Predictors of Metabolically Healthy Obesity in Children

Abstract

OBJECTIVETo determine the prevalence of metabolically healthy obesity (MHO) in children and examine the demographic, adiposity, and lifestyle predictors of MHO status. RESEARCH DESIGN AND METHODSThis cross-sectional study included 8-17 year olds with a BMI ‡85th percentile who were enrolled in a multidisciplinary pediatric weight management clinic from 2005-2010. Demographic, anthropometric, lifestyle, and cardiometabolic data were retrieved by retrospective medical record review. Participants were dichotomized as either MHO or metabolically unhealthy obese (MUO) according to two separate classification systems based on: 1) insulin resistance (IR) and 2) cardiometabolic risk (CR) factors (blood pressure, serum lipids, and glucose). Multivariable logistic regression was used to determine predictors of MHO using odds ratios (ORs) with 95% CIs. RESULTSThe prevalence of MHO-IR was 31.5% (n = 57 of 181) and MHO-CR was 21.5% (n = 39 of 181). Waist circumference (OR 0.33 [95% CI 0.18-0.59]; P = 0.0002) and dietary fat intake (OR 0.56 [95% CI 0.31-0.95]; P = 0.04) were independent predictors of MHO-IR; moderate-to-vigorous physical activity (OR 1.80 [95% CI 1.24-2.62]; P = 0.002) was the strongest independent predictor of MHO-CR. CONCLUSIONSUp to one in three children with obesity can be classified as MHO. Depending on the definition, adiposity and lifestyle behaviors both play important roles in predicting MHO status. These findings can inform for whom health services for managing pediatric obesity should be prioritized, especially in circumstances when boys and girls present with CR factors.In Canada, numerous multidisciplinary clinics offer weight management care for children with obesity (1), most of which are affiliated with children's hospitals. The supply of these services is exceeded by the potential demand since there are .2 million young Canadians (2,3) who are either overweight or obese and eligible to receive health services in these clinics. Because of the demand for weight management care, in circumstances when services are limited or difficult to access, there is a need to prioritize service delivery in these specialized centers for those individuals who are at greatest cardiometabolic health risk. By distinguishing individuals with obesity based on their relative health risks, those at lower health risk can be guided to less intensive services (e.g., self-management resources or outpatient dietitian counseling), whereas their peers at higher health risk can be directed to more intensive services (e.g., multidisciplinary obesity management or bariatric surgery). The heterogeneous

Metabolic syndrome in young children: definitions and results of the IDEFICS study

“…As expected, by far most of the children in the obese category are classified as being affected. But even in the normal weight/thin category, a small fraction of 46 We should also keep in mind that the body mass index, which is used to define the weight categories, reflects both fat and fat-free mass, as discussed in Nagy et al 16 (this issue). This gradient seems to continue even within the obese category as observed by Sen et al 47 who report a twofold increase of MetS Table 3.…”

Functional Significance and Predictive Value of MicroRNAs in Pediatric Obesity: Tiny Molecules with Huge Impact?

“…While some children show the phenotype of metabolically healthy obesity (MHO), others are affected by insulin resistance and low-grade inflammation [1,2]. Depending on definitions and the classification system used, around 20-30% of the obese children aged between 8 and 17 years can be classified as MHO [1,3,4]. To date, it is still not clear why some children develop associated pathologies while others do not.…”

“…From this, one might conclude that insulin sensitivity might be programmed and contribute to a phenotype of MHO. Furthermore, waist circumference, dietary fat intake, and moderate-to-vigorous physical activity can serve as predictors for MHO [3]. In any case, different subtypes of obesity might develop through different pathophysiological processes.…”

Associations between Diet Behaviors and Measures of Glycemia, in Clinical Setting, in Obese Adolescents

“…Studies have found independent associations between high fat and sugar intake and measures of glycemia and insulin dynamics in children. Prince et al 8 found that high total fat intake was associated with insulin resistance in overweight 8-to 17-year-olds. Davis et al 25 found that higher total sugar intake was associated with lower acute insulin secretion and lower b-cell function in 63 overweight Latino children.…”

“…Additionally, in the literature for both adults and youth, most studies evaluate the role of single nutrients rather than whole foods. 6,8 Whole foods capture the complexity of dietary intake and are realistic intervention targets.…”