421 resultados para Physical activity level


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We aimed to compare physical activity level and cardiorespiratory fitness in children with different chronic diseases, such as type 1 diabetes mellitus (T1DM), obesity (OB) and juvenile idiopathic arthritis (JIA), with healthy controls (HC). We performed a cross-sectional study including 209 children: OB: n = 45, T1DM: n = 48, JIA: n = 31, and HC: n = 85. Physical activity level was assessed by accelerometer and cardiorespiratory fitness by a treadmill test. ANOVA, linear regressions and Pearson correlations were used. Children with chronic diseases had reduced total daily physical activity counts (T1DM 497 +/- 54 cpm, p = 0.003; JIA 518 +/- 28, p < 0.001, OB 590 +/- 25, p = 0.003) and cardiorespiratory fitness (JIA 39.3 +/- 1.7, p = 0.001, OB 41.7 +/- 1.2, p = 0.020) compared to HC (668 +/- 35 cpm; 45.3 +/- 0.9 ml kg(-1) min(-1), respectively). Only 60.4% of HC, 51.6% of OB, 38.1% of JIA and 38.5% of T1DM children met the recommended daily 60 min of moderate-to-vigorous physical activity. Low cardiorespiratory fitness was associated with female gender and low daily PA. Children with chronic diseases had reduced physical activity and cardiorespiratory fitness. As the benefits of PA on health have been well demonstrated during growth, it should be encouraged in those children to prevent a reduction of cardiorespiratory fitness and the development of comorbidities.

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OBJECTIVE: Little is known regarding health-related quality of life and its relation with physical activity level in the general population. Our primary objective was to systematically review data examining this relationship. METHODS: We systematically searched MEDLINE, EMBASE, CINAHL, and PsycINFO for health-related quality of life and physical activity related keywords in titles, abstracts, or indexing fields. RESULTS: From 1426 retrieved references, 55 citations were judged to require further evaluation. Fourteen studies were retained for data extraction and analysis; seven were cross-sectional studies, two were cohort studies, four were randomized controlled trials and one used a combined cross sectional and longitudinal design. Thirteen different methods of physical activity assessment were used. Most health-related quality of life instruments related to the Medical Outcome Study SF-36 questionnaire. Cross-sectional studies showed a consistently positive association between self-reported physical activity and health-related quality of life. The largest cross-sectional study reported an adjusted odds ratio of "having 14 or more unhealthy days" during the previous month to be 0.40 (95% Confidence Interval 0.36-0.45) for those meeting recommended levels of physical activity compared to inactive subjects. Cohort studies and randomized controlled trials tended to show a positive effect of physical activity on health-related quality of life, but similar to the cross-sectional studies, had methodological limitations. CONCLUSION: Cross-sectional data showed a consistently positive association between physical activity level and health-related quality of life. Limited evidence from randomized controlled trials and cohort studies precludes a definitive statement about the nature of this association.

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Adolescence is an important time for acquiring high peak bone mass. Physical activity is known to be beneficial to bone development. The effect of estrogen-progestin contraceptives (EPC) is still controversial. Altogether 142 (52 gymnasts, 46 runners, and 42 controls) adolescent women participated in this study, which is based on two 7-year (n =142), one 6-year (n =140) and one 4-year (n =122) follow-ups. Information on physical activity, menstrual history, sexual maturation, nutrition, living habits and health status was obtained through questionnaires and interviews. The bone mineral density (BMD) and content (BMC) of lumbar spine (LS) and femoral neck (FN) were measured by dual- energy X-ray absoptiometry. Calcaneal sonographic measurements were also made. The physical activity of the athletes participating in this study decreased after 3-year follow-up. High-impact exercise was beneficial to bones. LS and FN BMC was higher in gymnasts than in controls during the follow-up. Reduction in physical activity had negative effects on bone mass. LS and FN BMC increased less in the group having reduced their physical activity more than 50%, compared with those continuing at the previous level (1.69 g, p=0.021; 0.14 g, p=0.015, respectively). The amount of physical activity was the only significant parameter accounting for the calcaneal sonography measurements at 6-year follow-up (11.3%) and reduced activity level was associated with lower sonographic values. Long-term low-dose EPC use seemed to prevent normal bone mass acquisition. There was a significant trend towards a smaller increase in LS and FN BMC among long-term EPC users. In conclusion, this study confirms that high-impact exercise is beneficial to bones and that the benefits are partly maintained even after a clear reduction in training level at least for 4 years. Continued exercise is needed to retain all acquired benefits. The bone mass gained and maintained can possibly be maximized in adolescence by implementing high-impact exercise for youngsters. The peak bone mass of the young women participating in the study may be reached before the age of 20. Use of low-dose EPCs seems to suppress normal bone mass acquisition.

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The aim of this study was to analyze the effect of muscle fatigue in active and inactive young adults on the kinematic and kinetic parameters of normal gait and obstacle crossing. Twenty male subjects were divided into active (10) and inactive (10), based on self-reported physical activity. Participants performed three trials of two tasks (normal gait and obstacle crossing) before and after a fatigue protocol, consisting of repeated sit-to-stand transfers until the instructed pace could no longer be maintained. MANOVAs were used to compare dependent variables with the following factors: physical activity level, fatigue and task. The endurance time in the fatigue protocol was lower for the inactive group. Changes of gait parameters with fatigue, among which increased step width and increased stride speed were the most consistent, were independent of task and physical activity level. These findings indicate that the kinematic and kinetic parameters of gait are affected by muscle fatigue irrespective of the physical activity level of the subjects and type of gait. Inactive individuals used a slightly different strategy than active individuals when crossing an obstacle, independently of muscle fatigue. © 2013.

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Appropriate measures of physical activity are essential for determining the population prevalence of physical activity, for tracking trends over time, and for guiding intervention efforts. Physical activity measurement is characterised by the synthesis of information on the type, frequency, intensity, and duration of activity over a specified period. To date, emphasis in physical activity assessment has been on the measurement of leisure time physical activities. However, some domestic and transport related activities entail energy expenditures equivalent to moderate intensity of 3.0–6.0 METS1 considered to be of sufficient intensity to achieve a health benefit are yet to be included in routine population level physical activity surveillance. This leads to population estimates based only on measures of leisure time physical activities.

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Abstract Background: Acute coronary syndrome (ACS) is one of the main causes of morbidity and mortality in the modern world. A sedentary lifestyle, present in 85% of the Brazilian population, is considered a risk factor for the development of coronary artery disease. However, the correlation of a sedentary lifestyle with cardiovascular events (CVE) during hospitalization for ACS is not well established. Objective: To evaluate the association between physical activity level, assessed with the International Physical Activity Questionnaire (IPAQ), with in-hospital prognosis in patients with ACS. Methods: Observational, cross-sectional, and analytical study with 215 subjects with a diagnosis of ACS consecutively admitted to a referral hospital for cardiac patients between July 2009 and February 2011. All volunteers answered the short version of the IPAQ and were observed for the occurrence of CVE during hospitalization with a standardized assessment conducted by the researcher and corroborated by data from medical records. Results: The patients were admitted with diagnoses of unstable angina (34.4%), acute myocardial infarction (AMI) without ST elevation (41.4%), and AMI with ST elevation (24.2%). According to the level of physical activity, the patients were classified as non-active (56.3%) and active (43.7%). A CVE occurred in 35.3% of the cohort. The occurrence of in-hospital complications was associated with the length of hospital stay (odds ratio [OR] = 1.15) and physical inactivity (OR = 2.54), and was independent of age, systolic blood pressure, and prior congestive heart failure. Conclusion: A physically active lifestyle reduces the risk of CVE during hospitalization in patients with ACS.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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This study, which involved a target population comprised by 292 workers of different industrial areas (metalmechanics, foundry, chemical, wood, food), aimed to verify the association between energy expenditure-EE, physical activity level-PAL and body composition (Body Mass Index-BMI, Waist-Hip Ratio-WHR and Waist To Height Ratio, WTHR) of participants. The work was completed with the description of the variables relating to the gender of the individuals (male and female) and the activities carried out in the two sectors of industrial work (administrative sector and productive sector). In this research, the statistical technique of principal components analysis (PCA) and the hierarchical analysis of clusters (HCA) were used. Sociodemographic and anthropometric data were collected as well as the level of physical activity and energy expenditure were assessed. The vast majority of individuals who spend greater energy expenditure and has more intense physical activity were male. Most of these workers are in the production sector. We can confirm that that both, gender and labor activity, are factors that have influence on the EE and the PAL.

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The number of physical activity measures and indexes used in the human literature is large and may result in some difficulty for the average investigator to choose the most appropriate measure. Accordingly, this review is intended to provide information on the utility and limitations of the various measures. Its primary focus is the objective assessment of free-living physical activity in humans based on physiological and biomechanical methods. The physical activity measures have been classified into three categories: Measures based on energy expenditure or oxygen uptake, such as activity energy expenditure, activity-related time equivalent, physical activity level, physical activity ratio, metabolic equivalent, and a new index of potential interest, daytime physical activity level. Measures based on heart rate monitoring, such as net heart rate, physical activity ratio heart rate, physical activity level heart rate, activity-related time equivalent, and daytime physical activity level heart rate. Measures based on whole-body accelerometry (counts/U time). Quantification of the velocity and duration of displacement in outdoor conditions by satellites using the Differential Global Positioning System may constitute a surrogate for physical activity, because walking is the primary activity of man in free-living conditions. A general outline of the measures and indexes described above is presented in tabular form, along with their respective definition, usual applications, advantages, and shortcomings. A practical example is given with typical values in obese and non-obese subjects. The various factors to be considered in the selection of physical activity methods include experimental goals, sample size, budget, cultural and social/environmental factors, physical burden for the subject, and statistical factors, such as accuracy and precision. It is concluded that no single current technique is able to quantify all aspects of physical activity under free-living conditions, requiring the use of complementary methods. In the future, physical activity sensors, which are of low-cost, small-sized, and convenient for subjects, investigators, and clinicians, are needed to reliably monitor, during extended periods in free-living situations, small changes in movements and grade as well as duration and intensity of typical physical activities.

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BACKGROUND: The assessment of physical activity and energy expenditure is relevant to the care of maintenance haemodialysis (MHD) patients. In the current study, we aimed to evaluate measurements of physical activity and energy expenditure in MHD patients from different centres and countries and explored the predictors of physical activity in these patients.¦METHODS: In this cross-sectional multicentre study, 134 MHD patients from four countries (France, Switzerland, Sweden and Brazil) were included. The physical activity was evaluated for 5.0 ± 1.4 days (mean ± SD) by a multisensory device (SenseWear Armband) and comprised the assessment of number of steps per day, activity-related energy expenditure (activity-related EE) and physical activity level (PAL).¦RESULTS: The number of steps per day, activity-related EE and PAL from the MHD patients were compatible with a sedentary lifestyle. In addition, all parameters were significantly lower in dialysis days when compared to non-dialysis days (P < 0.001). The multivariate regression analysis revealed that diabetes and higher body mass index (BMI) predicted a lower PAL and older age and diabetes predicted a reduced number of steps.¦CONCLUSIONS: The physical activity parameters of MHD patients were compatible with a sedentary lifestyle. This inactivity was worsened by aging, diabetes and higher BMI. Our results indicate that MHD patients should be encouraged by the health care team to increase their physical activity.

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Affiliation: J. O'Loughlin: Department of Social and Preventive Medicine, Centre de recherche CHUM, Université de Montréal

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Background: The high prevalence of physical inactivity worldwide calls for innovative and more effective ways to promote physical activity (PA). There are limited objective data on the effectiveness of Web-based personalized feedback on increasing PA in adults. Objective: It is hypothesized that providing personalized advice based on PA measured objectively alongside diet, phenotype, or genotype information would lead to larger and more sustained changes in PA, compared with nonpersonalized advice. Methods: A total of 1607 adults in seven European countries were randomized to either a control group (nonpersonalized advice, Level 0, L0) or to one of three personalized groups receiving personalized advice via the Internet based on current PA plus diet (Level 1, L1), PA plus diet and phenotype (Level 2, L2), or PA plus diet, phenotype, and genotype (Level 3, L3). PA was measured for 6 months using triaxial accelerometers, and self-reported using the Baecke questionnaire. Outcomes were objective and self-reported PA after 3 and 6 months. Results: While 1270 participants (85.81% of 1480 actual starters) completed the 6-month trial, 1233 (83.31%) self-reported PA at both baseline and month 6, but only 730 (49.32%) had sufficient objective PA data at both time points. For the total cohort after 6 months, a greater improvement in self-reported total PA (P=.02) and PA during leisure (nonsport) (P=.03) was observed in personalized groups compared with the control group. For individuals advised to increase PA, we also observed greater improvements in those two self-reported indices (P=.006 and P=.008, respectively) with increased personalization of the advice (L2 and L3 vs L1). However, there were no significant differences in accelerometer results between personalized and control groups, and no significant effect of adding phenotypic or genotypic information to the tailored feedback at month 3 or 6. After 6 months, there were small but significant improvements in the objectively measured physical activity level (P<.05), moderate PA (P<.01), and sedentary time (P<.001) for individuals advised to increase PA, but these changes were similar across all groups. Conclusions: Different levels of personalization produced similar small changes in objective PA. We found no evidence that personalized advice is more effective than conventional “one size fits all” guidelines to promote changes in PA in our Web-based intervention when PA was measured objectively. Based on self-reports, PA increased to a greater extent with more personalized advice. Thus, it is crucial to measure PA objectively in any PA intervention study.