64 resultados para ACTIGRAPH


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A new accelerometer, the Kenz Lifecorder EX (LC; Suzuken Co. Ltd, Nagoya, Japan), offers promise as a feasible monitor alternative to the commonly used Actigraph (AG: Actigraph LLC, Fort Walton Beach, FL). Purpose: This study compared the LC and AG accelerometers and the Yamax SW-200 pedometer (DW) under free-living conditions with regard to children's steps taken and time in light-intensity physical activity (PA) and moderate to vigorous PA (MVPA). Methods: Participants (N = 31, age = 10.2 ± 0.4 yr) wore LC, AG, and DW monitors from arrival at school (7:45 a.m.) until they went to bed. Time in light and MVPA intensities were calculated using two separate intensity classifications for the LC (LC_4 and LC_5) and four classifications for the AG (AG_Treuth, AG_Puyau, AG_Trost, and AG_Freedson). Both accelerometers provided steps as outputs. DW steps were self-recorded. Repeated-measures ANOVA was used to assess overlapping monitor outputs. Results: There was no difference between DW and LC steps (Δ = 200 steps), but a nonsignificant trend was observed in the pairwise comparison between DW and AG steps (Δ = 1001 steps, P = 0.058). AG detected significantly greater steps than the LC (Δ = 801 steps, P = 0.001). Estimates of light-intensity activity minutes ranged from a low of 75.6 ± 18.4 min (LC_4) to a high of 309 ± 69.2 min (AG_Treuth). Estimates of MVPA minutes ranged from a low of 25.9 ± 9.4 min (LC_5) to a high of 112.2 ± 34.5 min (AG_Freedson). No significant differences in MVPA were seen between LC_5 and AG_Treuth (Δ = 4.9 min) or AG_Puyau (Δ = 1.7 min). Conclusion: The LC detected a comparable number of steps as the DW but significantly fewer steps than the AG in children. Current results indicate that the LC_5 and either AG_Treuth or AG_Puyau intensity derivations provide similar mean estimates of time in MVPA during-free living activity in 10-yr-old children.

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Background Overweight and obesity has become a serious public health problem in many parts of the world. Studies suggest that making small changes in daily activity levels such as “breaking-up” sedentary time (i.e., standing) may help mitigate the health risks of sedentary behavior. The aim of the present study was to examine time spent in standing (determined by count threshold), lying, and sitting postures (determined by inclinometer function) via the ActiGraph GT3X among sedentary adults with differing weight status based on body mass index (BMI) categories. Methods Participants included 22 sedentary adults (14 men, 8 women; mean age 26.5 ± 4.1 years). All subjects completed the self-report International Physical Activity Questionnaire to determine time spent sitting over the previous 7 days. Participants were included if they spent seven or more hours sitting per day. Postures were determined with the ActiGraph GT3X inclinometer function. Participants were instructed to wear the accelerometer for 7 consecutive days (24 h a day). BMI was categorized as: 18.5 to <25 kg/m2 as normal, 25 to <30 kg/m2 as overweight, and ≥30 kg/m2 as obese. Results Participants in the normal weight (n = 10) and overweight (n = 6) groups spent significantly more time standing (after adjustment for moderate-to-vigorous intensity physical activity and wear-time) (6.7 h and 7.3 h respectively) and less time sitting (7.1 h and 6.9 h respectively) than those in obese (n = 6) categories (5.5 h and 8.0 h respectively) after adjustment for wear-time (p < 0.001). There were no significant differences in standing and sitting time between normal weight and overweight groups (p = 0.051 and p = 0.670 respectively). Differences were not significant among groups for lying time (p = 0.55). Conclusion This study described postural allocations standing, lying, and sitting among normal weight, overweight, and obese sedentary adults. The results provide additional evidence for the use of increasing standing time in obesity prevention strategies.

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In this study, we evaluated agreement among three generations of ActiGraph (TM) accelerometers in children and adolescents. Twenty-nine participants (mean age = 14.2 +/- 3.0 years) completed two laboratory-based activity sessions, each lasting 60 min. During each session, participants concurrently wore three different models of the ActiGraph (TM) accelerometers (GT1M, GT3X, GT3X+). Agreement among the three models for vertical axis counts, vector magnitude counts, and time spent in moderate-to-vigorous physical exercise (MVPA) was evaluated by calculating intraclass correlation coefficients and Bland-Altman plots. The intraclass correlation coefficient for total vertical axis counts, total vector magnitude counts, and estimated MVPA was 0.994 (95% CI = 0.989-0.996), 0.981 (95% CI = 0.969-0.989), and 0.996 (95% CI = 0.989-0.998), respectively. Inter-monitor differences for total vertical axis and vector magnitude counts ranged from 0.3% to 1.5%, while inter-monitor differences for estimated MVPA were equal to or close to zero. On the basis of these findings, we conclude that there is strong agreement between the GT1M, GT3X, and GT3X+ activity monitors, thus making it acceptable for researchers and practitioners to use different ActiGraph (TM) models within a given study.

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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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PURPOSE The purposes of this study were to: 1) establish inter-instrument reliability between left and right hip accelerometer placement; 2) examine procedural reliability of a walking protocol used to measure physical activity (PA), and; 3) confirm concurrent validity of accelerometers in measuring PA intensity as compared to the gold standard of oxygen consumption measured by indirect calorimetry. METHODS Eight children (mean age: 11.9; SD: 3.2, 75% male) with CP (GMFCS levels I-III) wore ActiGraph GT3X accelerometers on each hip and the Cosmed K4b^{2} portable indirect calorimeter during two measurement sessions in which they performed the six minute walk test (6MWT) at three self-selected speeds (comfortable/slow, brisk, fast). Oxygen consumption (VO2) and accelerometer step and activity count data were recorded. RESULTS Inter-instrument reliability of ActiGraph GT3X accelerometers placed on left and right hips was excellent (ICC=0.96-0.99, CI_{95}: 0.81-0.99). Reproducibility of the protocol was good/excellent (ICC=0.75-0.95, CI_{95}: 0.75-0.98). Concurrent validity of accelerometer count data and VO2 was fair/good (rho=0.67, p< 0.001). The correlation between step count and VO2 was not significant (rho=0.29, p=0.2). CONCLUSION This preliminary research suggests that ActiGraph GT3X accelerometers are reliable and valid devices to monitor PA during walking in children with CP and may be appropriate in rehabilitation research and clinical practice. ActiGraph GTX3 step counts were not valid for this sample and further research is warranted.

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Purpose This study aimed to determine the feasibility and acceptability of actigraphy to monitor sleep quality and quantity in healthy self-rated good sleeper adults at home-based settings. Method Sixteen healthy volunteers (age > 18) were invited to participate. Each participant was provided with a wrist actigraph device to be worn for 24-hour/day for seven consecutive days to monitor their sleep-wake patterns. Actigraphy data were downloaded using-proprietary software to generate an individual-sleep report. Participants also completed a set of self-reported Health Related Quality of Life (HRQOL) using WHO (five) Well Being Index (WBI) questionnaires. Results Actigraphy was well accepted by all participants. Only 43.8% of the participants achieved normal total sleep time (TST) and 62.5% had a mean sleep efficiency value below the normal range. Despite a reduced quality of sleep among the participants, the self-reported HRQOL scores produced by the WHO-5 WBI showed a “fair” to “good” among the participants. Conclusions To maintain healthy well-being, it is vital to have efficient and quality sleep. Insufficient and poor sleep may contribute to various health problems and hazardous outcomes. People often believe they have normal and efficient sleep, not realising they may be developing poor sleep habits. This study found that actigraphy can be easily utilized to monitor sleep-wake patterns at home-based settings. We proposed that actigraphy could be adapted for use in the primary care settings (e.g. community pharmacy) to improve the sleep health management in the community.

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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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Purpose: The Australian Women’s Activity Survey (AWAS) was developed based on a systematic review and qualitative research on how to measure activity patterns of women with young children (WYC). AWAS assesses activity performed across five domains (planned activities, employment, childcare, domestic responsibilities and transport), and intensity levels (sitting, light-intensity, brisk walking, moderate-intensity and vigorous-intensity) in a typical week in the past month. The purpose of this study was to assess the test-retest reliability and criterion validity of the AWAS. Methods: WYC completed the AWAS on two occasions 7-d apart (test-retest reliability protocol) and/or wore an MTI ActiGraph accelerometer for 7-d in between (validity protocol). Forty WYC (mean age 35 ± 5yrs) completed the test-retest reliability protocol and 75 WYC (mean age 33 ± 5yrs) completed the validity protocol. Interclass Correlation Coefficients (ICC) between AWAS administrations and Spearman’s Correlation Coefficients (rs) between AWAS and MTI data were calculated. Results: AWAS showed good test-retest reliability (ICC=0.80 (0.65-0.89)) and acceptable criterion validity (rs= 0.28, p=0.01) for measuring weekly health-enhancing physical activity. AWAS also provided repeatable and valid estimates of sitting time (test-retest reliability ICC=0.42 (0.13-0.64), and criterion validity (rs= 0.32, p=0.006)). Conclusion: The measurement properties of the AWAS are comparable to those reported for existing self-report measures of physical activity. However, AWAS offers a more comprehensive and flexible alternative for accurately assessing different domains and intensities of activity relevant to WYC. Future research should investigate whether the AWAS is a suitable measure of intervention efficacy by examining its sensitivity to change.

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Objectives Obesity rates are increasing among children of all ages, and reduced physical activity is a likely contributor to this trend. Little is known about the physical activity behavior of preschool-aged children or about the influence of preschool attendance on physical activity. The purpose of this study was to describe the physical activity levels of children while they attend preschools, to identify the demographic factors that might be associated with physical activity among those children, and to determine the extent to which children's physical activity varies among preschools. Methods A total of 281 children from 9 preschools wore an Actigraph (Fort Walton Beach, FL) accelerometer for an average of 4.4 hours per day for an average of 6.6 days. Each child's height and weight were measured, and parents of participating children provided demographic and education data. Results The preschool that a child attended was a significant predictor of vigorous physical activity (VPA) and moderate-to-vigorous physical activity (MVPA). Boys participated in significantly more MVPA and VPA than did girls, and black children participated in more VPA than did white children. Age was not a significant predictor of MVPA or VPA. Conclusions Children's physical activity levels were highly variable among preschools, which suggests that preschool policies and practices have an important influence on the overall activity levels of the children the preschools serve.

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The aim of this study was to investigate adolescents' potential reactivity and tampering while wearing pedometers by comparing different monitoring protocols to accelerometer output. The sample included adolescents (N=123, age range=14-15 years) from three secondary schools in New South Wales, Australia. Schools were randomised to one of the three pedometer monitoring protocols: (i) daily sealed (DS) pedometer group, (ii) unsealed (US) pedometer group or (iii) weekly sealed (WS) pedometer group. Participants wore pedometers (Yamax Digi-Walker CW700, Yamax Corporation, Kumamoto City, Japan) and accelerometers (Actigraph GT3X+, Pensacola, USA) simultaneously for seven days. Repeated measures analysis of variance was used to examine potential reactivity. Bivariate correlations between step counts and accelerometer output were calculated to explore potential tampering. The correlation between accelerometer output and pedometer steps/day was strongest among participants in the WS group (r=0.82, P <= 0.001), compared to the US (r=0.63, P <= 0.001) and DS (r=0.16, P=0.324) groups. The DS (P <= 0.001) and US (P=0.003), but not the WS (P=0.891), groups showed evidence of reactivity. The results suggest that reactivity and tampering does occur in adolescents and contrary to existing research, pedometer monitoring protocols may influence participant behaviour.

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Objectives This study explored the criterion-related validity and test-retest reliability of the modified RESIDential Environment physical activity questionnaire and whether the instrument's validity varied by body mass index, education, race/ethnicity, or employment status. Design Validation study using baseline data collected for randomized trial of a weight loss intervention. Methods Participants recruited from health departments wore an ActiGraph accelerometer and self-reported non-occupational walking, moderate and vigorous physical activity on the modified RESIDential Environment questionnaire. We assessed validity (n = 152) using Spearman correlation coefficients, and reliability (n = 57) using intraclass correlation coefficients. Results When compared to steps, moderate physical activity, and bouts of moderate/vigorous physical activity measured by accelerometer, these questionnaire measures showed fair evidence for validity: recreational walking (Spearman correlation coefficients 0.23–0.36), total walking (Spearman correlation coefficients 0.24–0.37), and total moderate physical activity (Spearman correlation coefficients 0.18–0.36). Correlations for self-reported walking and moderate physical activity were higher among unemployed participants and women with lower body mass indices. Generally no other variability in the validity of the instrument was found. Evidence for reliability of RESIDential Environment measures of recreational walking, total walking, and total moderate physical activity was substantial (intraclass correlation coefficients 0.56–0.68). Conclusions Evidence for questionnaire validity and reliability varied by activity domain and was strongest for walking measures. The questionnaire may capture physical activity less accurately among women with higher body mass indices and employed participants. Capturing occupational activity, specifically walking at work, may improve questionnaire validity.

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Purpose This study aimed to objectively measure the physical activity (PA) characteristics of a racially and ethnically diverse sample of inner-city elementary schoolchildren and to examine the influence of sex, race/ethnicity, grade level, and weight status on PA. Methods A total of 470 students in grades 4-6 from six inner-city schools in Philadelphia wore an ActiGraph GT3X+ accelerometer (Actigraph, Pensacola, FL) for up to 7 d. The resultant data were uploaded to a customized Visual Basic EXCEL macro to determine the time spent in sedentary (SED), light-intensity PA (LPA), and moderate- to vigorous-intensity PA (MVPA). Results On average, students accumulated 48 min of MVPA daily. Expressed as a percentage of monitoring time, students were sedentary for 63% of the time, in LPA 31% of the time, and in MVPA 6% of the time. Across all race/ethnicity and grade level groups, boys exhibited significantly higher levels of MVPA than girls did; fifth-grade boys exhibited significantly lower MVPA levels than fourth-and sixth-grade boys did, and sixth-grade girls exhibited significantly lower MVPA levels than fourth-and fifth-grade girls did. Hispanic children exhibited lower levels of MVPA than children from other racial/ethnic groups did, and overweight and obese children exhibited significantly lower MVPA levels than children in the healthy weight range did. Across the entire sample, only 24.3% met the current public health guidelines for PA. Physical inactivity was significantly greater among females, Hispanics, and overweight and obese students. Conclusions Fewer than one in four inner-city schoolchildren accumulated the recommended 60 min of MVPA daily. These findings highlight the need for effective and sustainable programs to promote PA in inner-city youth.

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Background Accelerometers have become one of the most common methods of measuring physical activity (PA). Thus, validity of accelerometer data reduction approaches remains an important research area. Yet, few studies directly compare data reduction approaches and other PA measures in free-living samples. Objective To compare PA estimates provided by 3 accelerometer data reduction approaches, steps, and 2 self-reported estimates: Crouter's 2-regression model, Crouter's refined 2-regression model, the weighted cut-point method adopted in the National Health and Nutrition Examination Survey (NHANES; 2003-2004 and 2005-2006 cycles), steps, IPAQ, and 7-day PA recall. Methods A worksite sample (N = 87) completed online-surveys and wore ActiGraph GT1M accelerometers and pedometers (SW-200) during waking hours for 7 consecutive days. Daily time spent in sedentary, light, moderate, and vigorous intensity activity and percentage of participants meeting PA recommendations were calculated and compared. Results Crouter's 2-regression (161.8 +/- 52.3 minutes/day) and refined 2-regression (137.6 +/- 40.3 minutes/day) models provided significantly higher estimates of moderate and vigorous PA and proportions of those meeting PA recommendations (91% and 92%, respectively) as compared with the NHANES weighted cut-point method (39.5 +/- 20.2 minutes/day, 18%). Differences between other measures were also significant. Conclusions When comparing 3 accelerometer cut-point methods, steps, and self-report measures, estimates of PA participation vary substantially.

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The purpose of this study was to derive ActiGraph cut-points for sedentary (SED), light-intensity physical activity (LPA), and moderate-to-vigorous physical activity (MVPA) in toddlers and evaluate their validity in an independent sample. The predictive validity of established preschool cut-points were also evaluated and compared. Twenty-two toddlers (mean age = 2.1 years ± 0.4 years) wore an ActiGraph accelerometer during a videotaped 20-min play period. Videos were subsequently coded for physical activity (PA) intensity using the modified Children's Activity Rating Scale (CARS). Receiver operating characteristic (ROC) curve analyses were conducted to determine cut-points. Predictive validity was assessed in an independent sample of 18 toddlers (mean age = 2.3 ± 0.4 years). From the ROC curve analyses, the 15-s count ranges corresponding to SED, LPA, and MVPA were 0–48, 49–418, and >418 counts/15 s, respectively. Classification accuracy was fair for the SED threshold (ROC-AUC = 0.74, 95% confidence interval = 0.71–0.76) and excellent for MVPA threshold (ROC-AUC = 0.90, 95% confidence interval = 0.88–0.92). In the cross-validation sample, the toddler cut-point and established preschool cut-points significantly overestimated time spent in SED and underestimated time in spent in LPA. For MVPA, mean differences between observed and predicted values for the toddler and Pate cut-points were not significantly different from zero. In summary, the ActiGraph accelerometer can provide useful group-level estimates of MVPA in toddlers. The results support the use of the Pate cut-point of 420 counts/15 s for MVPA.