962 resultados para accelerometry-based physical activity


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In addition to the well-known health risks associated with lack of physical activity (PA), evidence is emerging about the health risks of sedentary behaviour (sitting). Research about patterns and correlates of sitting and PA in older women is scarce. METHODS: Self-report data from 6,116 women aged 76-81 years were collected as part of the Australian Longitudinal Study on Woman’s Health. Linear regression models were computed to examine whether demographic, social and health factors were associated with sitting and PA. RESULTS: Women who did no PA sat more than women who did any PA (p<0.001). Seven correlates were associated with sitting and PA (p<0.05). Five of these were associated with more sitting and less PA: three health-related (BMI, chronic conditions, anxiety/depression) and two social correlates (caring duties, volunteering). One demographic (being from another English-speaking country) and one social correlate (more social interaction) were associated with more sitting and more PA. Four correlates, two demographic (living in a city; post-high school education), one social (being single), and one health-related correlate (dizziness/loss of balance) were associated with more sitting only. Two other health-related correlates (stiff/painful joints; feet problems) were associated with less PA only. CONCLUSION: Sedentary behaviour and PA are distinct behaviours in older Australian women. Information about the correlates of both behaviours can be used to identify population groups who might benefit from interventions to reduce sedentary behaviour and/or increase PA.

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Objective: The aim of this study was to investigate the associations among measured physical fitness, perceived fitness, intention towards future physical activity and self-reported physical activity through junior high school years. Methods: Study participants included 122 Finnish students who were 13 years old during Grade 7. The sample was comprised of 80 girls and 42 boys from 3 junior high schools (Grades 7-9). During the autumn semester of Grade 7, students completed fitness tests and a questionnaire analyzing self-perception of their physical fitness. The questionnaire delivered at Grade 8 included intention towards future physical activity. At Grade 9 students’ self-reported physical activity levels. Results: Structural Equation Modeling revealed an indirect path from physical fitness to self-reported physical activity via perceived physical fitness and intention towards future physical activity. The model also demonstrated a correlation between perceived physical fitness and physical activity. Squared multiple correlations revealed that perceived physical fitness explained 33 % of the actual physical fitness. Conclusions: The results of this study highlight the role of physical and cognitive variables in the process of adoption of physical activity in adolescence.

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Biomarker analysis has been implemented in sports research in an attempt to monitor the effects of exertion and fatigue in athletes. This study proposed that while such biomarkers may be useful for monitoring injury risk in workers, proteomic approaches might also be utilised to identify novel exertion or injury markers. We found that urinary urea and cortisol levels were significantly elevated in mining workers following a 12 hour overnight shift. These levels failed to return to baseline over 24h in the more active maintenance crew compared to truck drivers (operators) suggesting a lack of recovery between shifts. Use of a SELDI-TOF MS approach to detect novel exertion or injury markers revealed a spectral feature which was associated with workers in both work categories who were engaged in higher levels of physical activity. This feature was identified as the LG3 peptide, a C-terminal fragment of the anti-angiogenic / anti-tumourigenic protein endorepellin. This finding suggests that urinary LG3 peptide may be a biomarker of physical activity. It is also possible that the activity mediated release of LG3 / endorepellin into the circulation may represent a biological mechanism for the known inverse association between physical activity and cancer risk / survival.

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Background Although physical activity is associated with health-related quality of life (HRQL), the nature of the dose-response relationship remains unclear. This study examined the concurrent and prospective dose-response relationships between total physical activity (TPA) and (only) walking with HRQL in two age cohorts of women. Methods Participants were 10,698 women born in 1946-1951 and 7,646 born in 1921-1926, who completed three mailed surveys for the Australian Longitudinal Study on Women's Health. They reported weekly TPA minutes (sum of walking, moderate, and vigorous minutes). HRQL was measured with the Medical Outcomes Study Short-Form 36 Health Status Survey (SF-36). Linear mixed models, adjusted for socio-demographic and health-related variables, were used to examine associations between TPA level (none, very low, low, intermediate, sufficient, high, and very high) and SF-36 scores. For women who reported walking as their only physical activity, associations between walking and SF-36 scores were also examined. Results Curvilinear trends were observed between TPA and walking with SF-36 scores. Concurrently, HRQL scores increased significantly with increasing TPA and walking, in both cohorts, with increases less marked above sufficient activity levels. Prospectively, associations were attenuated although significant and meaningful improvements in physical functioning and vitality were observed across most TPA and walking categories above the low category. Conclusion For women in their 50s-80s without clinical depression, greater amounts of TPA are associated with better current and future HRQL, particularly physical functioning and vitality. Even if walking is their only activity, women, particularly those in their 70s-80s, have better health-related quality of life.

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Background: Physical activity is a key modifiable behavior impacting a number of important health outcomes. The path to developing chronic diseases commonly commences with lifestyle patterns developed during childhood and adolescence. This study examined whether parent physical activity and other factors correlated with physical activity amongst children are associated with self-reported physical activity in adolescents. Methods: A total of 115 adolescents (aged 12-14) and their parents completed questionnaire assessments. Self-reported physical activity was measured amongst adolescents and their parents using the International Physical Activity Questionnaire for Adolescents (IPAQ-A), and the International Physical Activity Questionnaire (IPAQ) respectively. Adolescents also completed the Children’s Physical Activity Correlates (CPAC), which measured factors that have previously demonstrated association with physical activity amongst children. To examine whether parent physical activity or items from the CPAC were associated with self-reported adolescent physical activity, backward step-wise regression was undertaken. One item was removed at each step in descending order of significance (until two tailed item alpha=0.05 was achieved). Results: A total of 93 (80.9%) adolescents and their parents had complete data sets and were included in the analysis. Independent variables were removed in the order: perceptions of parental role modeling; importance of exercise; perceptions of parental encouragement; peer acceptance; fun of physical exertion; perceived competence; parent physical activity; self-esteem; liking of exercise; and parental influence. The only variable remaining in the model was ‘liking of games and sport’ (p=0.003, adjusted r-squared=0.085). Discussion: These findings indicate that factors associated with self-reported physical activity in adolescents are not necessarily the same as younger children (aged 8-11). While ‘liking of games and sport’ was included in the final model, the r-squared value did not indicate a strong association. Interestingly, parent self-reported physical activity was not included in the final model. It is likely that adolescent physical activity may be influenced by a variety of direct and indirect forms of socialization. These findings do support the view that intrinsically motivated themes such as the liking of games and sport take precedence over outside influences, like those presented by parents, in determining youth physical activity behaviors. These findings do not suggest that parents have no influence on adolescent physical activity patterns, but rather, the influence is likely to be more complex than physical activity behavior modeling perceived by the adolescent. Further research in this field is warranted in order to better understand potential contributors to successful physical activity promotion interventions amongst young adolescents.

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Not having 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 health problem. To address this, 25 studies have used improvement activities directed at communities using more than one approach in a single program. When we looked at the available research, we observed that there was a lack of good studies which could show whether this approach was or wasn't beneficial. For example, some research studies claimed that community wide programs improved physical activities and other studies did not. It was not possible to determine what might work. Future research is needed with improved designs, measures of outcomes and larger samples of participants.

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Parents are at risk for inactivity; however, research into understanding parental physical activity (PA) is scarce. We integrated self-determined motivation, planning, and the theory of planned behavior (TPB) to better understand parental PA. Parents (252 mothers, 206 fathers) completed a main questionnaire assessing measures underpinning these constructs and a 1-week follow-up of PA behavior to examine whether self-determined motivation indirectly influenced intention via the TPB variables (i.e., attitude, subjective norm, and perceived behavioral control) and intention indirectly influenced behavior via planning. We found self-determined motivation on intention was fully mediated by the TPB variables and intention on behavior was partially mediated by the planning variables. In addition, slight differences in the model’s paths between the sexes were revealed. The results illustrate the range of important determinants of parental PA and provide support for the integrated model in explaining PA decision making as well as the importance of examining sex differences.

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This study suggests that physical activity is a more important lifestyle modification than sleep to improve cardiovascular risk factors in postmenopausal women; however both lifestyle modifications, including, ensuring sufficient sleep quality and duration and increasing physical activity should be strongly encouraged by menopause practitioners in postmenopausal women care.

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In many countries, governments and health agencies are strongly promoting physical activity as a means to prevent the accumulation of fatness that leads to weight gain and obesity. However, there is often a resistance to respond to health promotion initiatives. For example, in the UK, the Chief Medical Officer has recently reported that 71% of women and 61% of men fail to carry out even the minimal amount of physical activity recommended in the government’s guidelines. Similarly, the Food safety Agency has promoted reductions in the intake of fat, sugar and salt but with very little impact on the pattern of consumption. Why is it that recommendations to improve health are so difficult to implement, and produce the desired outcome?