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1.
The aim of this study was to assess the capability of the 3dNX accelerometer to predict energy expenditure in two separate, free-living cohorts. Twenty-three adolescents and 14 young adults took a single dose of doubly labelled water and wore a 3dNX activity monitor during waking hours for a 10-day period while carrying out their normal routines. Multiple linear regression with backward elimination was used to establish the strength of the associations between various indices of energy expenditure, physical activity counts, and anthropometric variables. 3dNX output accounted for 27% and 35% of the variance in the total energy expenditure of the adolescent and young adult cohort, respectively. The explained variance increased to 78%, with a standard error of estimate of 7%, when 3dNX output was combined with body composition variables. The 3dNX accelerometer can be used to predict free-living daily energy expenditure with a standard error of estimate of 1.65 MJ in adolescents and 1.52 MJ in young adults. The inclusion of anthropometric variables reduces the error to approximately 1 MJ. Although it remains to cross-validate these models in other populations, early indications suggest that the 3dNX provides a useful method of predicting energy expenditure in free-living individuals.  相似文献   

2.
The RT3 is a relatively new triaxial accelerometer that has replaced the TriTrac. The aim of this study was to validate the RT3 against doubly labeled water (DLW) in a free-living, mixed weight sample of adults. Total energy expenditure (TEE) was measured over a 15-day period using DLW. Activity-related energy expenditure (AEE) was estimated by subtracting resting energy expenditure and thermic effect of feeding from TEE. The RT3 triaxial accelerometer was worn over 14 consecutive days. TEE and AEE were estimated using the RT3 proprietary equation. Thirty-six adults ages 18–56 years (56% women) with an average weight of 75.9 kg (SD = 14.8) completed all measurements. Compared to DLW, the RT3 underestimated TEE by 539 kJ (4%) and AEE by 485 kJ (15%) on average. The RT3 provided a relatively accurate assessment of free-living activity-related energy expenditure at the group level and generally underestimated total and activity-related energy expenditure compared to DLW.  相似文献   

3.
Abstract

This study developed a multivariate model to predict free-living energy expenditure (EE) in independent military cohorts. Two hundred and eighty-eight individuals (20.6 ± 3.9 years, 67.9 ± 12.0 kg, 1.71 ± 0.10 m) from 10 cohorts wore accelerometers during observation periods of 7 or 10 days. Accelerometer counts (PAC) were recorded at 1-minute epochs. Total energy expenditure (TEE) and physical activity energy expenditure (PAEE) were derived using the doubly labelled water technique. Data were reduced to n = 155 based on wear-time. Associations between PAC and EE were assessed using allometric modelling. Models were derived using multiple log-linear regression analysis and gender differences assessed using analysis of covariance. In all models PAC, height and body mass were related to TEE (P < 0.01). For models predicting TEE (r 2 = 0.65, SE = 462 kcal · d?1 (13.0%)), PAC explained 4% of the variance. For models predicting PAEE (r 2 = 0.41, SE = 490 kcal · d?1 (32.0%)), PAC accounted for 6% of the variance. Accelerometry increases the accuracy of EE estimation in military populations. However, the unique nature of military life means accurate prediction of individual free-living EE is highly dependent on anthropometric measurements.  相似文献   

4.
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   

5.
The purpose of this study was to validate a wireless network of accelerometers and compare it to a hip-mounted accelerometer for predicting energy expenditure in a semi-structured environment. Adults (n = 25) aged 18–30 engaged in 14 sedentary, ambulatory, exercise, and lifestyle activities over a 60-min protocol while wearing a portable metabolic analyser, hip-mounted accelerometer, and wireless network of three accelerometers worn on the right wrist, thigh, and ankle. Participants chose the order and duration of activities. Artificial neural networks were created separately for the wireless network and hip accelerometer for energy expenditure prediction. The wireless network had higher correlations (r = 0.79 vs. r = 0.72, P < 0.01) but similar root mean square error (2.16 vs. 2.09 METs, P > 0.05) to the hip accelerometer. Measured (from metabolic analyser) and predicted energy expenditure from the hip accelerometer were significantly different for the 3 of the 14 activities (lying down, sweeping, and cycle fast); conversely, measured and predicted energy expenditure from the wireless network were not significantly different for any activity. In conclusion, the wireless network yielded a small improvement over the hip accelerometer, providing evidence that the wireless network can produce accurate estimates of energy expenditure in adults participating in a range of activities.  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.
Abstract

The agreement between self-reported and objective estimates of activity energy expenditure was evaluated in adolescents by age, sex, and weight status. Altogether, 403 participants (217 females, 186 males) aged 13–16 years completed a 3-day physical activity diary and wore a GT1M accelerometer on the same days. Partial correlations (controlling for body mass) were used to determine associations between estimated activity energy expenditure (kcal · min?1) from the diary and accelerometry. Differences in the magnitude of the correlations were examined using Fisher's r to z transformations. Bland–Altman procedures were used to determine concordance between the self-reported and objective estimates. Partial correlations between assessments of activity energy expenditure (kcal · min?1) did not differ significantly by age (13–14 years: r = 0.41; 15–16 years: r = 0.42) or weight status (normal weight: r = 0.42; overweight: r = 0.39). The magnitude of the association was significantly affected by sex (Δr = 0.11; P < 0.05). The agreement was significantly higher in males than in females. The relationship between activity energy expenditure assessed by the objective method and the 3-day diary was moderate (controlling for weight, correlations ranged between 0.33 and 0.44). However, the 3-day diary revealed less agreement in specific group analyses; it markedly underestimated activity energy expenditure in overweight/obese and older adolescents. The assessment of activity energy expenditure is complex and may require a combination of methods.  相似文献   

8.
This study compared accuracy of energy expenditure (EE) prediction models from accelerometer data collected in structured and simulated free-living settings. Twenty-four adults (mean age 45.8 years, 50% female) performed two sessions of 11 to 21 activities, wearing four ActiGraph GT9X Link activity monitors (right hip, ankle, both wrists) and a metabolic analyzer (EE criterion). Visit 1 (V1) involved structured, 5-min activities dictated by researchers; Visit 2 (V2) allowed participants activity choice and duration (simulated free-living). EE prediction models were developed incorporating data from one setting (V1/V2; V2/V2) or both settings (V1V2/V2). The V1V2/V2 method had the lowest root mean square error (RMSE) for EE prediction (1.04–1.23 vs. 1.10–1.34 METs for V1/V2, V2/V2), and the ankle-worn accelerometer had the lowest RMSE of all accelerometers (1.04–1.18 vs. 1.17–1.34 METs for other placements). The ankle-worn accelerometer and associated EE prediction models developed using data from both structured and simulated free-living settings should be considered for optimal EE prediction accuracy.  相似文献   

9.
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10.
Abstract

The aim of this study was to evaluate the utility of the RT3 accelerometer in young children, compare its accuracy with heart rate monitoring, and develop an equation to predict energy expenditure from RT3 output. Forty-two volunteers (mean age 12.2 years, s = 1.1) exercised at two horizontal and graded walking speeds (4 and 6 km · h?1, 0% grade and 6% grade), and one horizontal running speed (8 km · h?1, 0% grade), on a treadmill. Energy expenditure and oxygen consumption ([Vdot]O2) served as the criterion measures. Comparison of RT3 estimates (counts and energy expenditure) demonstrated significant differences at 4, 6, and 8 km · h?1 on level ground (P < 0.01), while no significant differences were noted between horizontal and graded walking at 4 and 6 km · h?1. Correlation and regression analyses indicated no advantage of vector magnitude over the vertical plane (X) alone. A strong relationship between RT3 estimates and indirect calorimetry across all speeds was obtained (r = 0.633–0.850, P < 0.01). A child-specific prediction equation (adjusted R 2 = 0.753) was derived and cross-validated that offered a valid energy expenditure estimate for walking/running activities. Despite recognized limitations, the RT3 may be a useful tool for the assessment of children's physical activity during walking and running.  相似文献   

11.
Activity monitors are frequently used to assess activity in many settings. But as technology advances, so do the mechanisms used to estimate activity causing a continuous need to validate newly developed monitors. The purpose of this study was to examine the step count validity of the Yamax Digiwalker SW-701 pedometer (YX), Omron HJ-720 T pedometer (OP), Polar Active accelerometer (PAC) and Actigraph gt3x+ accelerometer (AG) under controlled and free-living conditions. Participants completed five stages of treadmill walking (n = 43) and a subset of these completed a 3-day free-living wear period (n = 37). Manually counted (MC) steps provided a criterion measure for treadmill walking, whereas the comparative measure during free-living was the YX. During treadmill walking, the OP was the most accurate monitor across all speeds (±1.1% of MC steps), while the PAC underestimated steps by 6.7–16.0% per stage. During free-living, the OP and AG counted 97.5% and 98.5% of YX steps, respectively. The PAC overestimated steps by 44.0%, or 5,265 steps per day. The Omron pedometer seems to provide the most reliable and valid estimate of steps taken, as it was the best performer under lab-based conditions and provided comparable results to the YX in free-living. Future studies should consider these monitors in additional populations and settings.  相似文献   

12.
Abstract

The aims of this study were to (1) investigate the influence of general anthropometric variables, handball-specific anthropometric variables, and upper-limb power and strength on ball-throwing velocity in a standing position (νball), and (2) predict this velocity using multiple regression methods. Forty-two skilled male handball players (age 21.0 ± 3.0 years; height = 1.81 ± 0.07 m; body mass = 78.3 ± 11.3 kg) participated in the study. We measured general anthropometric variables (height, body mass, lean mass, body mass index) and handball-specific anthropometric parameters (hand size, arm span). Upper-limb dynamic strength was assessed using a medicine ball (2 kg) throwing test, and power using a one-repetition maximum bench-press test. All the variables studied were correlated with ball velocity. Medicine ball throwing performance was the best predictor (r = 0.80). General anthropometric variables were better predictors (r = 0.55–0.70) than handball-specific anthropometric variables (r = 0.35–0.51). The best multiple regression model accounted for 74% of the total variance and included body mass, medicine ball throwing performance, and power output in the 20-kg bench press. The equation formulated could help trainers, athletes, and professionals detect future talent and test athletes' current fitness.  相似文献   

13.
This study examined ageing and free-living daily physical activity effects on salivary human beta-defensin 2 (hBD2). A total of 168 healthy elderly and 26 healthy young volunteers underwent saliva sampling. Free-living step count, energy expenditure and activity durations at specific intensity levels (inactive, light, moderate and vigorous) were evaluated. The results show significantly lower salivary hBD2 secretion rates for elderly than for young participants (P < 0.05). Data from elderly participants were stratified by steps per day using quartiles (Q1–Q4) for distribution. Elderly in quartiles respectively showed step counts of 3145 ± 129 in Q1, 5294 ± 83 in Q2, 7001 ± 86 in Q3 and 10,236 ± 416 steps · day?1 in Q4. In elderly participants, significant differences were found in the mean step count, energy expenditure and activity duration with increasing pedometer-determined activity quartiles. hBD2 secretion rates were significantly higher for Q2, Q3 and Q4 than for Q1 (P < 0.05). Elderly participants in Q3 had the highest hBD2 secretion. In conclusion, these results suggest that moderate physical activity in daily living improves age-related impairment of oral immune function mediated by hBD2. For oral immune function enhancement and for prevention of upper respiratory tract infections in elderly people, we recommend accumulation of more than 7000 steps · day?1.  相似文献   

14.
The purpose of this study was to examine RT3 accelerometer activity counts and activity energy expenditure of 36 pregnant women at 20 and 32 weeks' gestation during treadmill walking and free-living conditions. During treadmill walking, oxygen consumption was collected, and activity energy expenditure was estimated for a 30-min walk at a self-selected walking pace. The number of min it would take a pregnant woman to meet exercise recommendations (i.e., kcal/week) were calculated. Preliminary activity count cut points at a self-selected walking pace were then estimated and applied in interpreting free-living data. For the treadmill walking condition, the self-selected walking pace significantly decreased from 20 to 32 weeks' gestation. Additionally, few women (< 12% each day) met physical activity guidelines in the free-living condition. Encouraging pregnant women to walk for 30-40 min per day at a self-selected walking pace may be an appropriate public health recommendation.  相似文献   

15.
Purpose: This study aimed to compare the energy expenditure and intensity of active video games to that of treadmill walking in children and adolescents. Method: Seventy-two boys and girls (aged 8–13 years) were recruited from local public schools. Energy expenditure and heart rate were measured during rest, during 3-km/hr, 4-km/hr, and 5-km/hr walks, and during active games (Adventure, Boxing I, Boxing II, and Dance). During walking and active games, we also assessed physical activity using an accelerometer. Results: The energy expenditure of the active games Adventure, Boxing I, Boxing II, and Dance was similar to that of treadmill walking at 5 km/hr in boys and girls. Heart rate was significantly higher for the game Adventure compared with walking at 3 km/hr, 4 km/hr, and 5 km/hr and the game Dance in both genders. The heart rate of girls during the games Adventure and Dance was significantly higher compared with boys. There was a statistically significant difference (p < .05, with an effect size ranging from 0.40 to 3.54) in the counts·min?1, measured through accelerometry, between activities. Conclusion: XBOX 360 Kinect games provide energy expenditure and physical activity of moderate intensity for both genders. The use of active video games can be an interesting alternative to increase physical activity levels.  相似文献   

16.
To determine the daily energy requirements of professional soccer players during a competitive season, we measured total energy expenditure in seven players (age 22.1 - 1.9 years, height 1.75 - 0.05 m, mass 69.8 - 4.7 kg; mean - s ) using the doubly labelled water method. Energy intake was simultaneously estimated from 7 day self-report dietary records. Mean total energy expenditure and energy intake were 14.8 - 1.7 MJ · day -1 (3532 - 408 kcal· day -1 ) and 13.0 - 2.4 MJ · day -1 (3113 - 581 kcal· day -1 ), respectively. Although there was a significant difference between total energy expenditure and energy intake ( P ? 0.01), there was a strong relationship between the two ( r = 0.893, P ? 0.01). Basal metabolic rate and recommended energy allowance calculated from the Recommended Dietary Allowances for the Japanese were 7.0 - 0.3 MJ ·day -1 (1683 - 81 kcal· day -1 ) and 15.6 - 0.8 MJ · day -1 (3739 - 180 kcal· day -1 ), respectively. A physical activity level (total energy expenditure/ basal metabolic rate) of 2.11 - 0.30 indicated that, during the competitive season, professional soccer players undertake much routine physical activity, similar to that of competitive athletes during moderate training. Energy intake estimated using dietary records was under-reported, suggesting that its calculation from these data does not predict energy expenditure in soccer players.  相似文献   

17.
The aim of this study was to assess physical activity (PA) awareness of adolescents and to identify anthropometric and psychosocial factors that can lead to under or overestimation of PA. This study included 2044 adolescents. Participants wore a uniaxial accelerometer for 7 days to measure PA and completed a self-rated questionnaire about PA. Adolescents were classified into four PA awareness subgroups (realistically active, overestimators, underestimators and realistically inactive) according to the self-rated and objective assessment of PA. Characteristics and psychosocial factors of the self-rated physically active groups were compared using bivariate and multivariate mixed logistic regression models. Forty-five percent of adolescents reported their PA levels correctly (34.8% realistically active and 10.1% realistically inactive). Among the 59.4% who were objectively inactive, 82.9% tended to overestimate their PA level. Adolescents who overestimated their PA level were older (P < .05), had more support from mother and a best friend (P < .05) and had higher cardiorespiratory fitness (P < .001) compared with those who were realistically active. A significant number of adolescents believe that they are physically active when they are not. Improving awareness, especially in the high-risk groups identified here, might help to bring about behavioural changes in physically inactive adolescents.  相似文献   

18.
The primary aim was to examine the criterion and construct validity and test–retest reliability of the Lifesource XL-18 pedometer (A&D Medical, Toronto, ON, Canada) for measuring steps under controlled and free-living activities. The influence of body mass index, waist size and walking speed on the criterion validity of XL-18 was also explored. Forty adults (35–74 years) performed a 6-min walk test in the controlled condition, and the criterion validity of XL-18 was assessed by comparing it to steps counted manually. Thirty-five adults participated in the free-living condition and the construct validity of XL-18 was assessed by comparing it to Yamax SW-200 (YAMAX Health & Sports, Inc., San Antonio, TX, USA). During the controlled condition, XL-18 did not significantly differ from criterion (P > 0.05) and no systematic error was found using Bland–Altman analysis. The accuracy of XL-18 decreased with slower walking speed (P = 0.001). During the free-living condition, Bland–Altman analysis revealed that XL-18 overestimated daily steps by 327 ± 118 than Yamax (P = 0.004). However, the absolute percent error (APE) (6.5 ± 0.58%) was still within an acceptable range. XL-18 did not differ statistically between pant pockets. XL-18 is suitable for measuring steps in controlled and free-living conditions. However, caution may be required when interpreting the steps recorded under slower speeds and free-living conditions.  相似文献   

19.
This study examined the validity of the Actical accelerometer step count and energy expenditure (EE) functions in healthy young adults. Forty-three participants participated in study 1. Actical step counts were compared to actual steps taken during a 200 m walk around an indoor track at self-selected pace and during treadmill walking at different speeds (0.894, 1.56 and 2.01 m · s–1) for 5 min. The Actical was also compared to three pedometers. For study 2, 15 participants from study 1 walked on a treadmill at their predetermined self-selected pace for 15 min. Actical EE was compared to EE measured by indirect calorimetry. One-way analysis of variance and t-tests were used to examine differences. There were no statistical difference between Actical steps and actual steps in self-selected pace walking and during treadmill walking at moderate and fast speeds. During treadmill walking at slow speed, the Actical step counts significantly under predicted actual steps taken. For study 2, there was no statistical difference between measured EE and Actical-recorded EE. The Actical provides valid estimates of step counts at self-selected pace and walking at constant speeds of 1.56 and 2.01 m · s–1. The Actical underestimates EE of walking at constants speeds ≥1.38 m · s–1.  相似文献   

20.
This study examines the accuracy of three popular, free Android-based pedometer applications (apps), namely, Runtastic (RT), Pacer Works (PW), and Tayutau (TY) in laboratory and free-living settings. Forty-eight adults (22.5 ± 1.4 years) completed 3-min bouts of treadmill walking at five incremental speeds while carrying a test smartphone installed with the three apps. Experiment was repeated thrice, with the smartphone placed either in the pants pockets, at waist level, or secured to the left arm by an armband. The actual step count was manually counted by a tally counter. In the free-living setting, each of the 44 participants (21.9 ± 1.6 years) carried a smartphone with installed apps and a reference pedometer (Yamax Digi-Walker CW700) for 7 consecutive days. Results showed that TY produced the lowest mean absolute percent error (APE 6.7%) and was the only app with acceptable accuracy in counting steps in a laboratory setting. RT consistently underestimated steps with APE of 16.8% in the laboratory. PW significantly underestimated steps when the smartphone was secured to the arm, but overestimated under other conditions (APE 19.7%). TY was the most accurate app in counting steps in a laboratory setting with the lowest APE of 6.7%. In the free-living setting, the APE relative to the reference pedometer was 16.6%, 18.0%, and 16.8% for RT, PW, and TY, respectively. None of the three apps counted steps accurately in the free-living setting.  相似文献   

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