986 resultados para 204-1249


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The absence of comparative validity studies has prevented researchers from reaching consensus regarding the application of intensity-related accelerometer cut points for children and adolescents. PURPOSE This study aimed to evaluate the classification accuracy of five sets of independently developed ActiGraph cut points using energy expenditure, measured by indirect calorimetry, as a criterion reference standard. METHODS A total of 206 participants between the ages of 5 and 15 yr completed 12 standardized activity trials. Trials consisted of sedentary activities (lying down, writing, computer game), lifestyle activities (sweeping, laundry, throw and catch, aerobics, basketball), and ambulatory activities (comfortable walk, brisk walk, brisk treadmill walk, running). During each trial, participants wore an ActiGraph GT1M, and VO 2 was measured breath-by-breath using the Oxycon Mobile portable metabolic system. Physical activity intensity was estimated using five independently developed cut points: Freedson/Trost (FT), Puyau (PU), Treuth (TR), Mattocks (MT), and Evenson (EV). Classification accuracy was evaluated via weighted κ statistics and area under the receiver operating characteristic curve (ROC-AUC). RESULTS Across all four intensity levels, the EV (κ = 0.68) and FT (κ = 0.66) cut points exhibited significantly better agreement than TR (κ = 0.62), MT (κ = 0.54), and PU (κ = 0.36). The EV and FT cut points exhibited significantly better classification accuracy for moderate-to vigorous-intensity physical activity (ROC-AUC = 0.90) than TR, PU, or MT cut points (ROC-AUC = 0.77-0.85). Only the EV cut points provided acceptable classification accuracy for all four levels of physical activity intensity and performed well among children of all ages. The widely applied sedentary cut point of 100 counts per minute exhibited excellent classification accuracy (ROC-AUC = 0.90). CONCLUSIONS On the basis of these findings, we recommend that researchers use the EV ActiGraph cut points to estimate time spent in sedentary, light-, moderate-, and vigorous-intensity activity in children and adolescents. Copyright © 2011 by the American College of Sports Medicine.

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Purpose To describe the physical activity (PA) levels of children attending after-school programs, 2) examine PA levels in specific after-school sessions and activity contexts, and 3) evaluate after-school PA differences in groups defined by sex and weight status. Methods One hundred forty-seven students in grades 3-6 (mean age: 10.1 +/- 0.7, 54.4% male, 16.5% overweight (OW), 22.8% at-risk for OW) from seven after-school programs in the midwestern United States wore Actigraph GT1M accelerometers for the duration of their attendance to the program. PA was objectively assessed on six occasions during an academic year (three fall and three spring). Stored activity counts were uploaded to a customized data-reduction program to determine minutes of sedentary (SED), light (LPA), moderate (MPA), vigorous (VPA), and moderate-to-vigorous (MVPA) physical activity. Time spent in each intensity category was calculated for the duration of program attendance, as well as specific after-school sessions (e.g., free play, snack time). Results On average, participants exhibited 42.6 min of SED, 40.8 min of LPA, 13.4 min of MPA, and 5.3 min of VPA. The average accumulation of MVPA was 20.3 min. Boys exhibited higher levels of MPA, VPA, and MVPA, and lower levels of SED and LPA, than girls. OW and at-risk-for-OW students exhibited significantly less VPA than nonoverweight students, but similar levels of LPA, MPA, and MVPA. MVPA levels were significantly higher during free-play activity sessions than during organized or structured activity sessions. Conclusion After-school programs seem to be an important contributor to the PA of attending children. Nevertheless, ample room for improvement exists by making better use of existing time devoted to physical activity.

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Child care centers differ systematically with respect to the quality and quantity of physical activity they provide, suggesting that center-level policies and practices, as well as the center's physical environment, are important influences on children's physical activity behavior. Purpose To summarize and critically evaluate the extant peer-reviewed literature on the influence of child care policy and environment on physical activity in preschool-aged children. Methods A computer database search identified seven relevant studies that were categorized into three broad areas: cross-sectional studies investigating the impact of selected center-level policies and practices on moderate-to-vigorous physical activity (MVPA), studies correlating specific attributes of the outdoor play environment with the level and intensity of MVPA, and studies in which a specific center-level policy or environmental attribute was experimentally manipulated and evaluated for changes in MVPA. Results Staff education and training, as well as staff behavior on the playground, seem to be salient influences on MVPA in preschoolers. Lower playground density (less children per square meter) and the presence of vegetation and open play areas also seem to be positive influences on MVPA. However, not all studies found these attributes to be significant. The availability and quality of portable play equipment, not the amount or type of fixed play equipment, significantly influenced MVPA levels. Conclusions Emerging evidence suggests that several policy and environmental factors contribute to the marked between-center variability in physical activity and sedentary behavior. Intervention studies targeting these factors are thus warranted.

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Purpose This Study evaluated the predictive validity of three previously published ActiGraph energy expenditure (EE) prediction equations developed for children and adolescents. Methods A total of 45 healthy children and adolescents (mean age: 13.7 +/- 2.6 yr) completed four 5-min activity trials (normal walking. brisk walking, easy running, and fast running) in ail indoor exercise facility. During each trial, participants were all ActiGraph accelerometer oil the right hip. EE was monitored breath by breath using the Cosmed K4b(2) portable indirect calorimetry system. Differences and associations between measured and predicted EE were assessed using dependent t-tests and Pearson correlations, respectively. Classification accuracy was assessed using percent agreement, sensitivity, specificity, and area under the receiver operating characteristic (ROC) curve. Results None of the equations accurately predicted mean energy expenditure during each of the four activity trials. Each equation, however, accurately predicted mean EE in at least one activity trial. The Puyau equation accurately predicted EE during slow walking. The Trost equation accurately predicted EE during slow running. The Freedson equation accurately predicted EE during fast running. None of the three equations accurately predicted EE during brisk walking. The equations exhibited fair to excellent classification accuracy with respect to activity intensity. with the Trost equation exhibiting the highest classification accuracy and the Puyau equation exhibiting the lowest. Conclusions These data suggest that the three accelerometer prediction equations do not accurately predict EE on a minute-by-minute basis in children and adolescents during overground walking and running. The equations maybe, however, for estimating participation in moderate and vigorous activity.

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Previous studies have demonstrated that pattern recognition approaches to accelerometer data reduction are feasible and moderately accurate in classifying activity type in children. Whether pattern recognition techniques can be used to provide valid estimates of physical activity (PA) energy expenditure in youth remains unexplored in the research literature. Purpose: The objective of this study is to develop and test artificial neural networks (ANNs) to predict PA type and energy expenditure (PAEE) from processed accelerometer data collected in children and adolescents. Methods: One hundred participants between the ages of 5 and 15 yr completed 12 activity trials that were categorized into five PA types: sedentary, walking, running, light-intensity household activities or games, and moderate-to-vigorous intensity games or sports. During each trial, participants wore an ActiGraph GTIM on the right hip, and (V) Over dotO(2) was measured using the Oxycon Mobile (Viasys Healthcare, Yorba Linda, CA) portable metabolic system. ANNs to predict PA type and PAEE (METs) were developed using the following features: 10th, 25th, 50th, 75th, and 90th percentiles and the lag one autocorrelation. To determine the highest time resolution achievable, we extracted features from 10-, 15-, 20-, 30-, and 60-s windows. Accuracy was assessed by calculating the percentage of windows correctly classified and root mean square en-or (RMSE). Results: As window size increased from 10 to 60 s, accuracy for the PA-type ANN increased from 81.3% to 88.4%. RMSE for the MET prediction ANN decreased from 1.1 METs to 0.9 METs. At any given window size, RMSE values for the MET prediction ANN were 30-40% lower than the conventional regression-based approaches. Conclusions: ANNs can be used to predict both PA type and PAEE in children and adolescents using count data from a single waist mounted accelerometer.

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Purpose To evaluate the validity of a uniaxial accelerometer (MTI Actigraph) for measuring physical activity in people with acquired brain injury (ABI) using portable indirect calorimetry (Cosmed K4b(2)) as a criterion measure. Methods Fourteen people with ABI and related gait pattern impairment (age 32 +/- 8 yr) wore an MTI Actigraph that measured activity (counts(.)min-(1)) and a Cosmed K4b(2) that measured oxygen consumption (mL(.)kg(-1.)min(-1)) during four activities: quiet sitting (QS) and comfortable paced (CP), brisk paced (BP), and fast paced (FP) walking. MET levels were predicted from Actigraph counts using a published equation and compared with Cosmed measures. Predicted METs for each of the 56 activity bouts (14 participants X 4 bouts) were classified (light, moderate, vigorous, or very vigorous intensity) and compared with Cosmed-based classifications. Results Repeated-measures ANOVA indicated that walking condition intensities were significantly different (P < 0.05) and the Actigraph detected the differences. Overall correlation between measured and predicted METs was positive, moderate, and significant (r = 0.74). Mean predicted METs were not significantly different from measured for CP and BP, but for FP walking, predicted METs were significantly less than measured (P < 0.05). The Actigraph correctly classified intensity for 76.8% of all activity bouts and 91.5% of light- and moderate-intensity bouts. Conclusions Actigraph counts provide a valid index of activity across the intensities investigated in this study. For light to moderate activity, Actigraph-based estimates of METs are acceptable for group-level analysis and are a valid means of classifying activity intensity. The Actigraph significantly underestimated higher intensity activity, although, in practice, this limitation will have minimal impact on activity measurement of most community-dwelling people with ABI.

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PURPOSE To examine correlates and consequences of parents' encouragement of girls' physical activity (PA) for weight loss (ENCLOSS). METHODS Data were collected for 181 girls, mothers and fathers when girls were 9, 11, and 13 years old. Mothers and fathers completed a self-report questionnaire of ENCLOSS (e.g., “I have talked to my daughter about how to exercise to lose weight”). Correlates of ENCLOSS that were assessed include girls' Body Mass Index (BMI) z-score and parents' modeling of and logistic support for PA. Dependent variables assessed at age 13 include girls' self-reported and objectively-measured PA, enjoyment of physical activity, and weight concerns. Associations between ENCLOSS, girls' BMI, and parent's support for PA were assessed using spearman rank correlations. To examine links between ENCLOSS and the outcome variables, scores for ENCLOSS were divided into tertiles at each age. Three groups were created including girls who were in the highest tertile at each age (high ENCLOSS), girls who were in the lowest tertile at each age (low ENCLOSS), and girls who varied in their tertile ranking (mid ENCLOSS). Group differences in the outcome variables were assessed using regression analysis (referent group: low ENCLOSS), controlling for girls' BMI and the outcome variable at age 9. RESULTS Girls' with higher BMI had mothers and fathers who reported higher ENCLOSS (r = .61-. 69, p<. 0001). Parents'reports of ENCLOSS were not associated with modeling of or logistic support for PA. Girls in the high ENCLOSS group reported significantly lower enjoyment of PA and higher weight concerns at age 13, independent of covariates. No differences in PA were noted. CONCLUSION Parents who encourage their daughters to be active for weight loss do not model PA or facilitate girls' PA. Persistent encouragement of PA for weight loss may lead to low enjoyment of PA and higher weight concerns among adolescent girls.

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Obesity rates are increasing in children of all ages, and reduced physical activity (PA) is a likely contributor to this trend. Little is known about the physical activity behavior of preschool-age children, or about the influence of preschool attendance on physical activity. Purpose The purpose of this study was to quantify the physical activity levels of children attending a center-based half-day preschool program. Methods Forty-two 3-to-5-year old children (Mean age = 4.0 ± 0.7, 54.8% Male, Mean BMI = 16.5 ± 5.5, Mean BMI %tile = 52.1 ± 33.5) from four class groups (two morning and two afternoon), wore an Actigraph 7164 accelerometer for the entire halfday program (including classroom learning experiences, snack and recess time) 2 times per week, for 10 weeks (20 activity monitoring records in total). Activity counts for each 5-sec interval were uploaded to a customized data reduction program to determine total counts, minutes of moderate PA (MPA) (3–5.9 METs), and minutes of vigorous PA (VPA) (> = 6 METs) per session. Counts were categorized as either MPA or VPA using the cutpoints developed by Sirard and colleagues (2001). Results Across the four 2.5 hour programs, the average MPA, VPA and total counts (× 103) were 12.4 ± 3.1 minutes, 18.3 ± 4.6 minutes, and 171.1 ± 29.7 counts, respectively. Thus, on average, children accumulated just over 12 minutes of moderateto-vigorous PA per hour of program attendance. The PA variables did not differ significantly by gender, weight status, or time of day. There were, however, significant age differences, with 3-year-olds exhibiting significantly less PA than their 4- and 5-year-old counterparts. Conclusions These results suggest that young children are relatively lowactive while attending preschool. Accordingly, interventions to increase movement opportunities during the preschool day are warranted.

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Fatty acid methyl ester (FAME) profiles, together with Biolog substrate utilization patterns, were used in conjunction with measurements of other soil chemical and microbiological properties to describe differences in soil microbial communities induced by increased salinity and alkalinity in grass/legume pastures at three sites in SE South Australia. Total ester-linked FAMEs (EL-FAMEs) and phospholipid-linked FAMEs (PL-FAMEs), were also compared for their ability to detect differences between the soil microbial communities. The level of salinity and alkalinity in affected areas of the pastures showed seasonal variation, being greater in summer than in winter. At the time of sampling for the chemical and microbiological measurements (winter) only the affected soil at site 1 was significantly saline. The affected soils at all three sites had lower organic C and total N concentrations than the corresponding non-affected soils. At site 1 microbial biomass, CO 2-C respiration and the rate of cellulose decomposition was also lower in the affected soil compared to the non-affected soil. Biomarker fatty acids present in both the EL- and PL-FAME profiles indicated a lower ratio of fungal to bacterial fatty acids in the saline affected soil at site 1. Analysis of Biolog substrate utilization patterns indicated that the bacterial community in the affected soil at site 1 utilized fewer carbon substrates and had lower functional diversity than the corresponding community in the non-affected soil. In contrast, increased alkalinity, of major importance at sites 2 and 3, had no effect on microbial biomass, the rate of cellulose decomposition or functional diversity but was associated with significant differences in the relative amounts of several fatty acids in the PL-FAME profiles indicative of a shift towards a bacterial dominated community. Despite differences in the number and relative amounts of fatty acids detected, principal component analysis of the EL- and PL-FAME profiles were equally capable of separating the affected and non-affected soils at all three sites. Redundancy analysis of the FAME data showed that organic C, microbial biomass, electrical conductivity and bicarbonate-extractable P were significantly correlated with variation in the EL-FAME profiles, whereas pH, electrical conductivity, NH 4-N, CO 2-C respiration and the microbial quotient were significantly correlated with variation in the PL-FAME profiles. Redundancy analysis of the Biolog data indicated that cation exchange capacity and bicarbonate-extractable K were significantly correlated with the variation in Biolog substrate utilization patterns.

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This article critically analyses the provisions by which a caveat against dealings may be cleared from a land title in Queensland, namely ss 126, 127 and 128 of the Land Title Act 1994(Qld). It includes a comparison of the current provisions with the pre-existing law and provides a comprehensive guide as to the circumstances in which, and the manner by which, the current provisions may be utilised to clear caveats from land titles in Queensland.

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Purpose This study explores recent claims that humans exhibit a minimum cost of transport (CoTmin) for running which occurs at an intermediate speed, and assesses individual physiological, gait and training characteristics. Methods Twelve healthy participants with varying levels of fitness and running experience ran on a treadmill at six self-selected speeds in a discontinuous protocol over three sessions. Running speed (km[middle dot]hr-1), V[spacing dot above]O2 (mL[middle dot]kg-1[middle dot]km-1), CoT (kcal[middle dot]km-1), heart rate (beats[middle dot]min-1) and cadence (steps[middle dot]min-1) were continuously measured. V[spacing dot above]O2 max was measured on a fourth testing session. The occurrence of a CoTmin was investigated and its presence or absence examined with respect to fitness, gait and training characteristics. Results Five participants showed a clear CoTmin at an intermediate speed and a statistically significant (p < 0.05) quadratic CoT-speed function, while the other participants did not show such evidence. Participants were then categorized and compared with respect to the strength of evidence for a CoTmin (ClearCoTmin and NoCoTmin). The ClearCoTmin group displayed significantly higher correlation between speed and cadence; more endurance training and exercise sessions per week; than the NoCoTmin group; and a marginally non-significant but higher aerobic capacity. Some runners still showed a CoTmin at an intermediate speed even after subtraction of resting energy expenditure. Conclusion The findings confirm the existence of an optimal speed for human running, in some but not all participants. Those exhibiting a COTmin undertook a higher volume of running, ran with a cadence that was more consistently modulated with speed, and tended to be aerobically fitter. The ability to minimise the energetic cost of transport appears not to be ubiquitous feature of human running but may emerge in some individuals with extensive running experience.

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The relationship between small firm growth and HRM practices Rowena Barrett, Susan Mayson and Niel Warriner Introduction In this chapter we explore the relationship between small firms’ growth orientation, their business planning efforts and the role the owner plays and whether or not formal HRM practices are used. Formal HRM practices are assessed in terms of whether they are written down, regularly applied or assured to take place. We take on board Heneman et al.’s (2000) suggestion that ‘surveys of employer practices across SMEs [would] be [a] valuable addition to the strategic human resource management literature’ (p. 23) and report the results of an online and paper survey of a sample of 1753 small firms (defined as those employing less than 20 people) in the state of Victoria (SE Australia). Our particular interest in this chapter, which is based on an analysis of 410 responses to the survey, is whether growthoriented small firms adopt formal HRM practices. This research contributes to understanding whether more formal organizational systems and routines are more likely to be used (or not) to nurture human capital in growth-oriented small firms. Moreover by focusing on firm growth, this chapter, consistent with recent calls in the literature (see Baron, 2003; Barrett and Mayson, 2006; Katz et al., 2000; Tansky and Heneman, 2003), contributes to a better understanding of issues at the intersection of entrepreneurship and HRM research.

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Purpose Is eccentric hamstring strength and between limb imbalance in eccentric strength, measured during the Nordic hamstring exercise, a risk factor for hamstring strain injury (HSI)? Methods Elite Australian footballers (n=210) from five different teams participated. Eccentric hamstring strength during the Nordic was taken at the commencement and conclusion of preseason training and in season. Injury history and demographic data were also collected. Reports on prospectively occurring HSIs were completed by team medical staff. Relative risk (RR) was determined for univariate data and logistic regression was employed for multivariate data. Results Twenty-eight HSIs were recorded. Eccentric hamstring strength below 256N at the start of preseason and 279N at the end of preseason increased risk of future HSI 2.7 (relative risk, 2.7; 95% confidence interval, 1.3 to 5.5; p = 0.006) and 4.3 fold (relative risk, 4.3; 95% confidence interval, 1.7 to 11.0; p = 0.002) respectively. Between limb imbalance in strength of greater than 10% did not increase the risk of future HSI. Univariate analysis did not reveal a significantly greater relative risk for future HSI in athletes who had sustained a lower limb injury of any kind within the last 12 months. Logistic regression revealed interactions between both athlete age and history of HSI with eccentric hamstring strength, whereby the likelihood of future HSI in older athletes or athletes with a history of HSI was reduced if an athlete had high levels of eccentric strength. Conclusion Low levels of eccentric hamstring strength increased the risk of future HSI. Interaction effects suggest that the additional risk of future HSI associated with advancing age or previous injury was mitigated by higher levels of eccentric hamstring strength.