Defining Metabolically Healthy Obesity: Role of Dietary and Lifestyle Factors

Abstract

BackgroundThere is a current lack of consensus on defining metabolically healthy obesity (MHO). Limited data on dietary and lifestyle factors and MHO exist. The aim of this study is to compare the prevalence, dietary factors and lifestyle behaviours of metabolically healthy and unhealthy obese and non-obese subjects according to different metabolic health criteria.MethodCross-sectional sample of 1,008 men and 1,039 women aged 45-74 years participated in the study. Participants were classified as obese (BMI ≥30kg/m2) and non-obese (BMI <30kg/m2). Metabolic health status was defined using five existing MH definitions based on a range of cardiometabolic abnormalities. Dietary composition and quality, food pyramid servings, physical activity, alcohol and smoking behaviours were examined.ResultsThe prevalence of MHO varied considerably between definitions (2.2% to 11.9%), was higher among females and generally increased with age. Agreement between MHO classifications was poor. Among the obese, prevalence of MH was 6.8% to 36.6%. Among the non-obese, prevalence of metabolically unhealthy subjects was 21.8% to 87%. Calorie intake, dietary macronutrient composition, physical activity, alcohol and smoking behaviours were similar between the metabolically healthy and unhealthy regardless of BMI. Greater compliance with food pyramid recommendations and higher dietary quality were positively associated with metabolic health in obese (OR 1.45-1.53 unadjusted model) and non-obese subjects (OR 1.37-1.39 unadjusted model), respectively. Physical activity was associated with MHO defined by insulin resistance (OR 1.87, 95% CI 1.19-2.92, p = 0.006).ConclusionA standard MHO definition is required. Moderate and high levels of physical activity and compliance with food pyramid recommendations increase the likelihood of MHO. Stratification of obese individuals based on their metabolic health phenotype may be important in ascertaining the appropriate therapeutic or intervention strategy.

Obesity phenotypes: normal-weight individuals with metabolic disorders versus metabolically healthy obese

“…Therefore, there has been increasing interest in the role of adipose tissue in lipid and glucose metabolism. Due to the fact that these tissues secrete a large number of bioactive proteins and pro-inflammatory cytokines, adipocyte metabolism appears to be a major cause of the development of metabolic disorders [7,9,14,18]. Thus, it is crucial to evaluate the regional distribution of fat and ectopic fat depots.…”

“…However, MHO individuals display other obesity-related complications: chronic pain, sleep problems, pulmonary disease, articulation and postural problems, etc. [1,6,7,36]. Moreover, Samocha-Bonet et al suggest that 30% of MHO people may be transitioned to the metabolically unhealthy obese group, while others propose as many as 50% [8].…”

“…Furthermore, treatment of obesity and obesity-related complications generates high costs. Thus, the aim of medicine nowadays is to identify those who are at risk of developing obesity and metabolic disorders, and to try to prevent secondary clinical complications [6][7][8].…”

Measured versus self-reported body height and body mass in patients after an acute coronary syndrome

“…The assessment of body weight requires, apart from values for body weight, the data for hip, extremities and waist circumference, and skinfold measures (van Wier et al, 2006). The easiest and most objective and frequently used method of assessing the degree of obesity is calculating the BMI (Body Mass Index) (Phillips et al 2013). Inappropriate and too high BMI is considered a significant, modifiable cardiovascular risk factor (Ezzati et al 2002, Whitlock et al 2009).…”

“…Imprecise, too high or too low, indication of somatic features can arrest the therapeutic and rehabilitation progress. The available data show that the most effective assessment of BMI is based on a direct measurement of the subject's body weight and height, and subsequent calculation of the BMI value (Phillips et al 2013, Targonski et al 2007.…”