Emily Hill Guseman

Graded Exercise Testing in a Pediatric Weight Management Center: The DeVos Protocol.

BACKGROUND In this article, we describe a protocol used to test the functional capacity of the obese pediatric patient and describe the peak oxygen consumption (VO2peak) of patients seeking treatment at a pediatric weight management center. METHODS One hundred eleven (mean age, 12.5 ± 3.0 years) patients performed a multistage exercise test on a treadmill, of which 90 (81%) met end-test criteria and provided valid VO2peak data. Peak VO2 was expressed: (1) in absolute terms (L·min(-1)); (2) as the ratio of the volume of oxygen consumed per minute relative to total body mass (mL·kg(-1)·min(-1)); and (3) as the ratio of the volume of oxygen consumed per minute relative to fat-free mass (mL·FFM·kg(-1)·min(-1)). RESULTS Mean BMI z-score was 2.4 ± 0.3 and the mean percent body fat was 36.5 ± 9.7%. Absolute VO2peak (L·min(-1)) was significantly different between sexes; however, relative values were similar between sexes. Mean VO2peak was 25.7 ± 4.8 mL·kg(-1)·min(-1) with a range of 13.5-36.7 mL·kg(-1)·min(-1). CONCLUSIONS Obese youth seeking treatment at a stage 3 pediatric weight management center exhibit low VO2peak. The protocol outlined here should serve as a model for similar programs interested in the submaximal and peak responses to exercise in obese pediatric patients.

Association between the Family Nutrition and Physical Activity Screening Tool and obesity severity in youth referred to weight management

BACKGROUND The Family Nutrition and Physical Activity Screening Tool (FNPA) evaluates family behavioural and environmental factors associated with pediatric obesity, but it is unknown if FNPA scores differ among youth across obesity severities. Our aim was to determine the association between the FNPA and obesity severity in youth referred to weight management. METHODS Upon initiating treatment, height, weight, and the FNPA were collected according to standard procedures. Cut-points for overweight/obesity, severe obesity (SO) class 2, and SO class 3 were calculated. FNPA scores were compared across weight status groups using analysis of covariance, and odds of SO across FNPA quartiles were evaluated with multiple logistic regression. RESULTS Participants included 564 5-18year old who initiated treatment and completed the FNPA. After adjustment, FNPA scores differed by weight status with higher/healthier scores in youth with overweight/obesity (56.6±8.5) when compared to those with SO class 2 (55.0±7.1; p=0.015) or SO class 3 (53.6±9.0; p<0.001). Compared to those in the highest FNPA quartile, youth in the 2nd quartile had 1.8 (95% CI: 1.1, 2.9) times higher odds of SO, and those in the lowest FNPA quartile had 2.1 (95% CI: 1.3, 3.4) times higher odds of SO. Youth with SO had unhealthier subscale scores among 6 of 10 constructs, including nutritional, physical activity, sedentary, and sleep behaviours. CONCLUSIONS Results suggest a consistent inverse relationship between the FNPA and adiposity among youth presenting for weight management. The FNPA is a useful metric for programs and clinicians targeting family behaviours and the home environment to combat obesity.

Physical activity does not attenuate the relationship between daily cortisol and metabolic syndrome in obese youth.

Abstract Objective: We examined the associations among daily cortisol, physical activity (MVPA) and continuous metabolic syndrome score (cMetS) in obese youth. Methods: Fifty adolescents (mean age 14.8±1.9 years) were recruited from medical clinics. Daily MVPA (min/day) was assessed by accelerometry. Saliva was sampled at prescribed times: immediately upon waking; 30 min after waking; and 3, 6 and 9 h after waking. Fasting lipids, glucose, waist circumference and blood pressure were used to calculate a continuous metabolic syndrome score (cMetS). Multiple linear regression analysis was used to examine associations among variables. Results: The mean cMetS score was 4.16±4.30 and did not differ by clinic or sex. No significant relationship was found between cortisol area under the curve (cAUC) and cMetS, nor did the interaction of MVPA with cAUC significantly predict cMetS. Conclusions: Physical activity, cortisol, and metabolic risk were not associated in this sample of obese adolescents. Future research should examine the role of insulin sensitivity in these relationships.

Healthy Pokes: After-School Education and Mentoring to Enhance Child Health.

Childhood obesity and related health consequences are currently considered some of the most important health challenges in our nation today. Early intervention programs designed to teach healthy lifestyle choices and behaviors are imperative to addressing this issue. Evidence suggests that intervention programs offered at an earlier age may reduce the various problems that affect at-risk youth, such as poor academic performance, decreased physical health and issues relating to behavioral health. This article describes an after-school program developed to address the physical activity and health needs of at-risk youth in Laramie, WY. It discusses (1 the importance of a comprehensive approach to addressing child health, (2) the Healthy Pokes program components, (3) weekly club sessions, and (4) the value of community partners.

Calculating a Continuous Metabolic Syndrome Score Using Nationally Representative Reference Values

OBJECTIVE The prevalence of metabolic syndrome in youth varies on the basis of the classification system used, prompting implementation of continuous scores; however, the use of these scores is limited to the sample from which they were derived. We sought to describe the derivation of the continuous metabolic syndrome score using nationally representative reference values in a sample of obese adolescents and a national sample obtained from National Health and Nutrition Examination Survey (NHANES) 2011-2012. METHODS Clinical data were collected from 50 adolescents seeking obesity treatment at a stage 3 weight management center. A second analysis relied on data from adolescents included in NHANES 2011-2012, performed for illustrative purposes. The continuous metabolic syndrome score was calculated by regressing individual values onto nationally representative age- and sex-specific standards (NHANES III). Resultant z scores were summed to create a total score. RESULTS The final sample included 42 obese adolescents (15 male and 35 female subjects; mean age, 14.8 ± 1.9 years) and an additional 445 participants from NHANES 2011-2012. Among the clinical sample, the mean continuous metabolic syndrome score was 4.16 ± 4.30, while the NHANES sample mean was quite a bit lower, at -0.24 ± 2.8. CONCLUSIONS We provide a method to calculate the continuous metabolic syndrome by comparing individual risk factor values to age- and sex-specific percentiles from a nationally representative sample.

The Association Between Measures of Fitness and Metabolic Health in Treatment-Seeking Youth with Obesity

BACKGROUND Both cardiorespiratory fitness (CRF) and measures of muscular fitness are associated with metabolic syndrome in adults. However, limited information exists about these relationships in youth with severe obesity who are at increased risk of metabolic dysfunction. The purpose of this study was to examine the relationship between fitness and metabolic health in treatment-seeking youth with obesity. METHODS Data for this analysis were collected at the time of baseline visits at a stage 3 pediatric weight management center. Maximal voluntary contractions were obtained by using isometric hand-grip dynamometry, and CRF was obtained from a maximal treadmill test. Resting blood pressure and fasting measures of blood lipids, glucose, and insulin were used to calculate a continuous metabolic syndrome score (cMetS); homeostasis model assessment of insulin resistance (HOMA-IR) was calculated from fasting insulin and glucose. Relationships between measures of fitness and metabolic health were evaluated by using partial correlations adjusted for age. RESULTS Sixty-nine participants (21 boys, 48 girls) were included in this analysis. Of these, 46% (n = 32) met the criteria for metabolic syndrome. No differences were found between boys and girls for any variable analyzed. Muscular strength was positively associated with cMetS (r = 0.35), though this association weakened after adjustment for body mass index percentile. CRF was inversely associated with homeostasis model assessment of insulin resistance (HOMA-IR) (r = -0.26) and fasting insulin (r = -0.27). Body fat percentage was positively associated with insulin (r = 0.36). No significant relationship was found between CRF and cMetS. CONCLUSION Contrary to previous studies, CRF was not associated with metabolic syndrome in this group. Muscular strength, however, was associated with cMetS. Notably, CRF was associated with elevated HOMA-IR, which may be seen as a precursor to metabolic syndrome. These results suggest that CRF and muscular strength influence metabolic function independently.