966 resultados para Stewart, Margaret
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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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Parents and 531 students (46% males, 78% white) completed equivalent questionnaires. Agreement between student and parent responses to questions about hypothesized physical activity (PA) correlates was assessed. Relationships between hypothesized correlates and an objective measure of student's moderate-to-vigorous physical activity (MVPA) in a subset of 177 students were also investigated. Agreement between student and parent ranged from r = .34 to .64 for PA correlates. Spearman correlations between MVPA and PA correlates ranged from –.04 to .21 for student report and –.14 to .32 for parent report, and there were no statistical differences for 8 out of 9 correlations between parent and student. Parents can provide useful data on PA correlates for students in Grades 7–12.
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The purpose of this study was to determine the extent to which sport education can provide students with sufficient opportunities for developing moderate- to-vigorous physical activity (MVPA). Nineteen seventh-grade boys (average age = 12.9 yrs.) participated in a 22-lesson season of floor hockey. For all students (both higher and lower skilled), students averaged a total of 31.6 min of MVPA during the season, or 63.2% of lesson time. Further, there was no significant difference according to skill level (33.4 min [Higher] vs. 30.4 min [Lower]), nor were there any significant differences in MVPA levels across the phases of the season.
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The purpose of this study was to document the level of physical activity and sedentary behavior in a representative sample of Singaporean adolescents. A random sample of 1,827 secondary school students from six secondary schools (929 boys, 898 girls, mean age 14.9 +/- 1.2 yr) completed the Three-Day Physical Activity Recall (3DPAR) self-report instrument. Approximately 63% of Singaporean high school students met current guidelines requiring 60 min of moderate to vigorous physical activity daily. Just over half (51.6%) met the guideline calling for regular vigorous physical activity. Across all grade levels, boys were consistently more active than girls. More than 70% of Singaporean high school students exceeded the recommended 2 hours per day of electronic media use. Collectively, these findings suggest that a significant proportion of Singaporean adolescents are not sufficiently active and are in need of programs to promote physical activity and decrease sedentary behavior.
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The unique physical and movement characteristics of children necessitate the development of accelerometer equations and cut points that are population specific. The purpose of this study is to develop an ecologically valid cut point for the Biotrainer Pro monitor that reflects a threshold for moderate-intensity physical activity in elementary school children. A sample of 30 children (ages 8-12) wore a Biotrainer monitor while completing a series of 7 movement tasks (calibration phase) and while participating in an organized group activity (cross-validation phase). Videotapes from each session were processed using a computerized direct-observation technique to provide a criterion measure of physical activity. Analyses involved the use of mixed-model regression and receiver operator characteristic (ROC) curves. The results indicated that a cut point of 4 counts/min provides the optimal balance between the related needs for sensitivity (accurately detecting activity) and specificity (limiting misclassification of activity as inactivity). Results with the cross-validation data demonstrated that this value yielded the best overall kappa (.58) and a high classification agreement (84%) for activity determination. The specificity of 93% demonstrates that the proposed cut point can accurately detect activity; however, the lower sensitivity value of 61% suggests that some minutes of activity might be incorrectly classified as inactivity. The cut point of 4 counts/min provides an ecologically valid cut point to capture physical activity in children using the Biotrainer Pro activity monitor.
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This study evaluated the validity of the Previous Day Physical Activity Recall (PDPAR) self-report instrument in quantifying after-school physical activity behavior in fifth-grade children. Thirty-eight fifth-grade students (mean age, 10.8 +/- 0.1; 52.6% female; 26.3% African American) from two urban elementary schools completed the PDPAR after wearing a CSA WAM 7164 accelerometer for a day. The mean within-subject correlation between self-reported MET level and total counts for each 30-min block was 0.57 (95% C.I., 0.51-0.62). Self-reported mean MET level during the after-school period and the number of 30-min blocks with activity rated at greater than or equal to 6 METs were significantly correlated with the CSA outcome variables. Validity coefficients for these variables ranged from 0.35 to 0.43 (p <.05). Correlations between the number of 30-min blocks with activity rated at greater than or equal to 3 METs and the CSA variables were positive but failed to reach statistical significance (r = 0.19-0.23). The PDPAR provides moderately valid estimates of relative participation in vigorous activity and mean MET level in fifth-grade children. Caution should be exercised when using the PDPAR to quantify moderate physical activity in preadolescent children.
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Objective To determine if a clinic-based behavioral intervention program for low-income mid-life women that emphasizes use of community resources will increase moderate intensity physical activity (PA) and improve dietary intake. Methods Randomized trial conducted from May 2003 to December 2004 at one community health center in Wilmington, NC. A total of 236 women, ages 40–64, were randomized to receive an Enhanced Intervention (EI) or Minimal Intervention (MI). The EI consisted of an intensive phase (6 months) including 2 individual counseling sessions, 3 group sessions, and 3 phone calls from a peer counselor followed by a maintenance phase (6 months) including 1 individual counseling session and 7 monthly peer counselor calls. Both phases included efforts to increase participants' use of community resources that promote positive lifestyle change. The MI consisted of a one-time mailing of pamphlets on diet and PA. Outcomes, measured at 6 and 12 months, included the comparison of moderate intensity PA between study groups as assessed by accelerometer (primary outcome) and questionnaire, and dietary intake assessed by questionnaire and serum carotenoids (6 months only). Results For accelerometer outcomes, follow-up was 75% at 6 months and 73% at 12 months. Though moderate intensity PA increased in the EI and decreased in the MI, the difference between groups was not statistically significant (p = 0.45; multivariate model, p = 0.08); however, moderate intensity PA assessed by questionnaire (92% follow-up at 6 months and 75% at 12 months) was greater in the EI (p = 0.01; multivariate model, p = 0.001). For dietary outcomes, follow-up was 90% for questionnaire and 92% for serum carotenoids at 6 months and 74% for questionnaire at 12 months. Dietary intake improved more in the EI compared to the MI (questionnaire at 6 and 12 months, p < 0.001; serum carotenoid index, p = 0.05; multivariate model, p = 0.03). Conclusion The EI did not improve objectively measured PA, but was associated with improved self-reported and objective measures of dietary intake.
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Objective To evaluate a conceptual model linking parent physical activity (PA) orientations, parental support for PA, and PA behavior in preschool children. Methods Participants were 156 parent-child dyads from 13 child care centers in Queensland, Australia. Parents completed a questionnaire measuring parental PA, parental enjoyment of PA, perceived importance of PA, parental support for PA, parents' perceptions of competence, and child PA at home. MVPA while attending child care was measured via accelerometry. Data were collected between May and August of 2003. The relationships between the study variables and child PA were tested using observed variable path analysis. Results Parental PA and parents' perceptions of competence were positively associated with parental support for PA (β= 0.23 and 0.18, respectively, p<0.05). Parental support, in turn, was positively associated with child PA at home (β= 0.16, p<0.05), but not at child care (β= 0.01, p= 0.94). Parents' perceptions of competence was positively associated with both home-based and child care PA (β= 0.20 and 0.28, respectively, p<0.05). Conclusions Family-based interventions targeting preschoolers should include strategies to increase parental support for PA. Parents who perceive their child to have low physical competence should be encouraged to provide adequate support for PA. © 2009 Elsevier Inc.
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Background This study evaluated the feasibility and preliminary efficacy of a church-based intervention to promote physical activity (PA) in children. Methods The study was conducted in 4 churches located in 2 large metropolitan areas and 2 regional towns in Kansas. Churches in the intervention condition implemented the "Shining Like Stars" physical activity curriculum module during their regularly scheduled Sunday school classes. Churches in the control condition delivered the same content without integrating physical activity into the lessons. In addition to the curriculum, the intervention churches completed a series of weekly family devotional activities designed to promote parental support for PA and increase PA outside of Sunday school. Results Children completing the Shining Like Stars curriculum exhibited significantly greater amounts of MVPA than those in the control condition (20 steps/min vs. 7 steps/min). No intervention effects were observed for PA levels outside of Sunday school or parental support for PA; however, relative to controls, children in the intervention churches did exhibit a significant reduction in screen time. Conclusion The findings confirm that the integration of physical activity into Sunday school is feasible and a potentially effective strategy for promoting PA in young children.
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Background The purposes of this study were 1) to establish accelerometer count cutoffs to categorize activity intensity of 3 to 5-y old-children and 2) to evaluate the accelerometer as a measure of children’s physical activity in preschool settings. Methods While wearing an ActiGraph accelerometer, 16 preschool children performed five, 3-min structured activities. Receiver Operating Characteristic (ROC) curve analyses identified count cutoffs for four physical activity intensities. In 9 preschools, 281 children wore an ActiGraph during observations performed by three trained observers (interobserver reli-ability = 0.91 to 0.98). Results Separate count cutoffs for 3, 4, and 5-y olds were established. Sensitivity and specificity for the count cutoffs ranged from 86.7% to 100.0% and 66.7% to 100.0%, respectively. ActiGraph counts/15 s were different among all activities (P < 0.05) except the two sitting activities. Correlations between observed and ActiGraph intensity categorizations at the preschools ranged from 0.46 to 0.70 (P < 0.001). Conclusions The ActiGraph count cutoffs established and validated in this study can be used to objectively categorize the time that preschool-age children spend in different physical activity intensity levels.