993 resultados para Physical activity measurement


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We investigated the key beliefs to target in interventions aimed at increasing physical activity (PA) among mothers and fathers of young children. Parents (288 mothers and 292 fathers) completed a Theory of Planned Behaviour belief-based questionnaire and a 1-week follow-up of PA behaviour. We found that a range of behavioural, normative, and control beliefs were significantly correlated with parents’ PA intentions and behaviour, with only a few differences observed in correlations between PA beliefs and intention and behaviour by gender. A range of key beliefs was identified as making independent contributions to parents’ PA intentions; however, the behavioural beliefs about improving parenting practices (β = 0.13), interfering with other commitments (β = −0.29); normative beliefs about people I exercise with (β = 0.20); and control beliefs about lack of time (β = −0.24), inconvenience (β = −0.14), lack of motivation (β = −0.34), were revealed as significant independent predictors of actual PA behaviour. Furthermore, we found that a limited amount of parents already hold these beliefs, suggesting that these key beliefs warrant changing and, therefore, are appropriate targets for subsequent intervention. The current study fills an empirical gap in the PA literature by investigating an at-risk group and using a well established theoretical framework to identify key beliefs that guide parents’ PA decision-making. Overall, we found support for parents being a unique group who hold distinctive behavioural, normative, and control beliefs toward PA. Attention to these key underlying beliefs will assist intervention work aimed at combating inactivity among this at-risk population.

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Obesity is affecting an increasing proportion of children globally. Despite an appreciation that physical activity is essential for the normal growth and development of children and prevents obesity and obesity-related health problems, too few children are physically active. A concurrent problem is that today’s young people spend more time than previous generations did in sedentary pursuits, including watching television and engaging in screen-based games. Active behavior has been displaced by these inactive recreational choices, which has contributed to reductions in activity-related energy expenditure. Implementation of multifactorial solutions considered to offer the best chance of combating these trends is urgently required to redress the energy imbalance that characterizes obesity. The counterproductive ‘shame and blame’ mentality that apportions responsibility for the childhood obesity problem to sufferers, their parents, teachers or health-care providers needs to be changed. Instead, these groups should offer constant support and encouragement to promote appropriate physical activity in children. Failure to provide activity opportunities will increase the likelihood that the children of today will live less healthy (and possibly shorter)lives than their parents.

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Objective The Active Australia Survey (AAS) is used for physical activity (PA) surveillance in the general Australian adult population, but its validity in older adults has not been evaluated. Our aim was to examine the convergent validity of the AAS questions in older adults. Design The AAS was validated against pedometer step counts as an objective measure of PA, self-reported physical function, and a step-test to assess cardiorespiratory fitness. Method Participants were community-dwelling adults, aged 65-89 y, with the ability to walk 100 m. They completed a self-administered AAS and the step-test in one interview. One week earlier, they completed the Short Form-36 physical function subscale. Between these two interviews, they each wore a YAMAX Digiwalker SW200 pedometer and recorded daily steps. Using the AAS data, daily walking minutes and total PA minutes (walking, moderate-intensity PA and vigorous-intensity PA) were compared with the validity measures using Spearman rank-order correlations. Fifty-three adults completed the study. Results Median daily walking minutes were 34.2 (interquartile range [IQR] 17.1, 60.0), and median daily total PA minutes were 68.6 (IQR 31.4, 113.6). Walking and total PA minutes were both moderately correlated with pedometer steps (Spearman correlation r=0.42, p=0.003, for each) but not with step-test seconds to completion (r=-0.11, p=0.44; r=-0.25, p=0.08, respectively). Total PA minutes were significantly correlated with physical function scores (r=0.39, p=0.004), but walking minutes were not (r=0.15, p=0.29). Conclusions This initial examination of the psychometric properties of the AAS for older adults suggests that this surveillance tool has acceptable convergent validity for ambulatory, community-dwelling older adults.

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Background Postnatal women (<12 months postpartum) are at increased risk of physical inactivity. Purpose To evaluate the efficacy and feasibility of a theory-based physical activity (PA) intervention delivered to postnatal women primarily via mobile telephone short message service (SMS). Methods Eighty-eight women were randomized to the intervention (n=45) or minimal contact control (n=43) condition. The 12-week intervention consisted of a face-to-face PA goal-setting consultation, a goal-setting magnet, three to five personally tailored SMS/week and a nominated support person who received two SMS per week. SMS content targeted constructs of social cognitive theory. Frequency (days/week) and duration (min/week) of PA participation and walking for exercise were assessed via self-report at baseline, 6 and 13 weeks. Results Intervention participants increased PA frequency by 1.82 days/week (SE±0.18) by 13 weeks (F(2,85)=4.46, p=0.038) and walking for exercise frequency by 1.08 days/ week (SE±0.24) by 13 weeks (F(2,85)=5.38, p=0.02). Positive trends were observed for duration (min/week) of PA and walking for exercise. Conclusions Intervention exposure resulted in increased frequency of PA and walking for exercise in postnatal women.

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This review assembles pedometry literature focused on youth, with particular attention to expected values for habitual, school day, physical education class, recess, lunch break, out-of-school, weekend, and vacation activity. From 31 studies published since 1999, we constructed a youth habitual activity step-curve that indicates: (a) from ages 6 to 18 years, boys typically take more steps per day than girls; (b) for both sexes the youngest age groups appear to take fewer steps per day than those immediately older; and (c) from a young age, boys decline more in steps per day to become move consistent with girls at older ages. Additional studies revealed that boys take approximately 42-49% of daily steps during the school day; girls take 41-47%. Steps taken during physical education class contribute to total steps per day by 8.7-23.7% in boys and 11.4-17.2% in girls. Recess represents 8-11% and lunch break represents 15-16% of total steps per day. After-school activity contributes approximately 47-56% of total steps per day for boys and 47-59% for girls. Weekdays range from approximately 12,000 to 16,000 steps per day in boys and 10,000 to 14,000 steps per day in girls. The corresponding values for weekend days are 12,000-13,000 steps per day in boys and 10,000-12,000 steps per day in girls.

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The figure Beets took exception to displays sex‐ and age‐specific median values of aggregated published expected values for pedometer determined physical activity.

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The purpose of this review is to update expected values for pedometer-determined physical activity in free-living healthy older populations. A search of the literature published since 2001 began with a keyword (pedometer, "step counter," "step activity monitor" or "accelerometer AND steps/day") search of PubMed, Cumulative Index to Nursing & Allied Health Literature (CINAHL), SportDiscus, and PsychInfo. An iterative process was then undertaken to abstract and verify studies of pedometer-determined physical activity (captured in terms of steps taken; distance only was not accepted) in free-living adult populations described as ≥ 50 years of age (studies that included samples which spanned this threshold were not included unless they provided at least some appropriately age-stratified data) and not specifically recruited based on any chronic disease or disability. We identified 28 studies representing at least 1,343 males and 3,098 females ranging in age from 50–94 years. Eighteen (or 64%) of the studies clearly identified using a Yamax pedometer model. Monitoring frames ranged from 3 days to 1 year; the modal length of time was 7 days (17 studies, or 61%). Mean pedometer-determined physical activity ranged from 2,015 steps/day to 8,938 steps/day. In those studies reporting such data, consistent patterns emerged: males generally took more steps/day than similarly aged females, steps/day decreased across study-specific age groupings, and BMI-defined normal weight individuals took more steps/day than overweight/obese older adults. The range of 2,000–9,000 steps/day likely reflects the true variability of physical activity behaviors in older populations. More explicit patterns, for example sex- and age-specific relationships, remain to be informed by future research endeavors.

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Background Along with reduced levels of physical activity, older Australian's mean energy consumption has increased. Now over 60% of older Australians are considered overweight or obese. This study aims to confirm if a low-cost, accessible physical activity and nutrition program can improve levels of physical activity and diet of insufficiently active 60-70 year-olds. Methods/Design This 12-month home-based randomised controlled trial (RCT) will consist of a nutrition and physical activity intervention for insufficiently active people aged 60 to 70 years from low to medium socio-economic areas. Six-hundred participants will be recruited from the Australian Federal Electoral Role and randomly assigned to the intervention (n = 300) and control (n = 300) groups. The study is based on the Social Cognitive Theory and Precede-Proceed Model, incorporating voluntary cooperation and self-efficacy. The intervention includes a specially designed booklet that provides participants with information and encourages dietary and physical activity goal setting. The booklet will be supported by an exercise chart, calendar, bi-monthly newsletters, resistance bands and pedometers, along with phone and email contact. Data will be collected over three time points: pre-intervention, immediately post-intervention and 6-months post-study. Discussion This trial will provide valuable information for community-based strategies to improve older adults' physical activity and dietary intake. The project will provide guidelines for appropriate sample recruitment, and the development, implementation and evaluation of a minimal intervention program, as well as information on minimising barriers to participation in similar programs.

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Background By 2025, it is estimated that approximately 1.8 million Australian adults (approximately 8.4% of the adult population) will have diabetes, with the majority having type 2 diabetes. Weight management via improved physical activity and diet is the cornerstone of type 2 diabetes management. However, the majority of weight loss trials in diabetes have evaluated short-term, intensive clinic-based interventions that, while producing short-term outcomes, have failed to address issues of maintenance and broad population reach. Telephone-delivered interventions have the potential to address these gaps. Methods/Design Using a two-arm randomised controlled design, this study will evaluate an 18-month, telephone-delivered, behavioural weight loss intervention focussing on physical activity, diet and behavioural therapy, versus usual care, with follow-up at 24 months. Three-hundred adult participants, aged 20-75 years, with type 2 diabetes, will be recruited from 10 general practices via electronic medical records search. The Social-Cognitive Theory driven intervention involves a six-month intensive phase (4 weekly calls and 11 fortnightly calls) and a 12-month maintenance phase (one call per month). Primary outcomes, assessed at 6, 18 and 24 months, are: weight loss, physical activity, and glycaemic control (HbA1c), with weight loss and physical activity also measured at 12 months. Incremental cost-effectiveness will also be examined. Study recruitment began in February 2009, with final data collection expected by February 2013. Discussion This is the first study to evaluate the telephone as the primary method of delivering a behavioural weight loss intervention in type 2 diabetes. The evaluation of maintenance outcomes (6 months following the end of intervention), the use of accelerometers to objectively measure physical activity, and the inclusion of a cost-effectiveness analysis will advance the science of broad reach approaches to weight control and health behaviour change, and will build the evidence base needed to advocate for the translation of this work into population health practice.

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Overweight and obesity are a significant cause of poor health worldwide, particularly in conjunction with low levels of physical activity (PA). PA is health-protective and essential for the physical growth and development of children, promoting physical and psychological health while simultaneously increasing the probability of remaining active as an adult. However, many obese children and adolescents have a unique set of physiological, biomechanical, and neuromuscular barriers to PA that they must overcome. It is essential to understand the influence of these barriers on an obese child's motivation in order to exercise and tailor exercise programs to the special needs of this population. Chapter Outline • Introduction • Defining Physical Activity, Exercise, and Physical Fitness • Physical Activity, Physical Fitness, And Motor Competence In Obese Children • Physical Activity and Obesity in Children • Physical Fitness in Obese Children • Balance and Gait in Obese Children • Motor Competence in Obese Children • Physical Activity Guidelines for Obese Children • Clinical Assessment of the Obese Child • Physical Activity Characteristics: Mode • Physical Activity Characteristics: Intensity • Physical Activity Characteristics: Frequency • Physical Activity Characteristics: Duration • Conclusion