Prevalence and characteristics of metabolic phenotypes: The Rhineland study, Germany

Abstract

Background Body mass index (BMI) is a commonly used yet crude indicator of obesity as it does not provide any information about body composition or metabolic characteristics. The definition of obesity needs to be improved and is still a matter of on-going debate. Other single body measures and/or metabolic characteristics perform better at capturing adiposity-related health risk. Percentage of body fat (PBF) is an indicator of risk for several comorbidities related to obesity. Nevertheless, obese individuals differ not only in the amount of excess fat mass but also in regional fat distribution. Thus, waist circumference (WC) and waist to hip ratio (WHR) have been used as a proxy measures for body fat distribution and identifying individuals at-risk. More recently, metabolically healthy (MH) and metabolically unhealthy (MU) phenotypes based on several metabolic profiles have been suggested as a clinically more relevant classification for obesity. Objective To estimate (a) the prevalence of metabolic healthy and unhealthy phenotypes and (b) the prevalence of individuals at-risk defined by PBF, WC and WHR in German adults aged 30–93 years and (c) the proportion of overlap between these two risk assessments. Method We used cross-sectional data on anthropometric measures, body composition and clinical characteristics from the Rhineland Study, Germany. Metabolically healthy and unhealthy phenotypes were defined by a pre-established classification combining the following clinical criteria: blood pressure ≥ 130/85 mmHg, triglycerides ≥ 150 mg/dL, HDL cholesterol 0.1 mg/L, glycated haemoglobin (HbA1c) ≥ 6.5%. Study participants having two or more of these cardio metabolic abnormalities were considered as MU. We identified 6 metabolic phenotypes: normal weight (BMI Results Based on data from the first 990 participants (440 M and 550 W), overall prevalence of MU phenotype was 13.3%, with higher prevalence in men (7.8%) than in women (5.5%). The mean (± SD) age for the MH group was 55.8 ± 14.0 y and for the MU group 62.5 ± 12.2 y. According to BMI groups, the prevalence of MU for normal weight, overweight and obese participants were 4.3%, 16.9% and 33.5%, respectively. The prevalence of individuals at-risk identified by PBF was 46.8% of which 6.3% were classified as MU; for WC the prevalence was 52.4% of which 11.6% were categorized as MU. The prevalence of individuals at-risk based on WHR was 50.2%; 12.2% of those were categorized as MU. Conclusion Adiposity indicators, specifically WC and WHR that classify abdominal fat, identified the higher prevalence of individuals at metabolic risk than the classification of MU phenotypes. Adiposity indicators, specifically WC and WHR that classify abdominal fat, identified the higher prevalence of individuals at metabolic risk than the classification of MU phenotypes. These classification schemes slightly overlap and seem to identify partly different people. Therefore, a stratification of metabolic phenotypes including metabolic profile and indicators of abdominal obesity could improve the identification of individuals at metabolic risk.