36 resultados para 020501 Classical and Physical Optics
Resumo:
We carried out a cross-section study of the sex-specific relationship between bone mineral content and physical activity at sites with different loading in pre- and early pubertal girls and boys. There was significant sensitivity of bone mineral content of the hip to physical exercise in boys, but not in girls. BACKGROUND: Since little is known whether there are sex differences in sensitivity of bone to loading, we investigated sex differences in the cross-sectional association between measures of physical activity (PA) and bone mass and size in pre- and early pubertal children of both sexes. METHODS: We measured bone mineral content/density (BMC/BMD) and fat-free mass (FFM) in 269 6- to 13-year-old children from randomly selected schools by dual-energy X-ray absorptiometry. Physical activity (PA) was measured by accelerometers and lower extremity strength by a jump-and-reach test. RESULTS: Boys (n = 128) had higher hip and total body BMC and BMD, higher FFM, higher muscle strength and were more physically active than girls (n = 141). Total hip BMC was positively associated with time spent in total and vigorous PA in boys (r = 0.20-0.33, p < 0.01), but not in girls (r = 0.02-0.04, p = ns), even after adjusting for FFM and strength. While boys and girls in the lowest tertile of vigorous PA (22 min/day) did not differ in hip BMC (15.62 vs 15.52 g), boys in the highest tertile (72 min/day) had significantly higher values than the corresponding girls (16.84 vs 15.71 g, p < 0.05). CONCLUSIONS: Sex differences in BMC during pre- and early puberty may be related to a different sensitivity of bone to physical loading, irrespective of muscle mass.
Resumo:
OBJECTIVE: This study aims to measure the associations of physical activity and one of its components, sport and exercise, with at-risk substance use in a population of young men. METHOD: Baseline (2010-2012) and follow-up (2012-2013) data of 4748 young Swiss men from the Cohort Study on Substance Use Risk Factors (C-SURF) were used. Cross-sectional and prospective associations between at-risk substance use and both sport and exercise and physical activities were measured using Chi-squared tests and logistic regression models adjusting for covariates. RESULTS: At baseline, logistic regression indicated that sport and exercise is negatively associated with at-risk use of cigarettes and cannabis. A positive association was obtained between physical activity and at-risk alcohol use. At baseline, sport and exercise was negatively associated with at-risk use of cigarettes and cannabis at follow-up. Adjusted for sport and exercise, physical activity was positively associated with at-risk use of cigarettes and cannabis. CONCLUSION: Sport and exercise is cross-sectionally and longitudinally associated with a low prevalence of at-risk use of cigarettes and cannabis. This protective effect was not observed for physical activity broadly defined. Taking a substance use prevention perspective, the promotion of sport and exercise among young adults should be encouraged.
Resumo:
OBJECTIVE: Little is known regarding health-related quality of life and its relation with physical activity level in the general population. Our primary objective was to systematically review data examining this relationship. METHODS: We systematically searched MEDLINE, EMBASE, CINAHL, and PsycINFO for health-related quality of life and physical activity related keywords in titles, abstracts, or indexing fields. RESULTS: From 1426 retrieved references, 55 citations were judged to require further evaluation. Fourteen studies were retained for data extraction and analysis; seven were cross-sectional studies, two were cohort studies, four were randomized controlled trials and one used a combined cross sectional and longitudinal design. Thirteen different methods of physical activity assessment were used. Most health-related quality of life instruments related to the Medical Outcome Study SF-36 questionnaire. Cross-sectional studies showed a consistently positive association between self-reported physical activity and health-related quality of life. The largest cross-sectional study reported an adjusted odds ratio of "having 14 or more unhealthy days" during the previous month to be 0.40 (95% Confidence Interval 0.36-0.45) for those meeting recommended levels of physical activity compared to inactive subjects. Cohort studies and randomized controlled trials tended to show a positive effect of physical activity on health-related quality of life, but similar to the cross-sectional studies, had methodological limitations. CONCLUSION: Cross-sectional data showed a consistently positive association between physical activity level and health-related quality of life. Limited evidence from randomized controlled trials and cohort studies precludes a definitive statement about the nature of this association.
Resumo:
The present study tested the effect of a school-based physical activity (PA) program on quality of life (QoL) in 540 elementary school children. First and fifth graders were randomly assigned to a PA program or a no-PA control condition during one academic year. QoL was assessed by the Child Health Questionnaire at baseline and postintervention. Based on mixed linear model analyses, physical QoL in first graders and physical and psychosocial QoL in fifth graders were not affected by the intervention. In first graders, the PA intervention had a positive impact on psychosocial QoL (effect size [d], 0.32; p < .05). Subpopulation analyses revealed that this effect was caused by an effect in urban (effect size [d], 0.38; p < .05) and overweight first graders (effect size [d], 0.45; p < .05). In conclusion, a school-based PA intervention had little effect on QoL in elementary school children.
Resumo:
AIMS/HYPOTHESIS: To assist in the development of preventive strategies, we studied whether the neighbourhood environment or modifiable behavioural parameters, including cardiorespiratory fitness (CRF) and physical activity (PA), are independently associated with obesity and metabolic risk markers in children. METHODS: We carried out a cross-sectional analysis of 502 randomly selected first and fifth grade urban and rural Swiss schoolchildren with regard to CRF, PA and the neighbourhood (rural vs urban) environment. Outcome measures included BMI, sum of four skinfold thicknesses, homeostasis model assessment of insulin resistance (HOMA-IR) and a standardised clustered metabolic risk score. RESULTS: CRF and PA (especially total PA, but also the time spent engaged in light and in moderate and vigorous intensity PA) were inversely associated with measures of obesity, HOMA-IR and the metabolic risk score, independently of each other, and of sociodemographic and nutritional parameters, media use, sleep duration, BMI and the neighbourhood environment (all p < 0.05). Children living in a rural environment were more physically active and had higher CRF values and reduced HOMA-IR and metabolic risk scores compared with children living in an urban environment (all p < 0.05). These differences in cardiovascular risk factors persisted after adjustment for CRF, total PA and BMI. CONCLUSIONS/INTERPRETATION: Reduced CRF, low PA and an urban environment are independently associated with an increase in metabolic risk markers in children.
Resumo:
BACKGROUND: Physical activity and sedentary behaviour in youth have been reported to vary by sex, age, weight status and country. However, supporting data are often self-reported and/or do not encompass a wide range of ages or geographical locations. This study aimed to describe objectively-measured physical activity and sedentary time patterns in youth. METHODS: The International Children's Accelerometry Database (ICAD) consists of ActiGraph accelerometer data from 20 studies in ten countries, processed using common data reduction procedures. Analyses were conducted on 27,637 participants (2.8-18.4 years) who provided at least three days of valid accelerometer data. Linear regression was used to examine associations between age, sex, weight status, country and physical activity outcomes. RESULTS: Boys were less sedentary and more active than girls at all ages. After 5 years of age there was an average cross-sectional decrease of 4.2 % in total physical activity with each additional year of age, due mainly to lower levels of light-intensity physical activity and greater time spent sedentary. Physical activity did not differ by weight status in the youngest children, but from age seven onwards, overweight/obese participants were less active than their normal weight counterparts. Physical activity varied between samples from different countries, with a 15-20 % difference between the highest and lowest countries at age 9-10 and a 26-28 % difference at age 12-13. CONCLUSIONS: Physical activity differed between samples from different countries, but the associations between demographic characteristics and physical activity were consistently observed. Further research is needed to explore environmental and sociocultural explanations for these differences.