305 resultados para Moderate-to-vigorous physical activity
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Recent data from Australia, the United States and Europe show increased self-reported energy intake associated with obesity, in contrast to earlier suggestions that the obesity epidemic has occurred despite minimal or no increase in per capita energy intake from food. The effect of increased energy intake is compounded by sedentary lifestyles. Both physical activity and nutrition must be addressed to reduce the prevalence of obesity and improve the health of Australians.
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Chronic physical inactivity is a major risk factor for a number of important lifestyle diseases, while inappropriate exposure to high physical demands is a risk factor for musculoskeletal injury and fatigue. Proteomic and metabolomic investigations of the physical activity continuum - extreme sedentariness to extremes in physical performance - offer increasing insight into the biological impacts of physical activity. Moreover, biomarkers, revealed in such studies, may have utility in the monitoring of metabolic and musculoskeletal health or recovery following injury. As a diagnostic matrix, urine is non-invasive to collect and it contains many biomolecules, which reflect both positive and negative adaptations to physical activity exposure. This review examines the utility and landscape of biomarkers of physical activity with particular reference to those found in urine.
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BACKGROUND: Variations in 'slope' (how steep or flat the ground is) may be good for health. As walking up hills is a physiologically vigorous physical activity and can contribute to weight control, greater neighbourhood slopes may provide a protective barrier to weight gain, and help prevent Type 2 diabetes onset. We explored whether living in 'hilly' neighbourhoods was associated with diabetes prevalence among the Australian adult population. METHODS: Participants ([greater than or equal to]25years; n=11,406) who completed the Western Australian Health and Wellbeing Surveillance System Survey (2003-2009) were asked whether or not they had medically-diagnosed diabetes. Geographic Information Systems (GIS) software was used to calculate a neighbourhood mean slope score, and other built environment measures at 1600m around each participant's home. Logistic regression models were used to predict the odds of self-reported diabetes after progressive adjustment for individual measures (i.e., age, sex), socioeconomic status (i.e., education, income), built environment, destinations, nutrition, and amount of walking. RESULTS: After full adjustment, the odds of self-reported diabetes was 0.72 (95% CI 0.55-0.95) and 0.52 (95% CI 0.39-0.69) for adults living in neighbourhoods with moderate and higher levels of slope, respectively, compared with adults living in neighbourhoods with the lowest levels of slope. The odds of having diabetes was 13% lower (odds ratio 0.87; 95% CI 0.80-0.94) for each increase of one percent in mean slope. CONCLUSIONS: Living in a hilly neighbourhood may be protective of diabetes onset or this finding is spurious. Nevertheless, the results are promising and have implications for future research and the practice of flattening land in new housing developments.
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Aim Physical activity (PA) patterns of retirement village residents were investigated using self-report and objective measures. Methods Residents (n = 323) from retirement villages in Perth, Australia, were surveyed on PA behaviour and various demographic, residency, health-related and mobility factors. Most participants wore accelerometers for 7 days. Retirement village managers (n = 32) were surveyed on village descriptive characteristics, including the provision of amenities and facilities. Logistic regression models examined village and resident characteristics associated with PA. Results Based on objective measurement, only 27.1% of participants were sufficiently active (n = 288). Walking was one of the most popular PA modes. Few village characteristics were associated with PA; however, villages located in more walkable neighbourhoods increased participants’ odds of transport walking. Travelling outside the village daily also increased PA odds. Conclusions Most residents were insufficiently active to gain health benefits. Considering individual and environmental factors, within the retirement village and neighbourhood settings, and associations with PA, warrants attention.
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Public health research consistently demonstrates the salience of neighbourhood as a determinant of both health-related behaviours and outcomes across the human life course. This paper will report on the findings from a mixed-methods Brisbane-based study that explores how mothers with primary school children from both high and low socioeconomic suburbs use the local urban environment for the purpose of physical activity. Firstly, we demonstrate findings from an innovative methodology using the geographic information systems (GIS) embedded in social media platforms on mobile phones to track locations, resource-use, distances travelled, and modes of transport of the families in real-time; and secondly, we report on qualitative data that provides insight into reasons for differential use of the environment by both groups. Spatial/mapping and statistical data showed that while the mothers from both groups demonstrated similar daily routines, the mothers from the high SEP suburb engaged in increased levels of physical activity, travelled less frequently and less distance by car, and walked more for transport. The qualitative data revealed differences in the psychosocial processes and characteristics of the households and neighbourhoods of the respective groups, with mothers in the lower SEP suburb reporting more stress, higher conflict, and lower quality relationships with neighbours.
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OBJECTIVE: To evaluate patterns of physical activity (PA), the prevalence of physical inactivity and the relationships between PA and sociodemographic, clinical and biochemical parameters among Sri Lankan adults. DESIGN: Descriptive cross-sectional study. SETTING: Nationally representative population-based survey conducted in Sri Lanka. SUBJECTS: Data on PA and associated details were obtained from 5000 adults. PA was assessed using the International Physical Activity Questionnaire (short-form). A binary logistic regression analysis was performed using the dichotomous variable ‘health-enhancing PA’ (05‘active’, 15‘inactive’). RESULTS: Sample size was 4485. Mean age was 46.1 (SD 15.1) years, 39.5% were males. The mean weekly total MET (metabolic equivalents of task) minutes of PA among the study population was 4703 (SD 4369). Males (5464 (SD 5452)) had a significantly higher weekly total MET minutes than females (4205 (SD 3394); P,0.001). Rural adults (5175 (SD 4583)) were significantly more active than urban adults (2956 (SD 2847); P<0.001). Tamils had the highest mean weekly total MET minutes among ethnicities. Those with tertiary education had lowest mean weekly total MET minutes. In all adults 60.0% were in the ‘highly active’ category, while only 11.0% were ‘inactive’ (males 14.6%, females 8.7%; P<0.001). Of the ‘highly active’ adults, 85.8% were residing in rural areas. Results of the binary logistic regression analysis indicated that female gender (OR52?1), age .70 years (OR53.8), urban living (OR52.5), Muslim ethnicity (OR52.7), tertiary education (OR53.6), obesity (OR51.8), diabetes (OR51.6), hypertension (OR51.2) and metabolic syndrome (OR51.3) were all associated with significantly increased odds of being physically ‘inactive’. CONCLUSIONS: The majority of Sri Lankan adults were ‘highly active’ physically. Female gender, older age, urban living, Muslim ethnicity and tertiary education were all significant predictors of physical inactivity. Physical inactivity was associated with obesity, diabetes, hypertension and metabolic syndrome.
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Purpose: To objectively assess daily light exposure and physical activity levels in myopic and emmetropic children. Methods: One hundred and two children (41 myopes and 61 emmetropes) aged 10 to 15 years old had simultaneous objective measures of ambient light exposure and physical activity collected over a 2 week period during school term, using a wrist worn actigraphy device (Actiwatch-2). Measures of visible light illuminance and physical activity were captured every 30 seconds, 24 hours a day over this period. Mean hourly light exposure and physical activity for weekdays and weekends were examined. To ensure that seasonal variations didn’t confound comparisons, the light and activity data of the 41 myopes, was compared with 41 age and gender matched emmetropes who wore the Actiwatch over the same two week period. Results: Mean light exposure and physical activity for all 101 children with valid data exhibited significant changes with time of day and day of the week (p<0.0001). On average greater daily light exposure occurred on weekends compared to weekdays (p<0.05), and greater physical activity occurred on weekdays compared to weekends (p<0.01). Myopic children (n = 41, mean daily light exposure 915 ± 519 lux) exhibited significantly lower average light exposure compared to 41 age and gender matched emmetropic children (1272 ± 625 lux, p<0.01). The amount of daily time spent in bright light conditions (>1000 lux) was also significantly greater in emmetropes (127 ± 51 minutes) compared to myopes (91 ± 44 minutes, p<0.001). No significant differences were found between the average daily physical activity levels of myopes and emmetropes (p>0.05). Conclusions: Myopic children exhibit significantly lower daily light exposure, but no significant difference in physical activity compared to emmetropic children. This suggests the important factor involved in documented associations between myopia and outdoor activity is likely exposure to bright outdoor light rather than greater physical activity.
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Objectives Given increasing trends of obesity being noted from early in life and that active lifestyles track across time, it is important that children at a very young age be active to combat a foundation of unhealthy behaviours forming. This study investigated, within a theory of planned behaviour (TPB) framework, factors which influence mothers’ decisions about their child’s 1) adequate physical activity (PA) and 2) limited screen time behaviours. Methods Mothers (N = 162) completed a main questionnaire, via on-line or paper-based administration, which comprised standard TPB items in addition to measures of planning and background demographic variables. One week later, consenting mothers completed a follow-up telephone questionnaire which assessed the decisions they had made regarding their child’s PA and screen time behaviours during the previous week. Results Hierarchical multiple regression analyses revealed support for the predictive model, explaining an overall 73% and 78% of the variance in mothers’ intention and 38% and 53% of the variance in mothers’ decisions to ensure their child engages in adequate PA and limited screen time, respectively. Attitude and subjective norms predicted intention in both target behaviours, as did intentions with behaviour. Contrary to predictions, perceived behavioural control (PBC) in PA behaviour and planning in screen time behaviour were not significant predictors of intention, neither was PBC a predictor of either behaviour. Conclusions The findings illustrate the various roles that psycho-social factors play in mothers’ decisions to ensure their child engages in active lifestyle behaviours which can help to inform future intervention programs aimed at combating very young children’s inactivity.
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Background Not getting enough physical activity leads to poorer health. Regular physical activity can reduce the risk of chronic disease and improve one’s health and well-being. The lack of physical activity is a common and growing problem in many countries. We sought to evaluate the effects of community wide, multi-strategic interventions upon the physical activity patterns of populations. Method We undertook a Cochrane Systematic Review which included an extensive search of databases, including studies which met pre-determined criteria, and conducted independent risk of bias assessment and data extraction. Results After the selection process, 25 studies were included in the review. The strategies varied by the number and type of components and their intensity. No studies were identified as low risk of bias. Sixteen studies were identified as having a high risk of bias and thus untrustworthy. Nine studies were of considered to have an unclear risk of bias and some studies held back data they collected. The effects reported were inconsistent across the studies and the measures. Some of the better designed studies showed no improvement in measures of physical activity. Interventions which have an environmental change component seemed to be a promising direction. Those interventions which were primarily a mass media campaign were less likely to be successful. Conclusions Although numerous studies have been undertaken, there is considerable inconsistency in the findings of the available studies and this is confounded by serious methodological issues within the included studies. Simply combining interventions does not necessarily result in increased physical activity as many such studies, including some long term programs, failed to demonstrate efficacy. There is a clear need for well-designed studies and these studies should focus on the quality of measurement of physical activity. The review is currently being updated with newer studies.
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Purpose To review and update the evidence relating to the personal, social, and environmental factors associated with physical activity (PA) in adults. Methods Systematic review of the peer-reviewed literature to identify papers published between 1998 and 2000 with PA (and including exercise and exercise adherence). Qualitative reports or case studies were not included. Results Thirty-eight new studies were located. Most confirmed the existence of factors already known to be correlates of PA. Changes in status were noted in relation to the influence of marital status, obesity, smoking, lack of time, past exercise behavior, and eight environmental variables. New studies were located which focused on previously understudied population groups such as minorities, middle and older aged adults, and the disabled. Conclusion The newly reported studies tend to take a broader “ecological” approach to understanding the correlates of PA and are more focused on environmental factors. There remains a need to better understand environmental influences and the factors that influence different types of PA. As most of the work in this field still relies on cross-sectional studies, longitudinal and intervention studies will be required if causal relationships are to be inferred.
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The purpose of this study was to evaluate the validity and inter-rater reliability of the Observation System for Recording Activity in Children: Youth Sports (OSRAC:YS). Children (N=29) participating in a parks and recreation soccer program were observed during regularly scheduled practices. Physical activity (PA) intensity and contextual factors were recorded by momentary time-sampling procedures (10-sec observe, 20-sec record). Two observers simultaneously observed and recorded children's PA intensity, practice context, social context, coach behavior, and coach proximity. Inter-rater reliability was based on agreement (Kappa) between the observer's coding for each category, and the Intraclass Correlation Coefficient (ICC) for percent of time spent in MVPA. Validity was assessed by calculating the correlation between OSRAC:YS estimated and objectively measured MVPA. Kappa statistics for each category demonstrated substantial to almost perfect inter-observer agreement (Κappa = 0.67 to 0.93). The ICC for percent time in MVPA was 0.76 (95% C.I. = 0.49 - 0.90). A significant correlation (r = 0.73) was observed for MVPA recorded by observation and MVPA measured via accelerometry. The results indicate the OSRAC:YS is a reliable and valid tool for measuring children's PA and contextual factors during a youth soccer practice.
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With measurement of physical activity becoming more common in clinical practice, it is imperative that healthcare professionals become more knowledgeable about the different methods available to objectively measure physical activity behaviour. Objective measures do not rely on information provided by the patient, but instead measure and record the biomechanical or physiological consequences of performing physical activity, often in real time. As such, objective measures are not subject to the reporting bias or recall problems associated with self-report methods. The purpose of this article was to provide an overview of the different methods used to objectively measure physical activity in clinical practice. The review was delimited to heart rate monitoring, accelerometers and pedometers since their small size, low participant burden and relatively low cost make these objective measures appropriate for use in clinical practice settings. For each measure, strengths and weakness were discussed; and whenever possible, literature-based examples of implementation were provided.
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Physical activity (PA) parenting research has proliferated over the past decade, with findings verifying the influential role that parents play in children's emerging PA behaviors. This knowledge, however, has not translated into effective family-based PA interventions. During a preconference workshop to the 2012 International Society for Behavioral Nutrition and Physical Activity annual meeting, a PA parenting workgroup met to: (1) Discuss challenges in PA parenting research that may limit its translation, (2) identify explanations or reasons for such challenges, and; (3) recommend strategies for future research. Challenges discussed by the workgroup included a proliferation of disconnected and inconsistently measured constructs, a limited understanding of the dimensions of PA parenting, and a narrow conceptualization of hypothesized moderators of the relationship between PA parenting and child PA. Potential reasons for such challenges emphasized by the group included a disinclination to employ theory when developing measures and examining predictors and outcomes of PA parenting as well as a lack of agreed-upon measurement standards. Suggested solutions focused on the need to link PA parenting research with general parenting research, define and adopt rigorous standards of measurement, and identify new methods to assess PA parenting. As an initial step toward implementing these recommendations, the workgroup developed a conceptual model that: (1) Integrates parenting dimensions from the general parenting literature into the conceptualization of PA parenting, (2) draws on behavioral and developmental theory, and; (3) emphasizes areas which have been neglected to date including precursors to PA parenting and effect modifiers.
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Research Findings The present study investigated whether active play during recess was associated with self-regulation and academic achievement in a prekindergarten sample. A total of 51 children in classes containing approximately half Head Start children were assessed on self-regulation, active play, and early academic achievement. Path analyses indicated that higher active play was associated with better self-regulation, which in turn was associated with higher scores on early reading and math assessments. Practice or Policy Results point to the benefits of active play for promoting self-regulation and offer insight into possible interventions designed to promote self-regulation and academic achievement.
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Accurate and detailed measurement of an individual's physical activity is a key requirement for helping researchers understand the relationship between physical activity and health. Accelerometers have become the method of choice for measuring physical activity due to their small size, low cost, convenience and their ability to provide objective information about physical activity. However, interpreting accelerometer data once it has been collected can be challenging. In this work, we applied machine learning algorithms to the task of physical activity recognition from triaxial accelerometer data. We employed a simple but effective approach of dividing the accelerometer data into short non-overlapping windows, converting each window into a feature vector, and treating each feature vector as an i.i.d training instance for a supervised learning algorithm. In addition, we improved on this simple approach with a multi-scale ensemble method that did not need to commit to a single window size and was able to leverage the fact that physical activities produced time series with repetitive patterns and discriminative features for physical activity occurred at different temporal scales.