WHtR and Met-age was significantly better than chronological age (Z=-5.91, p<.01). Met-age was a good predictor of CVR (AUC=.88, 95%CI: .83-.92, p<.001), whereas chronological age was a fair predictor (AUC=.72, 95%CI: .66-.78, p<.001). However, Met-age showed a higher discriminatory capacity for CVR than chronological age (z=-4.597, p<.001). CONCLUSIONS: Here, we determined that Met-age correlated with a CVR index, WHtR, and was able to predict subjects with increased CVR better than chronological age.