Page 127 - Go4it

obese adolescents signed in at the obesity outpatient ward than expected. Because of the slow enrolment it sometimes took several weeks to start a new Go4it group. This waiting time was sometimes a reason for adolescents and their parents to withdraw from participation.
Blinding
The dietician and research assistants could not be blinded to group assignment because they were involved in both arranging the measurements, conducting the measurements, delivering the intervention materials and performing the Go4it sessions. Performing all measurements and the Go4it sessions according to a standardized protocol minimized the potential for observer bias.
Outcome measures
The quality of measurement instruments can be judged by their reliability, validity, sensitivity to change, and their feasibility.
Anthropometry, body composition and resting energy expenditure
We measured body height, body weight and waist circumference according to a standardised protocol. Body composition was measured by DXA and BIA. These objective measurements are a major strength, since weight, BMI or BMIsds does not discriminate between lean and fat mass. At baseline, the study group had a mean weight of 92.1 kg (mean fat mass was 41%), BMI of 33.2 kg/m2, and a BMIsds of 2.93. This indicates morbid obesity and a high risk of the metabolic syndrome. To reduce the risk of the metabolic syndrome, it is not only necessary to lose weight but more important to lose fat mass. By measuring the body composition after 18 months follow up, we could show that the average weight loss of 2.09 kg consisted of 81% fat mass. On an individual level it was motivating to see that the fat-free mass increased and fat mass decreased. For measuring REE, we used indirect calorimetry. If it is available, this is the best way to measure REE in this population and on an individual level. We used the results of the REE also as a motivation tool. Many adolescents and their parents thought the cause of the overweight was their ‘slow metabolism’. By measuring the REE, we were able to demonstrate that none of the adolescents had a slow metabolism, but that their obesity was the result of an imbalance in dietary intake and physical activity. Unfortunately, the indirect calorimetry is an expensive measurement and therefore not commonly used.
Metabolic components
Obesity in childhood increases the risk for metabolic syndrome, which is a group of cardiovascular risk factors including increased waist circumference, hypertension, dyslipidemia, and impaired fasting glucose levels (11). In the Go4it study, we also measured the insulin levels. High insulin levels are a
General discussion
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