The PEDRO (Pocketable Electronic Devices in Radiation Oncology) project: how clinical practice is changing among young radiation oncologists.

Purpose. To evaluate the impact of mobile devices and apps on the daily clinical activity of young radiation oncologists. Methods. A web-based questionnaire was sent to 382 young (≤40 years) members of the Italian Association of Radiation Oncology (AIRO). The 14 items investigated the diffusion of mobile devices (smartphones and/or tablets), their impact on daily clinical activity, and possible differences perceived by the participants over time. Results. A total of 158 questionnaires were available for statistical evaluation (response rate 41%). Up to 75% of respondents declared they used an electronic device during their clinical activity. Conversely, 82% considered the impact of smartphones/tables on daily practice low to moderate. Daily device use increased significantly from 2009 to 2012, with high daily use rates rising from 5% to 39.9%. Fulfillment of professional needs was declared by less than 42% of respondents and compliance with app indications by 32%. Almost all physicians desired in 2012 a comprehensive website concerning a variety of apps covering radiation oncologists' needs. Conclusions. Mobile devices are widely used by young Italian radiation oncologists in their daily clinical practice, while the indications so obtained are not always followed. Nevertheless, it would be important to verify the consistency of information found within apps, in order to avoid potential errors that might be detrimental to patients.

Body fat levels in children and adolescents: effects on the prevalence of obesity

BACKGROUND AND AIMS: There is little information regarding the effect of different definitions of obesity on nutritional epidemiology. The aim was thus to assess: (a) the values of percentage of body fat (%BF) by gender and age; (b) the prevalence of obesity according to different %BF cut-offs; and (c) the sensitivity and specificity of BMI according to different %BF cut-offs used to define obesity. METHODS: Cross-sectional study on 2494 boys and 2519 girls aged 10­18 years from the Lisbon area. %BF was measured using a hand-held device. In a sub sample of 211 boys and 724 girls %BF was assessed using skin folds. RESULTS: %BF levels were higher in girls and decreased with age in both genders. Prevalence of obesity varied considerably according to the %BF cut-off used: in boys, it ranged from 4.7% (age-specific 95th percentile) to 26.5% (fixed 25% cut-off), whereas by BMI it was 5.3%. In girls, prevalence of obesity ranged from 0.4% (age-specific BMI-derived %BF values) to 25.4% (fixed 30% cut-off), whereas by BMI it was 4.7%. The specificity of BMI criteria was over 95% irrespective of the %BF cut-off used; conversely, most sensitivities were below 40%. Sensitivities over 50% were obtained for the age-specific BMI-derived %BF values in boys and the age-specific 95th %BF percentile in both genders. Using %BF derived from the skin fold measurements leads to similar results. CONCLUSIONS: Prevalence of obesity varies considerably according to the %BF cut-off used. BMI cut-offs have a low sensitivity but a high specificity. Age- and gender-specific cut-offs for %BF should be used to define pediatric obesity.

Diagnostic accuracy of body mass index, body fat and waist in defining low aerobic fitness in adolescents

Objective: to assess the diagnostic accuracy of different anthropometric markers in defining low aerobic fitness among adolescents. Methods: cross-sectional study on 2,331 boys and 2,366 girls aged 10 - 18 years. Body mass index (BMI) was measured using standardized methods; body fat (BF) was assessed by bioelectrical impedance. Low aerobic fitness was assessed by the 20-meter shuttle run using the FITNESSGRAMR criteria. Waist was measured in a subsample of 1,933 boys and 1,897 girls. Overweight, obesity and excess fat were defined according to the International Obesity Task Force (IOTF) or FITNESSGRAMR criteria. Results: 38.5% of boys and 46.5% of girls were considered as unfit according to the FITNESSGRAMR criteria. In boys, the area under the ROC curve (AUC) and 95% confidence interval were 66.7 (64.1 - 69.3), 67.1 (64.5 - 69.6) and 64.6 (61.9 - 67.2) for BMI, BF and waist, respectively (P<0.02). In girls, the values were 68.3 (65.9 - 70.8), 63.8 (61.3 - 66.3) and 65.9 (63.4 - 68.4), respectively (P<0.001). In boys, the sensitivity and specificity to diagnose low fitness were 13% and 99% for obesity (IOTF); 38% and 86% for overweight + obesity (IOTF); 28% and 94% for obesity (FITNESSGRAMR) and 42% and 81% for excess fat (FITNESSGRAMR). For girls, the values were 9% and 99% for obesity (IOTF); 33% and 82% for overweight + obesity (IOTF); 22% and 94% for obesity (FITNESSGRAMR) and 26% and 90% for excess fat (FITNESSGRAMR). Conclusions: BMI, not body fat or waist, should be used to define low aerobic fitness. The IOTF BMI cut-points to define obesity have a very low screening capacity and should not be used.