957 resultados para Chip Stewart


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Objective To examine the relationship between pubertal timing and physical activity. Study design A longitudinal sample of 143 adolescent girls was assessed at ages 11 and 13 years. Girls' pubertal development was assessed at age 11 with blood estradiol levels, Tanner breast staging criteria, and parental report of pubertal development. Girls were classified as early maturers (n = 41) or later maturers (n = 102) on the basis of their scores on the 3 pubertal development measures. Dependent variables measured at age 13 were average minutes/day of moderate to vigorous and vigorous physical activity as measured by the ActiGraph accelerometer. Results Early-maturing girls had significantly lower self-reported physical activity and accumulated fewer minutes of moderate to vigorous and vigorous physical activity and accelerometer counts per day at age 13 than later maturing girls. These effects v.-ere independent of differences in percentage body fat and self-reported physical activity at age 11. Conclusion Girls experiencing early pubertal maturation at age 11 reported lower subsequent physical activity at age 13 than their later maturing peers. Pubertal maturation, in particular early maturation relative to peers, may lead to declines in physical activity among adolescent girls.

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The purposes of this study were to describe and compare the specific physical activity choices and sedentary pursuits of African American and Caucasian American girls. Participants were 1,124 African American and 1,068 Caucasian American eighth grade students from 31 middle schools. The 3-Day Physical Activity Recall (3DPAR) was used to measure participation in physical activities and sedentary pursuits. The most frequently reported physical activities were walking, basketball, jogging or running, bicycling, and social dancing. Differences between groups were found in 11 physical activities and 3 sedentary pursuits. Participation rates were higher in African American girls (p<.001)for social dancing, basketball, watching television, and church attendance but lower in calisthenics, ballet and other dance, jogging or running, rollerblading, soccer, softball or baseball, using an exercise machine, swimming, and homework. Cultural differences of groups should be considered when planning interventions to promote physical activity.

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The purpose of this study was to examine the effect of prolonged exercise oil plasma lipid and lipoprotein concentrations and to identify caloric time-points where changes occurred. Eleven active male Subjects ran oil a treadmill at 70%,, of maximal fitness (VO2max) and expended 6 278.7 kilojoules (Kj) energy (1500 kcal). Blood samples were obtained at the 4185.8 Kj (1000 kcal) time-point during exercise and at each additional 418.6 Kj (100 kcal) expenditure until 6278.7 Kj was expended. After correcting for plasma volume changes, decreases in low-density lipoprotein cholesterol (LDL-C) were observed during exercise at time-points corresponding to 4604.4 and 5441.5 Kj (1100 and 1300 kcal) of energy expenditure, and immediately after exercise. Total cholesterol concentrations decreased significantly at exercise kilojoule expenditures of 4604.4, 5441.5 and 5860.1 (1100, 1300 and 1400 kcal). There were also exercise induced increases in high-density lipoprotein cholesterol (HDL-C) and HDL2-C concentrations immediately after exercise. Although acute lipid and lipoprotein changes are typically reported in the days following exercise, the Current data indicate that some lipoprotein concentrations change during acute exercise. Our data suggest that a threshold of exercise may be necessary to change lipoproteins during exercise. Future work Should identify potential mechanisms (lipoprotein lipase, cholesterol ester transport protein, LDL uptake) that alter lipoprotein concentrations during prolonged exercise.

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Previous research has shown that early maturing girls at age I I have lower subsequent physical activity at age 13 in comparison to later maturing girls. Possible reasons for this association have not been assessed. This study examines girls' psychological response to puberty and their enjoyment of physical activity as intermediary factors linking pubertal maturation and physical activity. Participants included 178 girls who were assessed at age 11, of whom 168 were reassessed at age 13. All participants were non-Hispanic white and resided in the US. Three measures of pubertal development were obtained at age I I including Tanner breast stage, estradiol levels, and mothers' reports of girls' development on the Pubertal Development Scale (PDS). Measures of psychological well-being at ages I I and 13 included depression, global self-worth, perceived athletic competence, maturation fears, and body esteem. At age 13, girls' enjoyment of physical activity was assessed using the Physical Activity Enjoyment Scale and their daily minutes of moderate-to-vigorous physical activity (MVPA) were assessed using objective monitoring. Structural Equation Modeling was used to assess direct and indirect pathways between pubertal development at age I I and MVPA at age 13. In addition to a direct effect of pubertal development on MVPA, indirect effects were found for depression, global self-worth and maturity fears controlling for covariates. In each instance, more advanced pubertal development at age I I was associated with lower psychological wellbeing at age 13, which predicted lower enjoyment of physical activity at age 13 and in turn lower MVPA. Results from this study suggest that programs designed to increase physical activity among adolescent girls should address the self-consciousness and discontent that girls' experience with their bodies during puberty, particularly if they mature earlier than their peers, and identify activities or settings that make differences in body shape less conspicuous.

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Objective To compare the level of agreement in results obtained from four physical activity (PA) measurement instruments that are in use in Australia and around the world. Methods 1,280 randomly selected participants answered two sets of PA questions by telephone. 428 answered the Active Australia (AA) and National Health Surveys, 427 answered the AA and CDC Behavioural Risk Factor Surveillance System surveys (BRFSS), and 425 answered the AA survey and the short International Physical Activity Questionnaire (IPAQ). Results Among the three pairs of survey items, the difference in mean total PA time was lowest when the AA and NHS items were asked (difference=24) (SE:17) minutes, compared with 144 (SE:21) mins for AA/BRFSS and 406 (SE:27) mins for AA/IPAQ). Correspondingly, prevalence estimates for 'sufficiently active' were similar for AA and NHS (56% and 55% respectively), but about 10% higher when BRFSS data were used, and about 26% higher when the IPAQ items were used, compared with estimates from the AA survey. Conclusions The findings clearly demonstrate that there are large differences in reported PA times and hence in prevalence estimates of 'sufficient activity' from these four measures. Implications It is important to consistently use the same survey for population monitoring purposes. As the AA survey has now been used three times in national surveys, its continued use for population surveys is recommended so that trend data ever a longer period of time can be established.

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10,000 Steps Rockhampton is a multi-strategy health promotion program which aims to develop sustainable community-based strategies to increase physical activity.The central coordinating focus of the project is the use of pedometers to raise awareness of and provide motivation for physical activity, around the theme of '10,000 steps/day - Every step counts.' To date, five key strategies have been implemented: (1) a media-based awareness raising campaign; (2) promotion of physical activity by health professionals; (3) improving social support for physical activity through group-based programs; (4) working with local council to improve environmental support for physical activity, and; (5) establishment of a ‘micro-grants’ fund to which community groups could apply for assistance with small, innovative physical activity enhancing projects. Strategies were introduced on a rolling basis beginning in February 2002 with 'layering' of interventions designed to address the multi-level individual social and environmental determinants of physical activity. The project was quasi-experimental in design, involving collection of baseline and two year follow-up data from community based surveys in Rockhampton and in a matched regional Queensland town. In August 2001,the baseline CATI survey (N=1281)found that 47.9% of men and 33.0% of women were meeting the national guidelines for physical activity. In August 2002, a smaller survey (N=400) found an increase in activity levels among women (39.7% active) but not in men (48.5%). Data from the two year follow up survey, to be conducted in August 2003, will be presented, with discussion of the major successes and challenges of this landmark physical activity intervention. Acknowledgement: This project is supported by a grant from Health Promotion Queensland

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PURPOSE To examine correlates and consequences of parents' encouragement of girls' physical activity (PA) for weight loss (ENCLOSS). METHODS Data were collected for 181 girls, mothers and fathers when girls were 9, 11, and 13 years old. Mothers and fathers completed a self-report questionnaire of ENCLOSS (e.g., “I have talked to my daughter about how to exercise to lose weight”). Correlates of ENCLOSS that were assessed include girls' Body Mass Index (BMI) z-score and parents' modeling of and logistic support for PA. Dependent variables assessed at age 13 include girls' self-reported and objectively-measured PA, enjoyment of physical activity, and weight concerns. Associations between ENCLOSS, girls' BMI, and parent's support for PA were assessed using spearman rank correlations. To examine links between ENCLOSS and the outcome variables, scores for ENCLOSS were divided into tertiles at each age. Three groups were created including girls who were in the highest tertile at each age (high ENCLOSS), girls who were in the lowest tertile at each age (low ENCLOSS), and girls who varied in their tertile ranking (mid ENCLOSS). Group differences in the outcome variables were assessed using regression analysis (referent group: low ENCLOSS), controlling for girls' BMI and the outcome variable at age 9. RESULTS Girls' with higher BMI had mothers and fathers who reported higher ENCLOSS (r = .61-. 69, p<. 0001). Parents'reports of ENCLOSS were not associated with modeling of or logistic support for PA. Girls in the high ENCLOSS group reported significantly lower enjoyment of PA and higher weight concerns at age 13, independent of covariates. No differences in PA were noted. CONCLUSION Parents who encourage their daughters to be active for weight loss do not model PA or facilitate girls' PA. Persistent encouragement of PA for weight loss may lead to low enjoyment of PA and higher weight concerns among adolescent girls.

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PURPOSE Accurate monitoring of prevalence and trends in population levels of physical activity is fundamental to the planning of health promotion and disease-prevention strategies. Test-retest reliability (repeatability) was assessed for four self-report measures of physical activity commonly used in population surveys: the Active Australia survey (AA, N=356), the short form of the International Physical Activity Questionnaire (IPAQ-S, N=104), the physical activity items in the Behavioral Risk Factor Surveillance System (BRFSS, N=127) and the physical activity items in the Australian National Health Survey (NHS, N=122). METHODS Percent agreement and Kappa statistics were used to assess the reliability of classification of activity status (where ‘active’= 150 minutes of activity per week) and sedentariness (where ‘sedentary’ = reporting no physical activity). Intraclass correlations (ICCs) were used to assess agreement on minutes of activity reported for each item of each survey and on total minutes reported in each survey. RESULTS Percent agreement scores for both activity status and sedentariness were very good on all four instruments. Overall the percent agreement between repeated surveys was between 73% (NHS) and 87% (IPAQ) for the criterion measure of achieving 150 minutes per week, and between 77% (NHS) and 89% (IPAQ) for the criterion of being sedentary. Corresponding Kappa statistics ranged from 0.46 (NHS) to 0.61 (AA) for activity status and from 0.20 (BRFSS) to 0.52 (AA) for sedentariness. For the individual items ICCs were highest for walking (0.45 to 0.56) and vigorous activity (0.22 to 0.64) and lowest for the moderate questions (0.16 to 0.44). CONCLUSION All four measures provide acceptable levels of test-retest reliability for assessing both activity status and sedentariness, and moderate reliability for assessing total minutes of activity. Supported by the Australian Commonwealth Department of Health and Ageing.

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The 10,000 Steps Rockhampton project is a multi-strategy community-wide, physical activity intervention based on the simultaneous implementation of five strategies, each identified as 'best practice' for the promotion of physical activity. Several community partners were engaged to develop and implement the strategies during the first eighteen months of the project. These included: the local media (TV, newspaper and radio); the local Division of General Practice and other health professional groups; the Heart Foundation and ‘Just Walk It’; the local council; and several large worksites. A local physical activity task force was also formed to administer a 'micro-grants' scheme, and to guide the development of community based strategies. The presentation will focus on the critical elements involved in developing and maintaining relationships with community partners. These include identification and ‘courting’ of potential partners, strategies for keeping them engaged, and the challenges of maintaining the balance between ‘top-down’ (evidence-based) and ‘bottom-up’ (community-driven) strategies. Data on implementation and uptake of the key strategies will also be presented. These include: 1) process data on the number of health