956 resultados para Aperture height index


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Physical inactivity poses a huge burden on Canada's health care system and is detrimental to the health of Canadians (Katzmarzyk & Janssen, 2004). Walking is a viable option for individuals to become physically active on a daily basis and is in fact the most commonly reported leisure time physical activity. It has been associated with many health benefits including weight loss/weight control, reduced risk of coronary artery disease and diabetes, lowered blood pressure, and improved psychological wellbeing (Brisson & Tudor-Locke, 2004). Specifically, individuals' stage of change, selfefficacy and health related quality of life (HRQL) are three psychological constructs that can be greatly improved with increased physical activity (Dishman, 1991; Penedo & Dahn, 2005; Poag & McAuley, 1992). Public health physical activity recommendations exist but many individuals find these difficult to meet due to overly busy lifestyles (Public Health Agency of Canada, 2003). Pedometers are inexpensive devices that can monitor individual bouts of walking so that the incorporation of physical activity into one's daily life is more plausible. They are also excellent tools for motivation, goalsetting, and immediate feedback (Brisson & Tudor-Locke, 2004). Since many people spend a large proportion of their time at their places of employment, workplaces have begun to be a common site for the development of physical activity interventions. These programs have been growing in popUlarity and have shown numerous benefits for both employees and employers (Voit, 2001). The purpose of the current study was to implement and evaluate the use of a pedometer-based physical activity intervention incorporating goal-setting and physical activity logs in a workplace setting, and to examine the relationship between different types of self-efficacy (task, barrier, and scheduling) and different phases of the intervention. Twenty male participants from a local steel manufacturing plant who exhibited health risk factors (e.g. hypertension, diabetes, etc.) were assigned to one of two groups (group A or group B). All participants were asked to wear pedometers on their waists, record their daily steps, set goals that were outlined on a step-tracking sheet (detennined by their baseline number of steps), and keep track of their work days, wakelbed time, sedentary time, and time spent doing other physical activity. Group A began the intervention immediately following the baseline measures, whereas group B continued with their regular routine for 4 weeks before beginning. Physiological measures (height, weight, blood pressure, relative body fat, waist and hip circumference, and body mass index) were taken and a battery of questionnaires that assessed barrier, task and scheduling self-efficacy, HRQL, and stage of change administered at baseline, week 5 (end of intervention for group A), week 9 (end of intervention for group B; follow-up for group A) and week 13 (follow-up for both groups). Results showed that this workplace physical activity intervention was successful at increasing the participants' daily steps, that task self-efficacy is a significant predictor of participants' exercise adherence during the initial stages of participation (intervention phase), and that the participants felt that this intervention was effective. Finally, further exploratory analyses showed that this intervention was effective for all participants, but most valuable for participants most in need of improvement - that is, those who were most sedentary prior to the intervention. This intervention is an inexpensive use of simple and effective tools (e.g. pedometers), has the potential to attract a wide variety of participants and become a pennanent part of any health promotion initiative.

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The purpose of this study was to determine if Ontario's health and physical education curriculum contributes sufficiently to ensure the health of our children and young adults. To determine the curriculum effect, the health risk profile of Niagara Region's grade 9 students was compared to Canada's adolescent population. All subjects completed a "Heart Health Lifestyle" survey and were measured for height, weight, percent body fat, blood pressure, and total cholesterol and performed the 20-metre shuttle run test as part of their physical and health education classes. The Niagara Region grade 9 population had a healthy risk profile. Aerobic power was inversely related, and cholesterol levels were positively associated to body mass index and percent body fat in the whole group analysis. These results indicate that physical education can offer unique and essential aspects allowing individuals a means to learn and control body movements and keep physically fit while providing protection against modern disease. Ontario's health and physical education curriculum does contribute to the health of our children and adolescents; however, there is a need to implement a stronger mandate for daily vigorous physical activity.

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Baerg, S., Cairney, J., Hay, J., Rempel, L. and Faught, B.E. (2009). Physical Activity of Children with Developmental Coordination Disorder in the Presence of Attention Deficit Hyperactivity Disorder: Does Gender Matter? Brock University, St. Catharines, Ontario, CANADA. Children with Developmental Coordination Disorder (DCD) have difficulties in motor coordination. Attention-deficit hyperactive disorder (ADHD) is considered the condition most co-morbid with DCD at approximately 50%. Children with DCD are generally less physically active (PA) than their peers, while children with ADHD are often considered more physically active. It is not known if the physical activity patterns of children with DCD-ADHD resemble those of children with primarily DCD or that of their healthy peers. The primary objective of this research was to contrast physical activity patterns between children with DCD, DCD-ADHD, and healthy controls. Since boys are generally reported as more physically active than girls, a secondary objective was to determine if gender moderated the association between groups and physical activity. A sample of males (n=66) and females (n=44) were recruited from the Physical Health Activity Study Team (PHAST) longitudinal study. The Movement Assessment Battery for Children (2nd Ed.) was used to identify probable cases of DCD, and Connor's Revised Parent Rating Scale- Short Version to identify ADHD. Subjects (mean age=12.8±.4 yrs) were allocated to three groups; DCD (n=32), DCD-ADHD (n=30) and control (n=48). Physical activity was monitored for seven days with the Actical® accelerometer (activity count, step count and energy expenditure). Children completed the Participation Questionnaire (PQ) during the in-school session of data collection for the PHAST study. Height, weight and body mass index (BMI) were also determined. Analysis of variance showed significant group differences for activity count (F(2,56)=5.36, p=.007) and PQ (F(2,44 )=6. 71, p=.003) in males, while a significant group difference for step count (F(2,37)=3.55, p=.04) was found in females. Post hoc comparison tests (Tukey) identified significantly lower PQ and activity count between males with OCD and controls (p=.004) and males with DCD-ADHD and controls (p=.003). Conversely, females with DCD-ADHD had significantly more step counts than their controls (p=.01). Analysis of covariance demonstrated a gender by DCD groups negative interaction for males (activity count) (F(2,92):;:3.11, p=.049) and a positive interaction for females (step count) (F(1,92)=4.92, p=.009). Hyperactivity in females with DCD-ADHD appears to contribute to more physical activity, whereas DCD may contribute to decreased activity in males with DCD and DCDADHD. Further research is needed to examine gender differences in physical activity within the context of DCD and ADHD.

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Background: Increasing Overweight and Obesity (OwOb) prevalence in pediatric populations is becoming a public health concern in many countries. The purpose of this study was to determine if childhood stature components, particularly the Leg Length Index (LLI = [height - sitting height]! height), were useful in assessing risk of OwOb in adolescence. Methods: Data was from a longitudinal study conducted in south Ontario since 2004. Approximately 2360 students had body composition measurements including sitting height and standing height at baseline. Among them, 1167 children (573 girls, 594 boys) who had weight and height measured at the 5 th year follow-up, were included in this analysis. OwOb was defined using age and sex specific BMI (kg!m 2 ) cut-off points corresponding to adults' BMI ~ 25. Results: Overall, 34% (n=298) of adolescents were considered as OwOb. The results from logistic regression analysis indicated that with 1 unit increase in LLI the odds of OwOb decreased 24% (Odds Ratio, [95% Confidence Interval], 0.76, [0.66-0.87]) after adjusted for age, sex and baseline waist circumference. Further adjusting for birth weight, birth order, breastfeeding, child's physical activity, maternal smoking, education, mother's age at birth and mother's BMI, did not change the relationship. Our results also indicated that mother's smoking status is associated with LLI. Discussion: Although LLI measured at childhood in this study is related to OwOb risk in adolescents, the underlying mechanism is unclear and further study is needed.

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The aim of this study was to describe the nonlinear association between body mass index (BMI) and breast cancer outcomes and to determine whether BMI improves prediction of outcomes. A cohort of906 breast cancer patients diagnosed at Henry Ford Health System, Detroit (1985-1990) were studied. The median follow-up was 10 years. Multivariate logistic regression was used to model breast cancer recurrence/progression and breast cancer-specific death. Restricted cubic splines were used to model nonlinear effects. Receiver operator characteristic areas under the curves (ROC AUC) were used to evaluate prediction. BMI was nonlinearly associated with recurrence/progression and death (p= 0.0230 and 0.0101). Probability of outcomes increased with increase or decrease ofBMI away from 25. BMI splines were suggestive of improved prediction of death. The ROC AUCs for nested models with and without BMI were 0.8424 and 0.8331 (p= 0.08). I f causally associated, modifying patients BMI towards 25 may improve outcomes.