Go4it; study design of a randomised controlled trial and economic evaluation of a multidisciplinary group intervention for obese adolescents for prevention of diabetes mellitus type 2

<p>Abstract</p> <p>Background</p> <p>In the Netherlands, the first adolescents with diabetes mellitus type 2 as a result of obesity have recently been diagnosed. Therefore, it is very important that programs aiming at the prevention of type 2 diabetes of obese adolescents are developed and evaluated.</p> <p>Methods</p> <p>Go4it is a multidisciplinary group treatment that focuses on: 1) increasing awareness of the current dietary and physical activity behaviour (i.e. energy balance behaviour), 2) improving diet, 3) decreasing sedentary behaviour, 4) increasing levels of physical activity, and 5) coping with difficult situations. Go4it consists of 7 sessions with an interval of 2–3 weeks.</p> <p>The effectiveness of the multidisciplinary group treatment compared with usual care (i.e. referral to a dietician) was evaluated in a randomised controlled trial. We examined effects on BMI(sds), body composition, energy expenditure, glucose tolerance and insulin resistance (primary outcome measure), as well as dietary and physical activity behaviour and quality of life. An economic evaluation from a societal perspective was conducted alongside the randomised trial to evaluate the cost-effectiveness of the multidisciplinary treatment program vs. usual care.</p> <p>Discussion</p> <p>In this paper we described a multidisciplinary treatment program (Go4it) for obese adolescents and the design of a randomised controlled trial and economic evaluation to evaluate its effectiveness and cost-effectiveness.</p> <p>Trial registration</p> <p>Netherlands Trial Register (ISRCTN27626398).</p

Self-reported screen time and cardiometabolic risk in obese dutch adolescents

BACKGROUND: It is not clear whether the association between sedentary time and cardiometabolic risk exists among obese adolescents. We examined the association between screen time (TV and computer time) and cardiometabolic risk in obese Dutch adolescents. METHODS AND FINDINGS: For the current cross-sectional study, baseline data of 125 Dutch overweight and obese adolescents (12-18 years) participating in the Go4it study were included. Self-reported screen time (Activity Questionnaire for Adolescents and Adults) and clustered and individual cardiometabolic risk (i.e. body composition, systolic and diastolic blood pressure, low-density (LDL-C), high-density (HDL-C) and total cholesterol (TC), triglycerides, glucose and insulin) were assessed in all participants. Multiple linear regression analyses were used to assess the association between screen time and cardiometabolic risk, adjusting for age, gender, pubertal stage, ethnicity and moderate-to-vigorous physical activity. We found no significant relationship between self-reported total screen time and clustered cardiometabolic risk or individual risk factors in overweight and obese adolescents. Unexpectedly, self-reported computer time, but not TV time, was slightly but significantly inversely associated with TC (B = -0.002; CI = [-0.003;-0.000]) and LDL-C (B = -0.002; CI = [-0.001;0.000]). CONCLUSIONS: In obese adolescents we could not confirm the hypothesised positive association between screen time and cardiometabolic risk. Future studies should consider computer use as a separate class of screen behaviour, thereby also discriminating between active video gaming and other computer activities

Predicting resting energy expenditure in underweight, normal weight, overweight, and obese adult hospital patients

BACKGROUND: When indirect calorimetry is not available, predictive equations are used to estimate resing energy expenditure (REE). There is no consensus about which equation to use in hospitalized patients. The objective of this study is to examine the validity of REE predictive equations for underweight, normal weight, overweight, and obese inpatients and outpatients by comparison with indirect calorimetry. METHODS: Equations were included when based on weight, height, age, and/or gender. REE was measured with indirect calorimetry. A prediction between 90 and 110% of the measured REE was considered accurate. The bias and root-mean-square error (RMSE) were used to evaluate how well the equations fitted the REE measurement. Subgroup analysis was performed for BMI. A new equation was developed based on regression analysis and tested. RESULTS: 513 general hospital patients were included, (253 F, 260 M), 237 inpatients and 276 outpatients. Fifteen predictive equations were used. The most used fixed factors (25 kcal/kg/day, 30 kcal/kg/day and 2000 kcal for female and 2500 kcal for male) were added. The percentage of accurate predicted REE was low in all equations, ranging from 8 to 49%. Overall the new equation performed equal to the best performing Korth equation and slightly better than the well-known WHO equation based on weight and height (49% vs 45% accurate). Categorized by BMI subgroups, the new equation, Korth and the WHO equation based on weight and height performed best in all categories except from the obese subgroup. The original Harris and Benedict (HB) equation was best for obese patients. CONCLUSIONS: REE predictive equations are only accurate in about half the patients. The WHO equation is advised up to BMI 30, and HB equation is advised for obese (over BMI 30). Measuring REE with indirect calorimetry is preferred, and should be used when available and feasible in order to optimize nutritional support in hospital inpatients and outpatients with different degrees of malnutrition

Validation of predictive equations for resting energy expenditure in obese adolescents

Background: When the resting energy expenditure (REE) of overweight and obese adolescents cannot be measured by indirect calorimetry, it has to be predicted with an equation. Objective: The aim of this study was to examine the validity of published equations for REE compared with indirect calorimetry in overweight and obese adolescents. Design: Predictive equations based on weight, height, sex, age, fatfree mass (FFM), and fat mass were compared with measured REE. REE was measured by indirect calorimetry, and body composition was measured by dual-energy X-ray absorptiometry. The accuracy of the REE equations was evaluated on the basis of the percentage of adolescents predicted within 10% of REE measured, the mean percentage difference between predicted and measured values (bias), and the root mean squared prediction error (RMSE). Results: Forty-three predictive equations (of which 12 were based on FFM) were included. Validation was based on 70 girls and 51 boys with a mean age of 14.5 y and a mean (6SD) body mass index SD score of 2.93 6 0.45. The percentage of adolescents with accurate predictions ranged from 74% to 12% depending on the equation used. The most accurate and precise equation for these adolescents was the Molnar equation (accurate predictions: 74%; bias: –1.2%; RMSE: 174 kcal/d). The often-used Schofield-weight equation for age 10–18 y was not accurate (accurate predictions: 50%; bias: +10.7%; RMSE: 276 kcal/d). Conclusions: Indirect calorimetry remains the method of choice for REE in overweight and obese adolescents. However, the sex-specific Molnar REE prediction equation appears to be the most accurate for overweight and obese adolescents aged 12–18 y. This trial was registered at www.trialregister.nl with the Netherlands Trial Register as ISRCTN27626398

Associations between screen time (min/day) and cardiometabolic risk factors in obese adolescents (N = 125), adjusted for age, gender, pubertal stage, ethnicity and MVPA.

*<p> = significantly associated with computer time (p<0.05 for TC; p<0.01 for LDL).</p><p>B, unstandardised regression coefficient; BMI, body mass index; BP, blood pressure; CI; confidence interval; HDL-C, high density lipoprotein cholesterol; LDL-C low density lipoprotein cholesterol; MVPA, moderate-to-vigorous physical activity; TG, triglycerides; TC, total cholesterol; TV, television; zMetRisk, z-score for clustered cardiometabolic risk.</p

Participant characteristics (Mean (SD)).

*<p> = Significantly different between boys and girls.</p>a<p>N = 51;</p>b<p>N = 70;</p>c<p>N = 69.</p><p>BMI, body mass index; BP, blood pressure; HDL-C, high density lipoprotein cholesterol; LDL-C low density lipoprotein cholesterol; SD, standard deviation; TC, total cholesterol; TG, triglycerides; TV, television; zMetRisk, z-score for clustered cardiometabolic risk.</p

Validation of predictive equations for resting energy expenditure in obese adolescents

Background: When the resting energy expenditure (REE) of overweight and obese adolescents cannot be measured by indirect calorimetry, it has to be predicted with an equation. Objective: The aim of this study was to examine the validity of published equations for REE compared with indirect calorimetry in overweight and obese adolescents. Design: Predictive equations based on weight, height, sex, age, fat-free mass (FFM), and fat mass were compared with measured REE. REE was measured by indirect calorimetry, and body composition was measured by dual-energy X-ray absorptiometry. The accuracy of the REE equations was evaluated on the basis of the percentage of adolescents predicted within 10% of REE measured, the mean percentage difference between predicted and measured values (bias), and the root mean squared prediction error (RMSE). Results: Forty-three predictive equations (of which 12 were based on FFM) were included. Validation was based on 70 girls and 51 boys with a mean age of 14.5 y and a mean (+/- SD) body mass index SD score of 2.93 +/- 0.45. The percentage of adolescents with accurate predictions ranged from 74% to 12% depending on the equation used. The most accurate and precise equation for these adolescents was the Molnar equation (accurate predictions: 74%; bias: -1.2%; RMSE: 174 kcal/d). The often-used Schofield-weight equation for age 10-18 y was not accurate (accurate predictions: 50%; bias: +10.7%; RMSE: 276 kcal/d). Conclusions: Indirect calorimetry remains the method of choice for REE in overweight and obese adolescents. However, the sex-specific Molnar REE prediction equation appears to be the most accurate for overweight and obese adolescents aged 12-18 y. This trial was registered at www.trialregister.nl with the Netherlands Trial Register as ISRCTN27626398. Am J Clin Nutr 2010; 91: 1244-54.Developmen