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1.
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   

2.
Abstract

This aim of this study was to compare the new Actigraph (GT1M) with the widely used Model 7164. Seven days of free-living physical activity were measured simultaneously using both the Model 7164 and GT1M in 30 Indian adolescents (mean age 15.8 years, s = 0.6). The GT1M was on average 9% lower per epoch than model 7164, thus a correction factor of 0.91 is suggested for comparison between the two monitors. The differences between monitors increased in magnitude with intensity of activity (P < 0.001) but remained randomly distributed (r = 0.01, P = 0.96). No significant difference was observed between monitors for time spent in moderate (P = 0.31) and vigorous (P = 0.34) physical activity when using the same epoch length. The Model 7164 classified less time as sedentary (P < 0.001) and more time as light-intensity activity (P < 0.001) than the GT1M. In conclusion, data from the GT1M can be compared with historical data using average counts per minute with a correction factor, and the two models might be comparable for assessing time spent in moderate to vigorous physical activity in children when using the same epoch length.  相似文献   

3.
ABSTRACT

Accelerometer cut points are an important consideration for distinguishing the intensity of activity into categories such as moderate and vigorous. It is well-established in the literature that these cut points depend on a variety of factors, including age group, device, and wear location. The Actigraph GT9X is a newer model accelerometer that is used for physical activity research, but existing cut points for this device are limited since it is a newer device. Furthermore, there is not existing data on cut points for the GT9X at the ankle or foot locations, which offers some potential benefit for activities that do not involve arm and/or core motion. A total of N = 44 adults completed a four-stage treadmill protocol while wearing Actigraph GT9X sensors at four different locations: foot, ankle, wrist, and hip. Metabolic Equivalent of Task (MET) levels assessed by indirect calorimetry along with Receiver Operating Characteristic (ROC) curves were used to establish cut points for moderate and vigorous intensity for each wear location of the GT9X. Area under the ROC curves indicated high discrimination accuracy for each case.  相似文献   

4.
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   

5.
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   

6.
Abstract

The purpose of this study was (1) to describe physical activity prevalence, categorised according to the 2008 Physical Activity Guidelines for Americans (2008 Guidelines), using different accelerometer cut points and (2) to examine physical activity prevalence patterns by reported cut points across selected characteristics. Cut points from 9 studies were used to estimate physical activity prevalence in a national adult sample (n = 6547). Estimates were stratified by validation study activity protocols used to derive cut points – ambulatory (walking/running) and lifestyle activities (e.g. gardening, housework, walking). Results showed that the prevalence of meeting the 2008 Guidelines ranged from 6.3% to 98.3% overall and was lower for cut points derived from ambulatory (median = 11.5%, range = 6.3–27.4%) compared to lifestyle (median = 77.2%, range = 60.6–98.3%) protocols. Prevalence patterns across protocols differed for age, but were similar for other characteristics. In conclusion, prevalence of meeting the 2008 Guidelines varied widely, indicating that choice of cut point had an impact on prevalence. To generate future accelerometer cut points one may consider developing cut points for demographic subgroups using a variety of lifestyle physical activities.  相似文献   

7.
This study developed and validated a vector magnitude (VM) two-regression model (2RM) for use with an ankle-worn ActiGraph accelerometer. For model development, 181 youth (mean ± SD; age, 12.0 ± 1.5 yr) completed 30 min of supine rest and 2–7 structured activities. For cross-validation, 42 youth (age, 12.6 ± 0.8 yr) completed approximately 2 hr of unstructured physical activity (PA). PA data were collected using an ActiGraph accelerometer, (non-dominant ankle) and the VM was expressed as counts/5-s. Measured energy expenditure (Cosmed K4b2) was converted to youth METs (METy; activity VO2 divided by resting VO2). A coefficient of variation (CV) was calculated for each activity to distinguish continuous walking/running from intermittent activity. The ankle VM sedentary behavior threshold was ≤10 counts/5-s, and a CV≤15 counts/5-s was used to identify walking/running. The ankle VM2RM was within 0.42 METy of measured METy during the unstructured PA (P > 0.05). The ankle VM2RM was within 5.7 min of measured time spent in sedentary, LPA, MPA, and VPA (P > 0.05). Compared to the K4b2, the ankle VM2RM provided similar estimates to measured values during unstructured play and provides a feasible wear location for future studies.  相似文献   

8.
This aim of this study was to compare the new Actigraph (GT1M) with the widely used Model 7164. Seven days of free-living physical activity were measured simultaneously using both the Model 7164 and GT1M in 30 Indian adolescents (mean age 15.8 years, s = 0.6). The GT1M was on average 9% lower per epoch than model 7164, thus a correction factor of 0.91 is suggested for comparison between the two monitors. The differences between monitors increased in magnitude with intensity of activity (P < 0.001) but remained randomly distributed (r = 0.01, P = 0.96). No significant difference was observed between monitors for time spent in moderate (P = 0.31) and vigorous (P = 0.34) physical activity when using the same epoch length. The Model 7164 classified less time as sedentary (P < 0.001) and more time as light-intensity activity (P < 0.001) than the GT1M. In conclusion, data from the GT1M can be compared with historical data using average counts per minute with a correction factor, and the two models might be comparable for assessing time spent in moderate to vigorous physical activity in children when using the same epoch length.  相似文献   

9.
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   

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.
This study examined differences in physical activity (PA) estimates provided from raw and counts processing methods. One hundred and sixty-five children (87 girls) wore a hip-mounted ActiGraph GT3X+ accelerometer for 7 days. Data were available for 129 participants. Time in moderate PA (MPA), vigorous PA (VPA) and moderate-vigorous PA (MVPA) were calculated using R-package GGIR and ActiLife. Participants meeting the wear time criteria for both processing methods were included in the analysis. Time spent in MPA (?21.4 min.d?1, 95%CI ?21 to ?20) and VPA (?36 min.d?1, 95%CI ?40 to ?33) from count data were higher (P < 0.001) than raw data. Time spent in MVPA between the two processing methods revealed significant differences (All P < 0.001). Bland-Altman plots suggest that the mean bias for time spent in MPA, VPA and MVPA were large when comparing raw and count methods. Equivalence tests showed that estimates from raw and count processing methods across all activity intensities lacked equivalence. Lack of equivalence and poor agreement between raw and count processing methods suggest the two approaches to estimate PA are not comparable. Further work to facilitate the comparison of findings between studies that process and report raw and count physical activity data may be necessary.  相似文献   

12.
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   

13.
ABSTRACT

This study compared five different methods for analyzing accelerometer-measured physical activity (PA) in older adults and assessed the relationship between changes in PA and changes in physical function and depressive symptoms for each method. Older adult females (N = 144, Mage = 83.3 ± 6.4yrs) wore hip accelerometers for six days and completed measures of physical function and depressive symptoms at baseline and six months. Accelerometry data were processed by five methods to estimate PA: 1041 vertical axis cut-point, 15-second vector magnitude (VM) cut-point, 1-second VM algorithm (Activity Index (AI)), machine learned walking algorithm, and individualized cut-point derived from a 400-meter walk. Generalized estimating equations compared PA minutes across methods and showed significant differences between some methods but not others; methods estimated 6-month changes in PA ranging from 4 minutes to over 20 minutes. Linear mixed models for each method tested associations between changes in PA and health. All methods, except the individualized cut-point, had a significant relationship between change in PA and improved physical function and depressive symptoms. This study is among the first to compare accelerometry processing methods and their relationship to health. It is important to recognize the differences in PA estimates and relationship to health outcomes based on data processing method.

Abbreviation: Machine Learning (ML); Short Physical Performance Battery (SPPB); Center of Epidemiologic Studies Depression Scale (CES-D); Physical Activity (PA); Activity Index (AI); Activities of Daily Living (ADL)  相似文献   

14.
ABSTRACT

Reliability of accelerometer-determined physical activity (PA), and thus the required length of a monitoring period, appears to depend on the analytic approach used for its calculation. We compared reliability of objectively measured PA using different resolution of data in a sample of 221 Norwegian 2–6-year-old children providing 2–3 valid 14-day periods of accelerometer monitoring (ActiGraph GT3X+) during September–October, January–February, and May–June 2015–2016. Reliability (intra-class correlation [ICC]) was measured for 1–14 days of monitoring across the measurement periods using linear mixed effect modelling. These results were compared to reliability estimated using different resolution of data using the Spearman–Brown formula. The measured reliability improved only marginally with increased monitoring length and levelled off after 5–6 days. Estimated reliability differed substantially when derived from different resolution of data: 3.9–5.4, 6.7–9.2, 13.4–26.7 and 26.3–87.7 days of monitoring was required to achieve an ICC = 0.80 using an hour-by-hour, a day-by-day, a week-by-week and a period-by-period approach, respectively. Reliability could not be correctly estimated from any single resolution of data. We conclude that reconsideration is needed with regard to how reproducibility of objectively measured PA is analysed and interpreted.  相似文献   

15.
The GT3X+ worn at the wrist promotes greater compliance than at the hip. Minutes in SB and PA calculated from raw accelerations at the hip and wrist provide contrasting estimates and cannot be directly compared.

Wear-time for the wrist (15.6 to 17.4 h.d?1) was greater than the hip (15.2 to 16.8 h.d?1) across several wear-time criteria (all P < 0.05). Moderate-strong associations were found between time spent in SB (r = 0.39), LPA (r = 0.33), MPA (r = 0.99), VPA (r = 0.82) and MVPA (r = 0.81) between the two device placements (All P < 0.001). The wrist device detected more minutes in LPA, MPA, VPA and MVPA whereas the hip detected more SB (all P = 0.001). Estimates of time in SB and all activity outcomes from the wrist and hip lacked equivalence.

One hundred and eighty-eight 9–12-year-old children wore a wrist- and hip-mounted accelerometer for 7 days. Data were available for 160 (hip) and 161 (wrist) participants. Time spent in SB and PA was calculated using GGIR.

This study examined the compliance of children wearing wrist- and hip-mounted ActiGraph GT3X+ accelerometers and compared estimates of sedentary behaviour (SB) and physical activity (PA) between devices.  相似文献   

16.
This study investigated the reliability of a wireless accelerometer and its agreement with optical motion capture for the measurement of root mean square (RMS) acceleration during running. RMS acceleration provides a whole-body metric of movement mechanics and economy. Fifteen healthy college-age participants performed treadmill running for two 60-s trials at 2.22, 2.78, and 3.33 m/s and one trial of 150 s (five 30-s epochs) at 2.78 m/s. We assessed between-trial and within-trial reliability, and agreement in each axis between a trunk-mounted wireless accelerometer and a reflective marker on the accelerometer measured by optical motion capture. Intraclass correlations assessing between-trial repeatability were 0.89–0.97, depending on the axis, and intraclass correlations assessing within-trial repeatability were 0.99–1.00. Bland–Altman analyses assessing agreement indicated mean difference values between ?0.03 and 0.03 g, depending on the axis. Anterio-posterior acceleration had the greatest limits of agreement (LOA) (±0.12 g) and vertical acceleration had the smallest LOA (±0.03 g). For measuring RMS acceleration of the trunk, this wireless accelerometer node provides repeatable and valid measurement compared with the standard laboratory method of optical motion capture.  相似文献   

17.
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   

18.
This study compared step counts detected by four, low-cost, objective, physical-activity-assessment instruments and evaluated their ability to detect moderate-to-vigorous physical activity (MVPA) compared to the ActiGraph accelerometer (AG). Thirty-six 10–11-year-old children wore the NL-1000, Yamax Digiwalker SW 200, Omron HJ-151, and Walk4Life MVP concurrently with the AG during school hours on a single day. AG MVPA was derived from activity count data using previously validated cut points. Two of the evaluated instruments provided similar group mean MVPA and step counts compared to AG (dependent on cut point). Low-cost instruments may be useful for measurement of both MVPA and steps in children's physical activity interventions and program evaluation.  相似文献   

19.
This study compared step counts detected by four, low-cost, objective, physical-activity-assessment instruments and evaluated their ability to detect moderate-to-vigorous physical activity (MVPA) compared to the ActiGraph accelerometer (AG). Thirty-six 10-11-year-old children wore the NL-1000, Yamax Digiwalker SW 200, Omron HJ-151, and Walk4Life MVP concurrently with the AG during school hours on a single day. AG MVPA was derived from activity count data using previously validated cut points. Two of the evaluated instruments provided similar group mean MVPA and step counts compared to AG (dependent on cut point). Low-cost instruments may be useful for measurement of both MVPA and steps in children's physical activity interventions and program evaluation.  相似文献   

20.

Purpose: This study assessed mothers' opinions about the feasibility and acceptability of using the ActiGraph GT3X+, Actiheart, and activPAL3 with their 2- to 3-year-old children, as well as with themselves and their husbands/partners, for an 8-day period. Method: Six focus groups were run with Pakistani and White British mothers (n = 17), in English or Urdu, at Children's Centers in Bradford, United Kingdom. Each accelerometer was shown to the mothers while its characteristics and wearing procedures were explained. Mothers were then asked about their opinion on the feasibility of use with their toddlers, themselves, and husbands/partners, as well as their monitor preference. Data were transcribed verbatim and analyzed through thematic analysis. Results: The ActiGraph was the most preferred accelerometer for use with children, while the Actiheart was the least favorable. The ActiGraph was also the most preferred accelerometer for use with both mothers and fathers. Main issues raised included unsuitability of the Actiheart for fathers due to chest hair, discomfort due to the large size of the activPAL3 in relation to children's thighs, and children pulling off the Actiheart or tampering with the device if its presence was noticed (ActiGraph/Actiheart). Conclusion: The most preferred/accepted accelerometer overall was the ActiGraph GT3X+ for both children and parents. Issues raised with the devices have potential to impact recruitment and compliance rates of studies targeting this population, which highlights the importance of assessing the feasibility/acceptability of different devices with the target population ahead of planning research involving physical activity measurement.  相似文献   

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