Endocrine Abstracts

It is known that a subset of obese individuals do not exhibit features of the metabolic syndrome (Met-S); these are referred to as being metabolically healthy obese (MHO) individuals. Conversely there are other individuals who although have a normal BMI are insulin resistant and exhibit some of the features of the Met-S and are termed as being metabolically unhealthy normal weight (MUHNW) individuals. This study aims to identify the prevalence of metabolic health among a different array of body composition phenotypes in a randomly selected cohort and to identify potential predictors of metabolic health. This was an observational cross sectional study. Subjects with a BMI² were considered normal weight and subjects with BMI >25 kg/m² were considered overweight or obese. Individuals having two or less features of the Met-S (as per NCEP ATPIII criteria) were deemed as being metabolically healthy. The subjects were then classified into one of the following body composition phenotypes: Metabolically healthy normal weight (MHNW); metabolically unhealthy normal weight (MUHNW); metabolically healthy obese (MHO) and metabolically unhealthy obese (MUHO). A total of 343 individuals were recruited. 64% were female and a median age of 41 years. There were 26.5% MHNW; 0.88% MUHNW; 50%MHO; 22.5% MUHO subjects. In the obese cohort there was a higher percentage of MHO females and higher percentage of MUHO males. There were significant difference in a wide range of anthropometric and biochemical parameters in between the MHO and MUHO cohorts. In the normal weight cohort 96% were MHNW of whom 80% were female. There were only 3 female MUHNW individuals. There were no significant differences in anthropometric parameters between the two cohorts. Receiver operating characteristic analysis showed that BMI, neck and arm circumference and waist index (WI) all had very good discriminative power to predict metabolic health. In conclusion, there was a high percentage of obese subjects within the recruited population. This is in keeping with recent data showing Malta to have a high prevalence of obesity. A quarter of the studied population were metabolically unhealthy and certain bedside parameters (BMI, arm circumference and WI) can be used to predict metabolic health.