Comparison of accelerometer cut points for predicting activity intensity in youth

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.

Validity of the computer science and applications (CSA) activity monitor in children

Purpose The purpose of this study was to evaluate the validity of the CSA activity monitor as a measure of children's physical activity using energy expenditure (EE) as a criterion measure. Methods Thirty subjects aged 10 to 14 performed three 5-min treadmill bouts at 3, 4, and 6 mph, respectively. While on the treadmill, subjects wore CSA (WAM 7164) activity monitors on the right and left hips. (V) over dot O-2 was monitored continuously by an automated system. EE was determined by multiplying the average (V) over dot O-2 by the caloric equivalent of the mean respiratory exchange ratio. Results Repeated measures ANOVA indicated that both CSA monitors were sensitive to changes in treadmill speed. Mean activity counts from each CSA unit were not significantly different and the intraclass reliability coefficient for the two CSA units across all speeds was 0.87. Activity counts from both CSA units were strongly correlated with EE (r = 0.86 and 0.87, P < 0.001). An EE prediction equation was developed from 20 randomly selected subjects and cross-validated on the remaining 10. The equation predicted mean EE within 0.01 kcal.min(-1). The correlation between actual and predicted values was 0.93 (P < 0.01) and the SEE was 0.93 kcal.min(-1). Conclusion These data indicate that the CSA monitor is a valid and reliable tool for quantifying treadmill walking and running in children.

The use of uniaxial and triaxial accelerometers to measure children's "free-play" physical activity

In order to effectively measure the physical activity of children, objective monitoring devices must be able to quantify the intermittent and nonlinear movement of free play. The purpose of this study was to investigate the validity of the Computer Science and Applications (CSA) uniaxial accelerometer and the TriTrac-R3D triaxial accelerometer with respect to their ability to measure 8 "free-play" activities of different intensity. The activities ranged from light to very vigorous in intensity and included activities such as throwing and catching, hopscotch, and basketball. Twenty-eight children, ages 9 to 11, wore a CSA and a heart rate monitor while performing the activities. Sixteen children also wore a Tritrac. Counts from the CSA, Tritrac, and heart rates corresponding to the last 3 min of the 5 min spent at each activity were averaged and used in correlation analyses. Across all 8 activities, Tritrac counts were significantly correlated with predicted MET level (r= 0.69) and heart rate (r= 0.73). Correlations between CSA output, predicted MET level (0.43), and heart rate (0.64) were also significant but were lower than those observed for the Tritrac. These data indicate that accelerometers are an appropriate methodology for measuring children's free-play physical activities.

Tracking of physical activity, physical inactivity, and health-related physical fitness in rural youth

This study examined the tracking of selected measures of physical activity, inactivity, and fitness in a cohort of rural youth. Students (N = 181, 54.7% female, 63.5% African American) completed test batteries during their fifth-(age = 10.7 +/- 0.7 years), sixth-, and seventh-grade years. The Previous Day Physical Activity Recall (PDPAR) was used to assess 30-min blocks of vigorous physical activity (VPA), moderate-to-vigorous physical activity (MVPA), TV watching and other sedentary activities, and estimated energy expenditure (EE). Fitness measures included the PWC 170 cycle ergometer test, strength tests, triceps skinfold thickness, and BMI. Intraclass correlation coefficients (ICCs) for VPA, MVPA, and after-school EE ranged from 0.63 to 0.78. ICCs ranged from 0.49 to 0.71 for measures of inactivity and from 0.78 to 0.82 for the fitness measures. These results indicate that measures of physical activity, inactivity, and physical fitness tend to track during the transition from elementary to middle school.

Calibration of the biotrainer pro activity monitor in children

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.

Numerical investigation on stable crack growth in plane stress

Large deformation finite element analysis has been carried out to investigate the stress-strain fields ahead of a growing crack for compact tension .a=W D 0:5/ and three-point bend .a=W D 0:1 and 0:5/ specimens under plane stress condition. The crack growth is controlled by the experimental J -integral resistance curves measured by Sun et al. The results indicate that the distributions of opening stress, equivalent stress and equivalent strain ahead of a growing crack are not sensitive to specimen geometry. For both stationary and growing cracks, similar distributions of opening stress and triaxiality can be found along the ligament. During stable crack growth, the crack-tip opening displacement (CTOD) resistance curve and the cohesive fracture energy in the fracture process zone are independent of specimen geometry and may be suitable criteria for characterizing stable crack growth in plane stress.

State of the art reviews : measurement of physical activity in children and adolescents

To date, a wide range of methods has been used to measure physical activity in children and adolescents. These include self-report methods such as questionnaires, activity logs, and diaries as well as objective measures of physical activity such as direct observation, doubly labeled water, heart rate monitoring, accelerometers, and pedometers. The purpose of this review is to overview the methods currently being used to measure physical activity in children and adolescents. For each measurement approach, new developments and/or innovations are identified and discussed. Particular attention is given to the use of accelerometers and the calibration of accelerometer output to units of energy expenditure to developing children.

Validity of accelerometry in ambulatory children and adolescents with cerebral palsy

To evaluate the validity of the ActiGraph accelerometer for the measurement of physical activity intensity in children and adolescents with cerebral palsy (CP) using oxygen uptake (VO 2) as the criterion measure. Thirty children and adolescents with CP (mean age 12.6 ± 2.0 years) wore an ActiGraph 7164 and a Cosmed K4b 2 portable indirect calorimeter during four activities; quiet sitting, comfortable paced walking, brisk paced walking and fast paced walking. VO 2 was converted to METs and activity energy expenditure and classiWed as sedentary, light or moderate-to-vigorous intensity according to the conventions for children. Mean ActiGraph counts min -1 were classiWed as sedentary, light or moderate-to-vigorous (MVPA) intensity using four diVerent sets of cut-points. VO 2 and counts min¡1 increased signiWcantly with increases in walking speed (P < 0.001). Receiver operating characteristic (ROC) curve analysis indicated that, of the four sets of cut-points evaluated, the Evenson et al. (J Sports Sci 26(14):1557-1565, 2008) cut-points had the highest classiWcation accuracy for sedentary (92%) and MVPA (91%), as well as the second highest classiWcation accuracy for light intensity physical activity (67%). A ROC curve analysis of data from our participants yielded a CP-speciWc cut-point for MVPA that was lower than the Evenson cut-point (2,012 vs. 2,296 counts min¡1), however, the diVerence in classiWcation accuracy was not statistically signiWcant 94% (95% CI = 88.2-97.7%) vs. 91% (95% CI = 83.5-96.5%). In conclusion, among children and adolescents with CP, the ActiGraph is able to diVerentiate between diVerent intensities of walking. The use of the Evenson cut-points will permit the estimation of time spent in MVPA and allows comparisons to be made between activity measured in typically developing adolescents and adolescents with CP. © 2011 Springer-Verlag.

Accelerometer validity and placement for detection of changes in physical activity in dogs under controlled conditions on a treadmill

The objective of the research was to determine the optimal location and method of attachment for accelerometer-based motion sensors, and to validate their ability to differentiate rest and increases in speed in healthy dogs moving on a treadmill. Two accelerometers were placed on a harness between the scapulae of dogs with one in a pouch and one directly attached to the harness. Two additional accelerometers were placed (pouched and not pouched) ventrally on the dog's collar. Data were recorded in 1. s epochs with dogs moving in stages lasting 3. min each on a treadmill: (1) at rest, lateral recumbency, (2) treadmill at 0% slope, 3. km/h, (3) treadmill at 0% slope, 5. km/h, (4) treadmill at 0% slope, 7. km/h, (5) treadmill at 5% slope, 5. km/h, and; (6) treadmill at 5% slope, 7. km/h. Only the harness with the accelerometer in a pouch along the dorsal midline yielded statistically significant increases (P< 0.05) in vector magnitude as walking speed of the dogs increased (5-7. km/h) while on the treadmill. Statistically significant increases in vector magnitude were detected in the dogs as the walking speed increased from 5 to 7. km/h, however, changes in vector magnitude were not detected when activity intensity was increased as a result of walking up a 5% grade. Accelerometers are a valid and objective tool able to discriminate between and monitor different levels of activity in dogs in terms of speed of movement but not in energy expenditure that occurs with movement up hill.

Effects of four different single exercise sessions on lipids, lipoproteins, and lipoprotein lipase

The purpose of this study was to determine the threshold of exercise energy expenditure necessary to change blood lipid and lipoprotein concentrations and lipoprotein lipase activity (LPLA) in healthy, trained men. On different days, 11 men (age, 26.7 +/- 6.1 yr; body fat, 11.0 +/- 1.5%) completed four separate, randomly assigned, submaximal treadmill sessions at 70% maximal O-2 consumption. During each session 800, 1,100, 1,300, or 1,500 kcal were expended. Compared with immediately before exercise, high-density lipoprotein cholesterol (HDL-C) concentration was significantly elevated 24 h after exercise (P < 0.05) in the 1,100-, 1,300-, and 1,500-kcal sessions. HDL-C concentration was also elevated (P < 0.05) immediately after and 48 h after exercise in the 1,500-kcal session. Compared with values 24 h before exercise, LPLA. was significantly greater (P < 0.05) 24 h after exercise in the 1,100-, 1,300-, and 1,500-kcal sessions and remained elevated 48 h after exercise in the 1,500-kcal session. These data indicate that, in healthy, trained men, 1,100 kcal of energy expenditure are necessary to elicit increased HDL-C concentrations. These HDL-C changes coincided with increased LPLA.

Plasma lipid and lipoprotein responses during exercise

The purpose of this study was to examine the effect of prolonged exercise oil plasma lipid and lipoprotein concentrations and to identify caloric time-points where changes occurred. Eleven active male Subjects ran oil a treadmill at 70%,, of maximal fitness (VO2max) and expended 6 278.7 kilojoules (Kj) energy (1500 kcal). Blood samples were obtained at the 4185.8 Kj (1000 kcal) time-point during exercise and at each additional 418.6 Kj (100 kcal) expenditure until 6278.7 Kj was expended. After correcting for plasma volume changes, decreases in low-density lipoprotein cholesterol (LDL-C) were observed during exercise at time-points corresponding to 4604.4 and 5441.5 Kj (1100 and 1300 kcal) of energy expenditure, and immediately after exercise. Total cholesterol concentrations decreased significantly at exercise kilojoule expenditures of 4604.4, 5441.5 and 5860.1 (1100, 1300 and 1400 kcal). There were also exercise induced increases in high-density lipoprotein cholesterol (HDL-C) and HDL2-C concentrations immediately after exercise. Although acute lipid and lipoprotein changes are typically reported in the days following exercise, the Current data indicate that some lipoprotein concentrations change during acute exercise. Our data suggest that a threshold of exercise may be necessary to change lipoproteins during exercise. Future work Should identify potential mechanisms (lipoprotein lipase, cholesterol ester transport protein, LDL uptake) that alter lipoprotein concentrations during prolonged exercise.

Are mothers of young children really inactive?

Australian surveys have found that only 43% of women meet the current recommendation for regular moderate physical activity, and that women who are mothers of young children are even less likely to be adequately active for health benefit. These women spend a significant proportion of their day in occupational, household and care-giving activities, which may not be ‘captured’ in conventional physical activity surveys. The purpose of this study was to compare physical activity in young mothers and age-matched controls using three different measures of physical activity. 35 women (16 mothers of young children, M) and 19 age-matched comparison women (NM) completed a survey which asked about walking to and from places, and about moderate and vigorous activity in leisure time and at work (paid and unpaid). They also kept a detailed diary of all their activities for two week-days and two week-end days, and wore a pedometer (Yamax digiwalker) on these days. Each activity in the diary was assigned an energy expenditure (EE) score based on it's intensity (Compendium of Physical Activity) and time spent in that activity. There were no differences between M and NM for pedometer steps (M: 9270 sd 2947; NM: 9768 sd 3051) or for daily energy expenditure (EE) calculated from the diaries (M: 2029 sd 189; NM: 2015 sd 169 METS.mins) or survey (M: 2079 sd 448; NM: 1495 sd 325). There was a significant correlation between pedometer steps and daily METs.mins estimated from the diaries (r = 0.35, p = 0.04); however no relationship was observed between pedometer steps and EE from the survey (r = .09, p = .56). Further analysis of the individual survey items found pedometer steps to be related to EE from walking to and from places (r = .34) and leisure time (r = .31), but not work related activity (r = -.08). There were no significant relationships between EE computed from the diaries and any of the survey questions. The three activity measures indicate that the physical activity levels of the young mothers in our sample were comparable to age-matched non-mothers. The results of the correlation analyses highlight the difficulty of assessing low-intensity work-related physical activity via self-report. Supported by Australian Commonwealth Department of Health and Aged Care.