MEDIGREIF-Inselklinik Heringsdorf GmbH, Department of Diabetes and Metabolic Diseases, Setheweg 11, D-17424 Ostseebad Heringsdorf, Germany.
Appetite. 2012 Apr;58(2):432-7. doi: 10.1016/j.appet.2011.11.021. Epub 2011 Dec 1.
It was the goal of the trial to study the impact of electronic healthcare technology into treatment.
One hundred and twenty-four children/adolescents (females 56%, age 13.5±2.8 years, height 1.64±0.13 m, weight 85.4±23.0 kg, body-mass index (BMI) 31.3±5.2 kg/m(2), BMI-standard deviation score (SDS) 2.50±0.5) were included. To assess physical activity and eating habits, a mobile motion sensor integrated into a mobile phone with digital camera was used.
The children/adolescents had a significant weight reduction of 7.1±3.0 kg. BMI/BMI-SDS decreased (p<0.01). Intensity (14.1±6.4 activity units) and duration of physical activity (290.4±92.6 min/day) were assessed with sensors. Time walking: median 45.5 (range, 2.5-206.5), running 8.0 (range, 0-39.5), cycling 27.7 (range, 0-72.5), car driving 23.7 (range, 0-83.0) min/day. Comparing self-reported physical activity (walking 292.9 (range, 9.6-496.1), running 84.8 (range, 8.4-130.2) min/day) with assessment with sensors there were significant differences (p<0.01). Duration of physical activity documented by children/adolescents was higher than the assessment with motion sensors (walking 292.9 vs 45.5 min, p<0.01, running 84.8 vs 8.0 min, p<0.01). Sensor derived energy intake was higher than recommended (469.14±88.75 kcal vs 489.03±108.25 kcal, p=0.09). Performing multivariate analysis the following parameters showed associations with weight reduction (R-square=0.75): body weight (β=-0.95, p<0.01), C-reactive protein (CRP, β=0.15, p=0.07), physical activity, time spent in activities measured with sensors (β=-0.18, p=0.04), stress management (β=0.16, p=0.06), body fat mass at onset of the trial (β=0.45, p<0.01) and body shape (β=-0.25, p=0.01).
The innovative mobile movement detection system is highly accepted by children and adolescents. The system is able to augment existing weight reduction and stabilization strategies.
研究电子医疗技术对治疗的影响。
共纳入 124 名儿童/青少年（女性 56%，年龄 13.5±2.8 岁，身高 1.64±0.13m，体重 85.4±23.0kg，体重指数（BMI）31.3±5.2kg/m²，BMI-标准差分数（BMI-SDS）2.50±0.5）。为评估体力活动和饮食习惯，使用集成在具有数码相机的移动电话中的移动运动传感器。
儿童/青少年体重显著减轻 7.1±3.0kg。BMI/BMI-SDS 降低（p<0.01）。传感器评估体力活动强度（14.1±6.4 活动单位）和持续时间（290.4±92.6 分钟/天）。行走时间：中位数 45.5（范围，2.5-206.5），跑步 8.0（范围，0-39.5），骑车 27.7（范围，0-72.5），开车 23.7（范围，0-83.0）分钟/天。与自我报告的体力活动（行走 292.9（范围，9.6-496.1），跑步 84.8（范围，8.4-130.2）分钟/天）相比，传感器评估存在显著差异（p<0.01）。儿童/青少年记录的体力活动持续时间高于运动传感器评估（行走 292.9 与 45.5 分钟，p<0.01，跑步 84.8 与 8.0 分钟，p<0.01）。传感器得出的能量摄入高于推荐值（469.14±88.75kcal 与 489.03±108.25kcal，p=0.09）。进行多元分析后，以下参数与体重减轻相关（R²=0.75）：体重（β=-0.95，p<0.01），C 反应蛋白（CRP，β=0.15，p=0.07），体力活动，用传感器测量的活动时间（β=-0.18，p=0.04），压力管理（β=0.16，p=0.06），试验开始时的体脂肪量（β=0.45，p<0.01）和体型（β=-0.25，p=0.01）。
创新的移动运动检测系统受到儿童和青少年的高度认可。该系统能够增强现有的减肥和稳定策略。
