Capacity of Objective Measures of Physical Activity to Predict Brazilian Children's Low Motor Proficiency.

This study analyzed the associations between physical activity (PA) and motor proficiency (MP) to determine what level of moderate PA might help avoid low MP in 8-10-year-old Brazilian children. We assessed MP of 98 children using the Bruininks-Oseretsky Motor Proficiency, Second Edition Short Form (BOT-2 SF), and we assessed PA using the GT3X + accelerometer. We analyzed data using means, standard deviations, frequency distribution, spearman correlation coefficients, Mann-Whitney U test, and the Receiver Operating Characteristics curve.

Proposal of cutoff points for pediatric daytime sleepiness scale to identify excessive daytime sleepiness.

The objective of the present study was to propose cutoff points for the Pediatric Daytime Sleepiness Scale (PDSS) through sensitivity and specificity analyses in order to identify excessive daytime sleepiness, considering parameters such as duration and quality of sleep, health perception, stress control and depressive moods (feelings of sadness) in adolescents. A total of 1,132 adolescents, aged 14-19 years old, of both sexes, from the public high school of São José - SC, answered the questionnaire with information on age, daytime sleepiness, sleep duration, health perception, stress management, depressive moods (feelings of sadness) and quality of sleep. The Receiver Operating Characteristic (ROC) curve was used to estimate cutoff points considering the sensitivity and specificity values ​​that best identify adolescents with excessive daytime sleepiness, using independent variables as a reference.

Factors associated with sleep duration in Brazilian high school students.

The aim of this study was to investigate the factors associated with short sleep duration on southern Brazilian high school students. Our study was comprised of 1,132 adolescents aged 14 to 19 years, enrolled in public high schools in São José, Brazil. The students answered a questionnaire about working (work and workload), health perception, smoking, school schedule, sleep (duration and daytime sleepiness), and socio-demographics data.