244 resultados para Physical activity, Education level


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As obesity prevention becomes an increasing health priority in many countries, including Australia
and New Zealand, the challenge that governments are now facing is how to adopt a systematic
policy approach to increase healthy eating and regular physical activity. This article sets out a
structure for systematically identifying areas for obesity prevention policy action across the food
system and full range of physical activity environments. Areas amenable to policy intervention can
be systematically identified by considering policy opportunities for each level of governance (local,
state, national, international and organisational) in each sector of the food system (primary
production, food processing, distribution, marketing, retail, catering and food service) and each
sector that influences physical activity environments (infrastructure and planning, education,
employment, transport, sport and recreation). Analysis grids are used to illustrate, in a structured
fashion, the broad array of areas amenable to legal and regulatory intervention across all levels of
governance and all relevant sectors. In the Australian context, potential regulatory policy
intervention areas are widespread throughout the food system, e.g., land-use zoning (primary
production within local government), food safety (food processing within state government), food
labelling (retail within national government). Policy areas for influencing physical activity are
predominantly local and state government responsibilities including, for example, walking and
cycling environments (infrastructure and planning sector) and physical activity education in schools
(education sector). The analysis structure presented in this article provides a tool to systematically
identify policy gaps, barriers and opportunities for obesity prevention, as part of the process of
developing and implementing a comprehensive obesity prevention strategy. It also serves to
highlight the need for a coordinated approach to policy development and implementation across
all levels of government in order to ensure complementary policy action.

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Objective: The objective of this study was to identify school environmental characteristics associated with moderate to vigorous physical activity during school recess, including morning and lunch breaks.

Methods: Accelerometry data, child-level characteristics and school physical activity, policy and socio-cultural data were collected from 408 sixth grade children (mean age 11 years) attending 27 metropolitan primary schools in Perth, Western Australia. Hierarchical modelling identified key characteristics associated with children's recess moderate to vigorous physical activity (RMVPA).

Results: Nearly 40% of variability in children's RMVPA was explained by school environment and individual characteristics identified in this study. Children's higher daily RMVPA was associated with newer schools, schools with a higher number of grassed surfaces per child and fewer shaded grassed surfaces, and the physical education coordinator meeting Australian physical activity guidelines.

Conclusions:
Characteristics of the school physical and social environments are strongly correlated with children's MPVA during recess.

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BACKGROUND: School-based physical education is an important public health initiative as it has the potential to provide students with regular opportunities to participate in moderate-to-vigorous physical activity (MVPA). Unfortunately, in many physical education lessons students do not engage in sufficient MVPA to achieve health benefits. In this trial we will test the efficacy of a teacher professional development intervention, delivered partially via the Internet, on secondary school students' MVPA during physical education lessons. Teaching strategies covered in this training are designed to (i) maximize opportunities for students to be physically active during lessons and (ii) enhance students' autonomous motivation towards physical activity. METHOD: A two-arm cluster randomized controlled trial with allocation at the school level (intervention vs. usual care control). Teachers and Year 8 students in government-funded secondary schools in low socio-economic areas of the Western Sydney region of Australia will be eligible to participate. During the main portion of the intervention (6 months), teachers will participate in two workshops and complete two implementation tasks at their school. Implementation tasks will involve video-based self-reflection via the project's Web 2.0 platform and an individualized feedback meeting with a project mentor. Each intervention school will also complete two group peer-mentoring sessions at their school (one per term) in which they will discuss implementation with members of their school physical education staff. In the booster period (3 months), teachers will complete a half-day workshop at their school, plus one online implementation task, and a group mentoring session at their school. Throughout the entire intervention period (main intervention plus booster period), teachers will have access to online resources. Data collection will include baseline, post-intervention (7-8 months after baseline) and maintenance phase (14-15 months after baseline) assessments. Research assistants blinded to group allocation will collect all data. The primary outcome will be the proportion of physical education lesson time that students spend in MVPA. Secondary outcomes will include leisure-time physical activity, subjective well-being, and motivation towards physical activity.
DISCUSSION: The provision of an online training platform for teachers could help facilitate more widespread dissemination of evidence-based interventions compared with programs that rely exclusively on face-to-face training.

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Objective: This study examined associations between the family environment and children's television (TV) viewing and likelihood of being low-active.
Research Methods and Procedures: In 2001, children were recruited from 19 primary schools in Melbourne, Australia. Parents completed a questionnaire about their child's TV viewing and the family environment. Children also completed a questionnaire and wore an accelerometer for 8 days. Movement counts were used to identify low-active children (lowest quartile). Data were analyzed in May 2004.
Results: The sample consisted of 878 children (mean age = 11.5 0.6 yrs). Multiple logistic regression revealed that socioeconomic status [adjusted odds ratios (AOR) = 0.4 boys], frequency families watched TV together (AOR = 2.0 boys), mothers' (AOR = 1.8 boys; AOR = 2.5 girls) and fathers' (AOR = 2.6 boys; AOR = 2.8 girls) TV viewing, and rules prohibiting TV during mealtimes (AOR = 0.6 boys; AOR = 0.6 girls) related to children watching TV 2 h/d. Variables associated with low-level physical activity included self-reported enjoyment of Internet use (AOR = 1.7 boys) and preference for watching TV (AOR = 2.3 girls), perception that mother uses computer a lot (AOR = 1.9 boys) and likes using the computer (AOR = 0.6 girls), fathers' reported computer/electronic games use (AOR = 1.7 girls), frequency families used computer together (AOR = 0.4 girls), rules that TV viewing must be supervised (AOR = 1.9 boys; AOR = 0.6 girls), and having pay TV (AOR = 0.6 boys) and electronic games at home (AOR = 2.6 boys).
Discussion: These findings suggest that the relationships between the family environment and TV viewing and low-level activity are complex and that these behaviors are distinct.

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Objective:
To examine trends in active transport to and from school, in school sport and physical education (PE), and in weight status among children from high and low socio-economic status (SES) areas in Melbourne, Victoria, between 1985 and 2001.

Methods:
Cross-sectional survey data and measured height and weight from 1985 (n=557) and 2001 (n=926) were compared for children aged between 9–13 years within high and low SES areas.

Results:

From 1985 to 2001, the frequency of walking to or from school declined (4.38±4.3 vs. 3.61 ± 3.8 trips/wk, p<0.001), cycling to or from school also declined (1.22±2.9 vs. 0.36±1.5 trips/wk, p<0.001), and the frequency of PE lessons declined (1.64±1.1 vs. 1.18±0.9 lessons/wk, p<0.001). However, the frequency of school sport increased (0.9±1.22 vs. 1.24±0.8 sessions/wk, p<0.001). In 1985, 11.7% of children were overweight or obese compared with 28.7% in 2001 (p<0.001). Apart from walking to school and school sport, there were greater relative declines in cycling to school and PE, and increases in overweight and obesity among children attending schools in low SES areas compared with those attending schools in high SES areas.

Conclusions:

Declines in active school transport and PE have occurred at the same time as increases in overweight and obesity among Australian children.

Implications:
Promoting active school transport and maintaining school sport and PE should be important public health priorities in Australia. Current inequities in school sport and PE and in prevalence of overweight and obesity by area-level SES also need to be addressed.

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Background: The contribution of family circumstance to physical activity and television viewing has not been widely investigated in pre-adolescents, and available information is inconsistent. This study examines whether television viewing and objectively measured physical activity vary by different indicators of family circumstance.
Methods: Data from the 2001 Children's Leisure Activity Study and the 2002/3 Health, Eating and Play Study, involving Australian children in Grades Prep (mean age 6y) and 5–6 (mean age 11y), were combined. Children wore accelerometers for six consecutive 24 hour periods. Average min/day in low-intensity activity (1.0–1.9 METs) and moderate-to-vigorous-intensity activity (≥3 METs) were calculated. Parents reported children's television viewing and family circumstance. Linear regression analyses were conducted separately for young girls, young boys, older girls and older boys. Results: Complete data were available for 2458 children. Parental education and, to a lesser extent, employment level were inversely associated with television viewing. Children in single-parent families, those whose fathers were not in paid employment, and those without siblings tended to spend more time in low-intensity activity than their peers. Children with siblings spent more time in moderate-to-vigorous-intensity activity; associations were stronger for girls. Maternal education was positively associated with moderate-to-vigorous-intensity activity for younger children. Maternal employment was positively associated with moderate-to-vigorous-intensity activity for older children. Multivariable models did not demonstrate a cumulative explanatory effect.
Conclusion:
  Individual measures of family circumstance were differentially associated with television, low-intensity activity and moderate-to-vigorous-intensity activity and associations were often not consistent across age-by-gender groups. Interventions may need to be tailored accordingly.

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Purpose. To examine associations between children's perceptions of the neighborhood environment and walking and physical activity.
Design. Cross-sectional study of a school-based sample.
Setting. Elementary schools in Melbourne, Australia.
Subjects. 280 children aged 10 years (response rate 78%).
Measures. A self-report survey assessed children's perceptions of the neighborhood physical and social environments and their weekly walking frequency. Physical activity was also objectively measured using accelerometers.
Results. Multiple linear regression analyses showed a positive association between walking frequency and the number of accessible destinations in the neighborhood among boys; having a neighborhood that was easy to walk/cycle around and perceiving lots of graffiti were positively associated with walking frequency among girls. Perceiving lots of litter and rubbish was positively associated with boys' overall physical activity, but no environmental variables were associated with girls' overall physical activity.
Conclusion. Several different environmental factors were associated with walking and physical activity. Perceptions of the neighborhood environment were more strongly associated with girls' walking than with objectively-measured physical activity. Future studies should confirm these findings using objective measures and prospective study designs.

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Objective: To estimate variation between small areas in the levels of walking, cycling, jogging, and swimming and overall physical activity and the importance of area level socioeconomic disadvantage in predicting physical activity participation.

Methods: All census collector districts (CCDs) in the 20 innermost local government areas in metropolitan Melbourne, Australia, were identified and ranked by the percentage of low income households (<$400/week) living in the CCD. Fifty CCDs were randomly selected from the least, middle, and most disadvantaged septiles of the ranked CCDs and 2349 residents (58.7% participation rate) participated in a cross sectional postal survey about physical activity. Multilevel logistic regression (adjusted for extrabinomial variation) was used to estimate area level variation in walking, cycling, jogging, and swimming and in overall physical activity participation, and the importance of area level socioeconomic disadvantage in predicting physical activity participation.

Results: There were significant variations between CCDs in all activities and in overall physical participation in age and sex adjusted models; however, after adjustment for individual SES (income, occupation, education) and area level socioeconomic disadvantage, significant differences remained only for walking (p = 0.004), cycling (p = 0.003), and swimming (p = 0.024). Living in the most socioeconomically disadvantaged areas was associated with a decreased likelihood of jogging and of having overall physical activity levels that were sufficiently active for health; these effects remained after adjustment for individual socioeconomic status (sufficiently active: OR 0.70, 95% CI 0.55 to 0.90 and jogging: OR = 0.69, 95% CI 0.51 to 0.94).

Conclusion: These research findings support the need to focus on improving local environments to increase physical activity participation.

Abbreviations: SES, socioeconomic status; CCD, census collector district


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Objective: To examine socio-demographic and psychosocial moderators, and self-efficacy as a mediator of the cross-sectional relationships between having access to recreational facilities and leisure-time physical activity (LTPA); to investigate the extent to which the environment-LTPA associations could be explained by self-selection to neighborhoods.

Design: A two-stage stratified sampling design was used to recruit 2,650 adults (aged 20-65) from 32 urban communities varying in walkability and socioeconomic status. Participants reported perceived access to facilities and home equipment for LTPA, weekly minutes of LTPA, self-efficacy for and enjoyment of LTPA, reasons for neighborhood selection, and socio-demographic characteristics.

Main Outcome Measures:
Self-reported recreational walking and other forms of moderate-to-vigorous LTPA expressed in MET-minutes.

Results: Specific types of recreational facilities were independently  associated with LTPA. Age, education, being overweight/ obese, reasons for neighborhood selection, enjoyment of, and self-efficacy for LTPA moderated these relationships. Self-efficacy was not a significant mediator of these cross-sectional associations.

Conclusion:
These findings have potentially significant implications for the planning of environmental interventions aimed at increasing population-level LTPA particularly in those who are less attitudinally inclined to being physically active.

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Objective - To identify socio-demographic characteristics of children from socioeconomically disadvantaged neighbourhoods who meet physical activity and screen recommendations.
Method - Children aged 5–12 years (n = 373; 45% boys) were recruited in 2007 from socioeconomically disadvantaged urban and rural areas of Victoria, Australia. Children's physical activity, height and weight were objectively measured. Mothers reported their highest level of education, and proxy-reported their child's usual screen-time. Odds ratios (OR) and 95% confidence intervals (95% CI) examined odds of meeting physical activity (> 60 minutes/day) and screen (≤ 120 minutes/day) recommendations according to socio-demographic characteristics.
Results - Approximately 84% of children met physical activity and 43% met screen recommendations. Age was inversely associated with odds of meeting physical activity and screen recommendations, and overweight/obese status was associated with lower odds of meeting screen recommendations (boys: OR = 0.39, 95%CI = 0.16–0.95; girls: OR = 0.47, 95%CI = 0.26–0.83). Among boys, living in a rural area was positively associated with meeting screen recommendations (OR = 3.08, 95%CI = 1.42–6.64). Among girls, high levels of maternal education were positively associated with meeting screen recommendations (OR = 2.76, 95%CI = 1.33–5.75).
Conclusion - Specific socio-demographic characteristics were associated with odds of meeting physical activity and screen recommendations. Identifying factors associated with such ‘resilience’ among this group may provide important learnings to inform future physical activity promotion initiatives.

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The study purpose was to investigate predictive associations between adolescent girls’ motivational predispositions to physical education (PE) and habitual physical activity. Two hundred girls (age 13.1 ± 0.6 years) completed the Physical Education Predisposition Scale and the Physical Activity Questionnaire for Older Children. ANCOVAs revealed that girls with the highest Perceived PE Worth and Perceived PE Ability scores were the most habitually active groups (p < .0001). Significant predictors of physical activity identified by hierarchical regression were Perceived PE Ability and body mass index, which accounted for 17% and 3% of variance, respectively. As Perceived PE Ability was strongly associated with physical activity, the correlates of this construct should be further established to inform future school and PE-based interventions.

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Introduction Policy and regulatory interventions aimed at creating environments more conducive to physical activity (PA) are an important component of strategies to improve population levels of PA. However, many potentially effective policies are not being broadly implemented. This study sought to identify potential policy/regulatory interventions targeting PA environments, and barriers/facilitators to their implementation at the Australian state/territory government level.

Methods In-depth interviews were conducted with senior representatives from state/territory governments, statutory authorities and non-government organisations (n = 40) to examine participants': 1) suggestions for regulatory interventions to create environments more conducive to PA; 2) support for preselected regulatory interventions derived from a literature review. Thematic and constant comparative analyses were conducted.

Results Policy interventions most commonly suggested by participants fell into two areas: 1) urban planning and provision of infrastructure to promote active travel; 2) discouraging the use of private motorised vehicles. Of the eleven preselected interventions presented to participants, interventions relating to walkability/cycling and PA facilities received greatest support. Interventions involving subsidisation (of public transport, PA-equipment) and the provision of more public transport infrastructure received least support. These were perceived as not economically viable or unlikely to increase PA levels. Dominant barriers were: the powerful ‘road lobby’, weaknesses in the planning system and the cost of potential interventions. Facilitators were: the provision of evidence, collaboration across sectors, and synergies with climate change/environment agendas.

Conclusion This study points to how difficult it will be to achieve policy change when there is a powerful ‘road lobby’ and government investment prioritises road infrastructure over PA-promoting infrastructure. It highlights the pivotal role of the planning and transport sectors in implementing PA-promoting policy, however suggests the need for clearer guidelines and responsibilities for state and local government levels in these areas. Health outcomes need to be given more direct consideration and greater priority within non-health sectors.