Metabolic characterization of overweight and obese adults.

OBJECTIVES: Traditional evaluations of metabolic health may overlook underlying dysfunction in individuals who show no signs of insulin resistance or dyslipidemia. The purpose of this study was to characterize metabolic health in overweight and obese adults using traditional and non-traditional cardiometabolic variables. A secondary purpose was to evaluate differences between overweight/obese and male/female cohorts, respectively. METHODS: Forty-nine overweight and obese adults (Mean ± SD; Age = 35.0 ± 8.9 yrs; Body mass index = 33.6 ± 5.2 kg·m-2; Percent body fat [%fat] = 36.7 ± 7.9%) were characterized. Body composition (fat mass [FM], lean mass [LM], %fat) was calculated using a 4-compartment model; visceral adipose tissue (VAT) was quantified using B-mode ultrasound. Resting metabolic rate (RMR) and respiratory exchange ratio (RER) were evaluated using indirect calorimetry. Fasted blood and saliva samples were analyzed for total cholesterol (TC), high-density lipoproteins (HDL), low-density lipoproteins (LDL), triglycerides (TRG), glucose (GLUC), insulin, leptin, estradiol, and cortisol. RESULTS: The prevalence of individuals with two or more cardiometabolic risk factors increased from 13%, using traditional risk factors (GLUC, TRG, HDL), to 80% when non-traditional metabolic factors (VAT, LM, RMR, RER, TC, LDL, HOMA-IR) were considered. Between overweight/obese, there were no significant differences in %fat (p = 0.152), VAT (p = 0.959), RER (p = 0.493), lipids/GLUC (p > 0.05), insulin (p = 0.143), leptin (p = 0.053), or cortisol (p = 0.063); obese had higher FM, LM, RMR, and estradiol (p < 0.01). Males had greater LM, RMR, and TRG (p < 0.01); females had greater %fat, and leptin (p < 0.001). There were no significant sex differences in RER, estradiol, insulin, or cortisol (p > 0.05). CONCLUSIONS: Evaluating metabolic health beyond BMI and traditional cardiometabolic risk factors can give significant insights into metabolic status. Due to high variability in metabolic health in overweight and obese adults and inherent sex differences, implementation of body composition and visceral fat measures in the clinical setting can improve early identification and approaches to disease prevention.