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1.
ABSTRACT

Purpose: To compare children’s energy expenditure (EE) levels during object projection skill performance (OPSP; e.g., kicking, throwing, striking) as assessed by hip- and wrist-worn accelerometers. Method: Forty-two children (female n = 20, Mage = 8.1 ± 0.8 years) performed three, nine-minute sessions of kicking, over-arm throwing, and striking at performance intervals of 6, 12, and 30 seconds. EE was estimated using indirect calorimetry (COSMED k4b2) and accelerometers (ActiGraph GT3X+) worn on three different locations (hip, dominant-wrist, and non-dominant-wrist) using four commonly used cut-points. Bland-Altman plots were used to analyze the agreement in EE estimations between accelerometry and indirect calorimetry (METS). Chi-square goodness of fit tests were used to examine the agreement between accelerometry and indirect calorimetry. Results: Hip- and wrist-worn accelerometers underestimated EE, compared to indirect calorimetry, during all performance conditions. Skill practice at a rate of two trials per minute resulted in the equivalent of moderate PA and five trials per minute resulted in vigorous PA (as measured by indirect calorimetry), yet was only categorized as light and/or moderate activity by all measured forms of accelerometry. Conclusion: This is one of the first studies to evaluate the ability of hip- and wrist-worn accelerometers to predict PA intensity levels during OPSP in children. These data may significantly impact PA intervention measurement strategies by revealing the lack of validity in accelerometers to accurately predict PA levels during OPSP in children.  相似文献   

2.
Abstract

The ActiGraph activity monitors have developed and newer versions of the ActiGraph accelerometers (GT1M, GT3X and GT3X +) are now available, including changes in hardware and software compared to the old version (AM7164). This is problematic as most of the validation and calibration work includes the AM7164. The aims of the study were to validate the ActiGraph GT1M during level and graded walking and to assess the potential underestimation of physical activity during cycling. Data were obtained from 20 participants during treadmill walking and ergometer cycling. Energy expenditure was measured via indirect calorimetry and used as the criterion method. Activity counts were highly correlated with energy expenditure during level walking (R2 = 0.82) and graded walking at 5% and 8% (R2 = 0.82 and R2 = 0.67, respectively). There was no linear relationship between activity counts and energy expenditure during cycling. The average activity counts for all data points during cycling was 1,157 counts per minute (CPM) (SD = 974), and mean energy expenditure was 5.0 metabolic equivalents. The GT1M is a valid tool for assessing walking across a wide range of speeds and gradients. However, there is no relationship between activity counts and energy expenditure during cycling and physical activity is underestimated by ≈73% during cycling compared to walking.  相似文献   

3.
Abstract

In this study, we evaluated agreement among three generations of ActiGraph? 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? 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? models within a given study.  相似文献   

4.
ABSTRACT

Purpose: The purpose of this study was to evaluate the agreement of five commercially available accelerometers in estimating energy expenditure while performing an acute bout of high-intensity functional training (HIFT). Methods: Participants (n = 47; average age: 28.5 ± 11.6 years) consisted of recreationally active, healthy adults. Each participant completed a session of HIFT: a 15-minute workout consisting of 12 repetitions each of air-squats, sit-ups, push-ups, lunges, pull-ups, steps-ups, and high-knees; performed circuit-style by completing as many rounds as possible. During this session, each participant wore the Cosmed K4b2 portable metabolic analyzer (PMA) and five different accelerometers (ActiGraph GT3X, Nike Fuelband, Fitbit One, Fitbit Charge HR, and Jawbone UP Move). Results: Four of the five activity trackers reported lower (p < .05) total EE values compared to the PMA during the acute bout of HIFT. The waist-mounted device (ActiGraph, 182.55 ± 37.93 kcal) was not significantly different from, and most closely estimated caloric expenditure compared to the PMA (144.99 ± 37.13 kcal) (p = .056). A repeated-measures ANOVA showed that all activity trackers were significantly different from the reference measure (PMA) (p < .05). Systematic relative agreement between the activity trackers was calculated, exhibiting a significant ICC = 0.426 (F [46,230] = 5.446 [p < .05]). Conclusion: The wrist- and hip-mounted activity trackers did not accurately assess energy expenditure during HIFT exercise. With the exception of the ActiGraph GT3X, the remaining four activity trackers showed inaccurate estimates of the amount of kilocalories expended during the HIFT exercise bout compared to the PMA.  相似文献   

5.
Accelerometry is the gold standard for field-based physical activity assessment in children; however, the plethora of devices, data reduction procedures, and cut-points available limits comparability between studies. This study aimed to compare physical activity variables from the ActiGraph GT3X+ and Actical accelerometers in children under free-living conditions. A cross-sectional study of 379 children aged 9–11 years from Ottawa (Canada) was conducted. Children wore the ActiGraph GT3X+ and Actical accelerometers on the hip simultaneously for 7 consecutive days (24-h protocol). Moderate-to-vigorous (MVPA), vigorous (VPA), moderate (MPA), and light (LPA) physical activity, as well as sedentary time, (SED) were derived using established data reduction protocols. Excellent agreement between devices was observed for MVPA (ICC = 0.73–0.80), with fair to good agreement for MPA, LPA and SED, and poor agreement for VPA. Bland-Altman plots showed excellent agreement for MVPA, LPA, and SED, adequate agreement for MPA, and poor agreement for VPA. MVPA derived from the Actical was 11.7% lower than the ActiGraph GT3X+. The ActiGraph GT3X+ and Actical are comparable for measuring children’s MVPA. However, comparison between devices for VPA, MPA, LPA, and SED are highly dependent on data reduction procedures and cut-points, and should be interpreted with caution.  相似文献   

6.
Accurate estimation of energy expenditure (EE) from accelerometer outputs remains a challenge in older adults. The aim of this study was to validate different ActiGraph (AG) equations for predicting EE in older adults. Forty older adults (age = 77.4 ± 8.1 yrs) completed a set of household/gardening activities in their residence, while wearing an AG at the hip (GT3X+) and a portable calorimeter (MetaMax 3B – criterion). Predicted EEs from AG were calculated using five equations (Freedson, refined Crouter, Sasaki and Santos-Lozano (vertical-axis, vectormagnitude)). Accuracy of equations was assessed using root-mean-square error (RMSE) and mean bias. The Sasaki equation showed the lowest RMSE for all activities (0.47 METs) and across physical activity intensities (PAIs) (range 0.18–0.48 METs). The Freedson and Santos-Lozano equations tended to overestimate EE for sedentary activities (range: 0.48 to 0.97 METs), while EEs for moderate-to-vigorous activities (MVPA) were underestimated (range: ?1.02 to ?0.64 METs). The refined Crouter and Sasaki equations showed no systematic bias, but they respectively overestimated and underestimated EE across PAIs. In conclusion, none of the equations was completely accurate for predicting EE across the range of PAIs. However, the refined Crouter and Sasaki equations showed better overall accuracy and precision when compared with the other methods.  相似文献   

7.
The purpose of this study was to compare the validity and output of the biaxial ActiGraph GT1M and the triaxial GT3X (ActiGraph, LLC, Pensacola, FL, USA) accelerometer in 5- to 9-year-old children. Thirty-two children wore the two monitors while their energy expenditure was measured with indirect calorimetry. They performed four locomotor and four play activities in an exercise laboratory and were further measured during 12 minutes of a sports lesson. Validity evidence in relation to indirect calorimetry was examined with linear regression equations applied to the laboratory data. During the sports lessons predicted energy expenditure according to the regression equations was compared to measured energy expenditure with the Wilcoxon-signed rank test and the Spearman correlation. To compare the output, agreement between counts of the two monitors during the laboratory activities was assessed with Bland-Altman plots. The evidence of validity was similar for both monitors. Agreement between the output of the two monitors was good for vertical counts (mean bias =??14 ± 22 counts) but not for horizontal counts (?17 ± 32 counts). The current results indicate that the two accelerometer models are able to estimate energy expenditure of a range of physical activities equally well in young children. However, they show output differences for movement in the horizontal direction.  相似文献   

8.
This study investigated the effects of epoch length and cut point selection on adolescent physical activity intensity quantification using vertical axis and vector magnitude (VM) measurement with the ActiGraph GT3X+ accelerometer. Four hundred and nine adolescents (211 males; 198 females) aged 12–16 years of age wore accelerometers during waking hours. The GT3X+ acceleration counts were reintegrated into 1, 5, 15, 30 and 60 s epoch lengths for both vertical axis and VM counts. One cut point was applied to vertical axis counts and three different cut points were applied to VM counts for each epoch length. Significant differences (P < 0.01) in mean total counts per day were observed between vertical axis and VM counts, and between epoch lengths for VM only. Differences in physical activity levels were observed between vertical and VM cut points, and between epoch lengths across all activity intensities. Our findings illustrate the magnitude of differences in physical activity outcomes that occur between axis measurement, cut points and epoch length. The magnitude of difference across epoch length must be considered in the interpretation of accelerometer data and seen as a confounding variable when comparing physical activity levels between studies.  相似文献   

9.
Although accelerometers can assess sleep and activity over 24 h, sleep data must be removed before physical activity and sedentary time can be examined appropriately. We compared the effect of 6 different sleep-scoring rules on physical activity and sedentary time. Activity and sleep were obtained by accelerometry (ActiGraph GT3X) over 7 days in 291 children (51.3% overweight or obese) aged 4–8.9 years. Three methods removed sleep using individualised time filters and two methods applied standard time filters to remove sleep each day (9 pm–6 am, 12 am–6 am). The final method did not remove sleep but simply defined non-wear as at least 60 min of consecutive zeros over the 24-h period. Different methods of removing sleep from 24-h data markedly affect estimates of sedentary time, yielding values ranging from 556 to 1145 min/day. Estimates of non-wear time (33–193 min), wear time (736–1337 min) and counts per minute (384–658) also showed considerable variation. By contrast, estimates of moderate-to-vigorous activity (MVPA) were similar, varying by less than 1 min/day. Different scoring methods to remove sleep from 24-h accelerometry data do not affect measures of MVPA, whereas estimates of counts per minute and sedentary time depend considerably on which technique is used.  相似文献   

10.
This study establishes tri-axial activity count (AC) cut-points for the GT3X+ accelerometer to classify physical activity intensity in overweight and obese adults. Further, we examined the accuracy of established and novel energy expenditure (EE) prediction equations based on AC and other metrics. Part 1: Twenty overweight or obese adults completed a 30 minute incremental treadmill walking protocol. Heart rate (HR), EE, and AC were measured using the GT3X+ accelerometer. Part 2: Ten overweight and obese adults conducted a self-paced external walk during which EE, AC, and HR were measured. Established equations (Freedson et al., 1998; Sasaki et al., 2011) overestimated EE by 40% and 31%, respectively (p < .01). Novel gender-specific prediction equations provided good estimates of EE during treadmill and outdoor walking (standard error of the estimate = .91 and .65, respectively). We propose new cut-points and prediction equations to estimate EE using the GT3X+ tri-axial accelerometer in overweight and obese adults.  相似文献   

11.
Accelerometry is widely used to evaluate physical activity in toddlers however recommendations regarding wear time are needed to understand physical activity behaviours in this age group. This study aimed to determine the minimum wear time to reliably evaluate physical activity in toddlers. Children from the 3D Birth Cohort (n = 255, 49.8% boys, 2.1 ± 0.2 years) were asked to wear an accelerometer (GT3X+, ActiGraph) for 7 days. Physical activity was expressed in active time (min/day) and counts per minute (CPM). Single day intraclass correlation coefficients (ICCs) were calculated to assess the effect of varying minimal wear time on reliability estimates. The Spearman-Brown formula was used to determine wear time required to achieve reliability levels of 70%, 80% and 90%. For active time, a reliability of 72.1% was achieved with wearing the accelerometer for ≥ 4 days of ≥ 6 h, which comprised 85.9% of the sample. For CPM, ≥ 4 days of ≥ 6 h provided a reliability of 74.7% and comprised 85.9% of the children. Results differed slightly when girls and boys were analysed separately, but restricting analyses to children with a weekend day did not. In summary, a minimum of 4 days with ≥ 6 h of accelerometry data provides a reliable estimate of physical activity in 2-year toddlers.  相似文献   

12.
This study examined the metabolic cost (METs) of performing object projection skills at three practice trial intervals (6, 12, and 30 seconds). Forty adults (female n = 20) aged 18–30 (M = 23.7 ± 2.9 years) completed three, nine-minute sessions of skill trials performed at 6, 12, and 30 second intervals. Participants performed kicking, throwing and striking trials in a blocked schedule with maximal effort. Average METs during each session were measured using a COSMED K4b2. A three (interval condition) X two (sex) ANOVA was conducted to examine differences in METs across interval conditions and by sex. Results indicated a main effect for interval condition (F(5,114) = 187.02, p < .001, η2 = 0.76) with decreased interval times yielding significantly higher METs [30 sec = 3.45, 12 sec = 5.68, 6 sec = 8.21]. A main effect for sex (F(5, 114) = 35.39, p < .001, η2 = 0.24) also was found with men demonstrating higher METs across all intervals. At a rate of only two trials/min, participants elicited moderate physical activity, with 12 and 6-second intervals exhibiting vigorous PA. Demonstrating MVPA during the performance of object projection skill performance has potential implications for PA interventions.  相似文献   

13.
This study aimed at translating the physical activity (PA) guideline (180 min of total PA per day) into a step count target in preschoolers. 535 Flemish preschoolers (mean age: 4.41 ± 0.58) wore an ActiGraph accelerometer (GT1M, GT3X and GT3X+) – with activated step count function – for four consecutive days. The step count target was calculated from the accelerometer output using a regression equation, applying four different cut-points for light-to-vigorous PA: Pate, Evenson, Reilly, and Van Cauwenberghe. The present analysis showed that 180 min of total PA per day is equivalent to the following step count targets: 5,274 steps/day using the Pate cut-point, 4,653 steps/day using the Evenson cut-point, 11,379 steps/day using the Reilly cut-point and 13,326 steps/day using the Van Cauwenberghe cut-point. Future studies should focus on achieving consensus on which cut-points to use in preschoolers before a definite step count target in preschoolers can be proposed. Until then, we propose to use a provisional step count target of 11,500 steps/day as this step count target is attainable, realistic and helpful in promoting preschoolers’ PA.  相似文献   

14.
Objective: To examine children’s energy expenditure (EE) during object projection skill performance at three intensity intervals. Methods: Children’s (42, Mage = 8.1) average metabolic equivalents of task (METs) were calculated using a COSMED K4b2 while they repeatedly performed blocks of kicking, throwing (overhand), and striking (two-handed) during 6, 12, and 30-s interval conditions. A repeated-measures analysis of covariance examined differences in METs while controlling for skill level. Results: Data indicated a main effect for interval condition (df = 2, 123, F = 94.36, p <.001, η2 = .605). Post hoc t-tests demonstrated decreasing performance interval times yielded progressively higher METs (p <.001) across the three conditions (30s = 4.5±0.8 METs, 12s = 6.3±1.3, 6s = 8.3±1.6). There also was a main effect for sex (df = 1,120, F = 52.28, p <.001 η2 = .305). Boys demonstrated higher METs at each performance interval (p <.001). Conclusion: Skill practice with a maximum of one trial every 30s resulted in the equivalent of at least moderate physical activity (>4.0 METs) and intervals of 6s demonstrated vigorous physical activity (>7.0 METs). Practicing/performing object projection skills, even at intervals that allow for adequate instruction and feedback (i.e., 1 trial/30s), promotes MVPA in children.  相似文献   

15.
Research suggests participation in youth sport does not guarantee physical activity (PA) guidelines are met. Studies indicate few children achieve recommended levels of moderate-to-vigorous physical activity (MVPA) during their youth sport involvement, and habitual levels of MVPA are below the recommended 60 min per day. Informed by self-determination theory, this study examined whether the coach-created social environment and related player motivation predict variability in objectively measured MVPA within the youth sport setting. Seventy three male youth sport footballers (Mean age = 11.66 ± 1.62) completed a multisection questionnaire assessing their perceptions of the social environment created in youth sport (autonomy supportive and controlling) and motivation towards their football participation (autonomous and controlled). Intensity of PA during youth sport was measured using accelerometers (GT3X, ActiGraph). Results supported a model in which perceptions of autonomy support significantly and positively predicted autonomous motivation towards football, which in turn significantly and positively predicted youth sport MVPA (% time). A significant indirect effect was observed for perceptions of autonomy support on youth sport %MVPA via autonomous motivation. Results have implications for optimising MVPA engagement during youth sport and increasing daily MVPA towards recommended and health-enhancing levels on youth sport days.  相似文献   

16.
This study assessed children’s physical activity (PA) levels derived from wrist-worn GENEActiv and hip-worn ActiGraph GT3X+ accelerometers and examined the comparability of PA levels between the two devices throughout the segmented week. One hundred and twenty-nine 9–10-year-old children (79 girls) wore a GENEActiv (GAwrist) and ActiGraph GT3X+ (AGhip) accelerometer on the left wrist and right hip, respectively, for 7 days. Mean minutes of light PA (LPA) and moderate-to-vigorous PA (MVPA) per weekday (whole-day, before-school, school and after-school) and weekend day (whole-day, morning and afternoon–evening) segments were calculated, and expressed as percentage of segment time. Repeated measures analysis of variance examined differences in LPA and MVPA between GAwrist and AGhip for each time segment. Bland–Altman plots assessed between-device agreement for LPA and MVPA for whole weekday and whole weekend day segments. Correlations between GAwrist and AGhip were weak for LPA (r = 0.18–0.28), but strong for MVPA (r = 0.80–0.86). LPA and MVPA levels during all weekday and weekend day segments were significantly higher for GAwrist than AGhip (p < 0.001). The largest inter-device percent difference of 26% was observed in LPA during the school day segment. Our data suggest that correction factors are needed to improve raw PA level comparability between GAwrist and AGhip.  相似文献   

17.
The purpose of the current study was to determine metabolic thresholds and subsequent activity intensity cutoff points for the ActiGraph GT1M with various epochs spanning from 5 to 60 sec in young children. Twenty-two children, aged 4 to 9 years, performed 10 different activities including locomotion and play activities. Energy expenditure was measured with indirect calorimetry. Thresholds and cutoff points were determined through receiver operating characteristic curves. The lower metabolic threshold was 6.19 kcal·kg?1·h?1 for moderate and 9.28 kcal·kg?1·h?1 for vigorous intensity. The cutoff points for the GT1M accelerometer appear to be lower than those for the previous model (7164). For 5-sec epochs, a cutoff point of 143 counts resulted for moderate intensity and of 208 counts for vigorous intensity activity. Whether short or long epochs were chosen when collecting data to determine cutoff points, does not appear to have an influence on the resulting cutoff values. Similarly, comparable results are seen when analyses are based on locomotion only as opposed to a wide range of activities including children's play.  相似文献   

18.
The World Health Organisation’s (WHO) physical activity guidelines recommend 150min/week of moderate- to vigorous-intensity physical activity (MVPA) accumulated in 10 min bouts. To see whether people performing habitual exercise for recreation meet these guidelines, 25 long-distance runners [mean 67 km/wk], 25 joggers [mean 28 km/wk], and 20 sedentary adults wore an ActiGraph GT3X+ accelerometer for 7 days. Sedentary time and bouts were similar in runners and sedentary adults (p > 0.46). Sedentary adults performed 20 ± 16 min/day of MVPA (usual bout duration (W50%): 9.53 ± 3.45min), with joggers and runners performing 45 ± 31min (W50%: 16.92 ± 9.53min) and 83 ± 58min (W50%: 20.35 ± 8.85min), respectively (p ≤ 0.001 versus sedentary group). Data showed that 65% of the sedentary group, 32% of joggers and 4% of long-distance runners did not meet the WHO guideline for MVPA. Failure to meet the guideline was most prominent in, but not restricted to, runners who reported ≤50km running per week. Self-reported running does not ensure adults meet physical activity guidelines or offset daily sedentary behaviours. On the other hand, the sedentary group was very close in accumulating recommended bouts of MVPA in incidental activities. Future studies should assess whether modification of work and leisure physical activity would be more fruitful than encouraging recreational exercise per se in meeting physical activity guidelines.  相似文献   

19.
The aim of this study was to determine if a potential relationship among physical activity (PA), fundamental movement skills and weight status exists amongst early adolescent youth. Participants were a sample of 85 students; 54 boys (mean age = 12.94 ± 0.33 years) and 31 girls (mean age = 12.75 ± 0.43 years). Data gathered during physical education class included PA (accelerometry), fundamental movement skills and anthropometric measurements. Standard multiple regression revealed that PA and total fundamental movement skill proficiency scores explained 16.5% (P < 0.001) of the variance in the prediction of body mass index. Chi-square tests for independence further indicated that compared with overweight or obese adolescents, a significantly higher proportion of adolescents classified as normal weight achieved mastery/near-mastery in fundamental movement skills. Results from the current investigation indicate that weight status is an important correlate of fundamental movement skill proficiency during adolescence. Aligned with most recent research, school- and community-based programmes that include developmentally structured learning experiences delivered by specialists can significantly improve fundamental movement skill proficiency in youth.  相似文献   

20.
This study explored the validity of ActiGraph-determined sedentary time (<50 cpm, <100 cpm, <150 cpm, <200 cpm, <250 cpm) compared with the activPAL in a free-living sample of bus drivers. Twenty-eight participants were recruited between November 2013 and February 2014. Participants wore an activPAL3 and ActiGraph GT3X+ concurrently for 7 days and completed a daily diary. Time spent sedentary during waking hours on workdays, non-workdays, during working-hours, and non-working hours were compared between instruments. During working hours, all ActiGraph cut-points significantly underestimated sedentary time (p < 0.05), whereas during non-working hours the <50 cpm cut-point demonstrated the closest agreement (ActiGraph sedentary time: 250 ± 75 minutes versus activPAL sedentary time: 236 ± 65 minutes). Receiver operating characteristic analyses revealed that on workdays and non-workdays the ActiGraph cut-points exhibited relatively low sensitivity (all <0.62) and specificity (all <0.49) values. The use of the ActiGraph to measure sedentary time in this understudied, highly sedentary and at risk occupational group is not recommended.  相似文献   

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