Evaluation of low-intensity physical activity by triaxial accelerometry

Objective: To develop regression‐based equations that estimate physical activity ratios [energy expenditure (EE) per minute/sleeping metabolic rate] for low‐to‐moderate intensity activities using total acceleration obtained by triaxial accelerometry. Research Methods and Procedures: Twenty‐one Japanese adults were fitted with a triaxial accelerometer while also in a whole‐body human calorimeter for 22.5 hours. The protocol time was composed of sleep (8 hours), four structured activity periods totaling 4 hours (sitting, standing, housework, and walking on a treadmill at speeds of 71 and 95 m/min, 2 × 30 minutes for each activity), and residual time (10.5 hours). Acceleration data (milligausse) from the different periods and their relationship to physical activity ratio obtained from the human calorimeter allowed for the development of EE equations for each activity. The EE equations were validated on the residual times, and the percentage difference for the prediction errors was calculated as (predicted value ? measured value)/measured value × 100. Results: Using data from triaxial accelerations and the ratio of horizontal to vertical accelerations, there was relatively high accuracy in identifying the four different periods of activity. The predicted EE (882 ± 150 kcal/10.5 hours) was strongly correlated with the actual EE measured by human calorimetry (846 ± 146 kcal/10.5 hours, r = 0.94 p < 0.01), although the predicted EE was slightly higher than the measured EE. Discussion: Triaxial accelerometry, when total, vertical, and horizontal accelerations are utilized, can effectively evaluate different types of activities and estimate EE for low‐intensity physical activities associated with modern lifestyles.     

Energy Expenditure Determined by Self-Reported Physical Activity Is Related to Body Fatness

BUCHOWSKI, MACIEJ S., KAREN M. TOWNSEND, KONG Y. CHEN, SARI A. ACRA, AND MING SUN. Energy expenditure determined by self-reported physical activity is related to body fatness. Obes. Res. 1999;7:23–33. Objective : Activity self-reports are a commonly used tool in assessing daily physical activity (PA) and associated energy expenditure (EE). This study examined the effect of relative body fatness (%BF) on differences between self-reported and measured duration and associated EE in healthy adults. Research Methods and Procedures: Men and women (n= 115, age 38±9 years), ranging in %BF from 7.9% to 58.9%, spent two separate days (normal and exercise) in a whole-room indirect calorimeter where EE was measured. While in the room calorimeter, subjects reported the type, intensity, and duration of each performed PA. The Compendium of Physical Activity was used to calculate the energy cost of each reported activity. The EE of all self-reported activities (EE_r) was categorized into four intensity levels, synchronized, and compared with EE from the room calorimeter (EE_m). Results : With increasing %BF, subjects significantly overestimated duration of more strenuous activities (≥4.5), while underestimating moderate activities (2.5 to 4.4 metabolic equivalents (METs)). Misreporting of duration and/or intensity caused an overestimation or underestimation of PA-associated EE at these levels. Reported EE sleep was lower than measured EE sleep, although both had similar durations. As a result, total EE_r was similar to EE_m. Discussion : Individual variability of daily total PA and associated EE generated from self-reports in adults is high. Persons with a higher %BF report duration and/or intensity of moderate to high levels of PA with lower accuracy than leaner individuals. We conclude using the Compendium of Physical Activity is not suitable for the accurate estimation of self-reported EE of AA in adults with a higher %BF.     

An artificial neural network model of energy expenditure using nonintegrated acceleration signals.

Accelerometers are a promising tool for characterizing physical activity patterns in free living. The major limitation in their widespread use to date has been a lack of precision in estimating energy expenditure (EE), which may be attributed to the oversimplified time-integrated acceleration signals and subsequent use of linear regression models for EE estimation. In this study, we collected biaxial raw (32 Hz) acceleration signals at the hip to develop a relationship between acceleration and minute-to-minute EE in 102 healthy adults using EE data collected for nearly 24 h in a room calorimeter as the reference standard. From each 1 min of acceleration data, we extracted 10 signal characteristics (features) that we felt had the potential to characterize EE intensity. Using these data, we developed a feed-forward/back-propagation artificial neural network (ANN) model with one hidden layer (12 x 20 x 1 nodes). Results of the ANN were compared with estimations using the ActiGraph monitor, a uniaxial accelerometer, and the IDEEA monitor, an array of five accelerometers. After training and validation (leave-one-subject out) were completed, the ANN showed significantly reduced mean absolute errors (0.29 +/- 0.10 kcal/min), mean squared errors (0.23 +/- 0.14 kcal(2)/min(2)), and difference in total EE (21 +/- 115 kcal/day), compared with both the IDEEA (P < 0.01) and a regression model for the ActiGraph accelerometer (P < 0.001). Thus ANN combined with raw acceleration signals is a promising approach to link body accelerations to EE. Further validation is needed to understand the performance of the model for different physical activity types under free-living conditions.     

Triaxial accelerometry for assessment of physical activity in young children

Objective: The purpose of the present study was to derive linear and non‐linear regression equations that estimate energy expenditure (EE) from triaxial accelerometer counts that can be used to quantitate activity in young children. We are unaware of any data regarding the validity of triaxial accelerometry for assessment of physical activity intensity in this age group. Research Methods and Procedures: EE for 27 girls and boys (6.0 ± 0.3 years) was assessed for nine activities (lying down, watching a video while sitting and standing, line drawing for coloring‐in, playing blocks, walking, stair climbing, ball toss, and running) using indirect calorimetry and was then estimated using a triaxial accelerometer (ActivTracer, GMS). Results: Significant correlations were observed between synthetic (synthesized tri‐axes as the vector), vertical, and horizontal accelerometer counts and EE for all activities (0.878 to 0.932 for EE). However, linear and non‐linear regression equations underestimated EE by >30% for stair climbing (up and down) and performing a ball toss. Therefore, linear and non‐linear regression equations were calculated for all activities except these two activities, and then evaluated for all activities. Linear and non‐linear regression equations using combined vertical and horizontal acceleration counts, synthetic counts, and horizontal counts demonstrated a better relationship between accelerometer counts and EE than did regression equations using vertical acceleration counts. Adjustment of the predicted value by the regression equations using the vertical/horizontal counts ratio improved the overestimation of EE for performing a ball toss. Discussion: The results suggest that triaxial accelerometry is a good tool for assessing daily EE in young children.     

Comparison of Methods for Achieving 24‐Hour Energy Balance in a Whole‐Room Indirect Calorimeter

Objective: To evaluate and compare methods for achieving 24‐hour energy balance in a whole‐room indirect calorimeter. Research Methods and Procedures: Twenty‐four‐hour energy expenditure (EE) for 34 healthy adults (16 women, 18 men) was measured in a calorimeter during a prestudy day and on a subsequent nonconsecutive assessment day (AD). Several methods for estimating EE on the AD using activity factors or regression equations with data available before the AD [anthropometrics, body composition, resting metabolic rate (RMR), sleeping metabolic rate (SMR) on prestudy day, 24‐hour EE on prestudy day] were compared for predictive accuracy. Results: Use of a 24‐hour calorimeter stay gave the smallest mean absolute error (119 ± 16 kcal/d) and smallest single maximum error (361 kcal/d). However, several other methods were only slightly, and not significantly, less accurate (e.g., mean absolute error = 131 ± 17, 140 ± 20, and 141 ± 22 kcal/d and greatest error = 384, 370, and 593 kcal/d for anthropometric, RMR, and SMR regression equations, respectively). Fat‐free mass alone and SMR with a simple activity factor were seen to be less accurate. Discussion: Our results indicate that there may be some improvement in achieving 24‐hour energy balance in a metabolic chamber by using a preceding 24‐hour calorimeter stay; that only slightly less accurate predictions can be obtained using a combination of anthropometric, body composition, and/or RMR measurements; and that there is little or no advantage in using SMR from a previous overnight calorimeter stay.     

Field validation of the MTI Actigraph and BodyMedia armband monitor using the IDEEA monitor

Objective: Accelerometers offer considerable promise for improving estimates of physical activity (PA) and energy expenditure (EE) in free‐living subjects. Differences in calibration equations and cut‐off points have made it difficult to determine the most accurate way to process these data. The objective of this study was to compare the accuracy of various calibration equations and algorithms that are currently used with the MTI Actigraph (MTI) and the Sensewear Pro II (SP2) armband monitor. Research Methods and Procedures: College‐age participants (n = 30) wore an MTI and an SP2 while participating in normal activities of daily living. Activity patterns were simultaneously monitored with the Intelligent Device for Estimating Energy Expenditure and Activity (IDEEA) monitor to provide an accurate estimate (criterion measure) of EE and PA for this field‐based method comparison study. Results: The EE estimates from various MTI equations varied considerably, with mean differences ranging from ?1.10 to 0.46 METS. The EE estimates from the two SP2 equations were within 0.10 METS of the value from the IDEEA. Estimates of time spent in PA from the MTI and SP2 ranged from 34.3 to 107.1 minutes per day, while the IDEEA yielded estimates of 52 minutes per day. Discussion: The lowest errors in estimation of time spent in PA and the highest correlations were found for the new SP2 equation and for the recently proposed MTI cut‐off point of 760 counts/min (Matthews, 2005). The study indicates that the Matthews MTI cut‐off point and the new SP2 equation provide the most accurate indicators of PA.     

Screening Physical Activity in Family Practice: Validity of the Spanish Version of a Brief Physical Activity Questionnaire

Objectives

The use of brief screening tools to identify inactive patients is essential to improve the efficiency of primary care-based physical activity (PA) programs. However, the current employment of short PA questionnaires within the Spanish primary care pathway is unclear. This study evaluated the validity of the Spanish version of a Brief Physical Activity Assessment Tool (SBPAAT).

Methods

A validation study was carried out within the EVIDENT project. A convenience sample of patients (n = 1,184; age 58.9±13.7 years; 60.5% female) completed the SBPAAT and the 7-day Physical Activity Recall (7DPAR) and, in addition, wore an accelerometer (ActiGraph GT3X) for seven consecutive days. Validity was evaluated by measuring agreement, Kappa correlation coefficients, sensitivity and specificity in achieving current PA recommendations with the 7DPAR. Pearson correlation coefficients with the number of daily minutes engaged in moderate and vigorous intensity PA according to the accelerometer were also assessed. Comparison with accelerometer counts, daily minutes engaged in sedentary, light, moderate, and vigorous intensity PA, total daily kilocalories, and total PA and leisure time expenditure (METs-hour-week) between the sufficiently and insufficiently active groups identified by SBPAAT were reported.

Results

The SBPAAT identified 41.3% sufficiently active (n = 489) and 58.7% insufficiently active (n = 695) patients; it showed moderate validity (k = 0.454, 95% CI: 0.402–0.505) and a specificity and sensitivity of 74.3% and 74.6%, respectively. Validity was fair for identifying daily minutes engaged in moderate (r = 0.215, 95% CI:0.156 to 0.272) and vigorous PA (r = 0.282, 95% CI:0.165 to 0.391). Insufficiently active patients according to the SBPAAT significantly reported fewer counts/minute (-22%), fewer minutes/day of moderate (-11.38) and vigorous PA (-2.69), spent fewer total kilocalories/day (-753), and reported a lower energy cost (METs-hour-week) of physical activities globally (-26.82) and during leisure time (-19.62).

Conclusions

The SBPAAT is a valid tool to identify Spanish-speaking patients who are insufficiently active to achieve health benefits.     

Comparison of two ActiGraph accelerometer generations in the assessment of physical activity in free living conditions

ABSTRACT: BACKGROUND: The aim of this study was to compare physical activity measured using GT1M ActiGraph and GT3X ActiGraph accelerometers in free living conditions. FINDINGS: Twenty-five adults wore GT1M and GT3X Actigraph accelerometers simultaneously during a typical weekday of activity. Data were uploaded from the monitor to a computer at the end of test (one day). Previously established thresholds were used for defining time spent at each level of physical activity, physical activity was assessed at varying intensities comparing data from the two accelerometers by ANOVA and Bland and Altman statistical analysis. The concordance correlation coefficient between accelerometers at each intensity level was 0.99. There were no significant differences between accelerometers at any of the activity levels. Differences between data obtained in minutes with the GT1M accelerometer and the GT3X monitor were to 0.56, 0.36, 0.52 and 0.44% for sedentary, light, moderate and vigorous, respectively. The Bland and Altman method showed good agreement between data obtained for the two accelerometers. CONCLUSIONS: Findings suggest that the two accelerometers provided similar results and therefore the GT3X may be used in clinical and epidemiological studies without additional calibration or validation studies.     

Moderate-to-vigorous physical activity among children: discrepancies in accelerometry-based cut-off points

Objective: To highlight the discrepancies in accelerometry cut‐off points of moderate‐to‐vigorous physical activity (MVPA) according to the definitions of Puyau et al. (MVPA^P) and Trost et al. (MVPA^T). Research Methods and Procedures: Forty‐five children from 8 to 11 years old were monitored with the ActiGraph (ActiGraph, LLC, Fort Walton Beach, FL) for 3 consecutive days. Daily time spent at MVPA obtained with MVPA^P was compared with that obtained with MVPA^T using variability, regression, and agreement statistics. Data were then discussed with regard to physical activity recommendations. Results: The mean daily time spent at MVPA^P (28 ± 18 minutes) was significantly lower (p < 10^?4) than that spent at MVPA^T (141 ± 39 minutes). The coefficient of determination between the two definitions was low (R² = 0.49 ± 0.71). There was a lack of agreement between the two definitions, with a mean error or bias of 113 min/d. Thirty‐four point eight percent and 100% of children underwent 30‐minute MVPA/d with MVPA^P and MVPA^T definitions, respectively. Discussion: Comparability between studies devoted to describing children's physical activity or to assessing interventions may lack consistency according to the definition, with a real risk of misclassification.     

Pre‐ to Postoperative Physical Activity Changes in Bariatric Surgery Patients: Self Report vs. Objective Measures

Bariatric surgery patients report significant pre‐ to postoperative increases in physical activity (PA). However, it is unclear whether objective measures would corroborate these changes. The present study compared self‐reported and accelerometer‐based estimates of changes in moderate‐to‐vigorous intensity PA (MVPA) from pre‐ (pre‐op) to 6 months postsurgery (post‐op). Twenty bariatric surgery (65% laparoscopic‐adjustable gastric banding, 35% gastric bypass) patients (46.2 ± 9.8 years, 88% female, pre‐op BMI = 50.8 ± 9.7 kg/m²) wore RT3 accelerometers as an objective measure of MVPA and completed the Paffenbarger Physical Activity Questionnaire (PPAQ) as a subjective measure before and 6 months after bariatric surgery. Time (min/week) spent in MVPA was calculated for the PPAQ and RT3 (≥1‐min and ≥10‐min bouts) at pre‐op and post‐op. Self‐reported MVPA increased fivefold from pre‐op to post‐op (44.6 ± 80.8 to 212.3 ± 212.4 min/week; P < 0.005). By contrast, the RT3 showed nonsignificant decreases in MVPA for both ≥1‐min (186.0 ± 169.0 to 151.2 ± 118.3 min/week) and ≥10‐min (41.3 ± 109.3 to 39.8 ± 71.3 min/week) bouts. At pre‐op, the percentage of participants who accumulated ≥150‐min/week of MVPA in bouts ≥10‐min according to the PPAQ and RT3 was identical (10%). However, at post‐op, 55% of participants reported compliance with the recommendation compared to 5% based on RT3 measurement (P = 0.002). Objectively‐measured changes in MVPA from pre‐op to 6 months post‐op appear to be much smaller than self‐reported changes. Further research involving larger samples is needed to confirm these findings and to determine whether self‐report and objective PA measures are differentially associated with surgical weight loss outcomes.     

Physical activity compliance: differences between overweight/obese and normal-weight adults

Objectives: Comparisons of physical activity measured by accelerometers in overweight/obese adults and their normal‐weight counterparts are limited. Compliance with the 2002 Institute of Medicine (IOM) exercise recommendations for 60 minutes of moderate‐intensity exercise daily has not been reported. The purpose of this study was to compare physical activity, as measured by accelerometers, in overweight/obese adults vs. normal‐weight controls and to assess compliance with recommendations for physical activity by the IOM in 2002 and by the Centers for Disease Control and Prevention and American College of Sports Medicine in 1995 for 30 minutes of moderate‐intensity activity, preferably all days of the week. Research Methods and Procedures: Sixty‐two overweight/obese subjects, BMI ≥ 25, included 31 adults, 12 men and 19 women, 25 to 69 years old, and their normal‐weight controls, BMI 18.5 to 24.9, matched for gender, age, and height. Body composition was assessed using DXA. Physical activity was measured with Actigraph accelerometers (MTI, Fort Walton Beach, FL) worn by each participant for 7 consecutive days. Results: Accelerometry data indicated that overweight/obese adults recorded ～60 counts per minute less per day and spent 21 minutes less engaged in moderate or greater intensity activity than their normal‐weight counterparts. Although 71% to 94% of those studied met 1995 recommendations, only 13% of overweight/obese subjects and 26% of normal‐weight participants met 2002 exercise recommendations. Discussion: These results suggest that daily minutes spent in moderate‐intensity activity or greater are associated with weight status and that the 2002 IOM recommendations may be difficult to meet even for normal‐weight individuals.     

Objectively Measured Intensity of Physical Activity and Adiposity in Middle‐Aged Women

Objective: The aim of this study was to evaluate the relationship between objectively measured physical activity (ACT), particularly intensity of physical activity (iACT), and body fat percentage (BF%) in 278 middle‐aged women. Secondary purposes were to ascertain the association between physical activity duration (dACT) and BF% and the extent to which potentially confounding factors, including total ACT, energy intake, body weight, and season of assessment, influenced the relationship between iACT and BF%. Research Methods and Procedures: A cross‐sectional design was used. Subjects were apparently healthy, 35 to 45 years old, premenopausal, nonsmokers, with BMIs < 30 kg/m². Approximately 90 percent were white, 81% were married, and 37% were college graduates. ACT was assessed using Computer Science and Application accelerometers worn for 7 consecutive days. The accelerometers recorded movement continuously, and activity counts were collapsed into 10‐minute epochs. Intensity was indexed using seven activity count cut‐off points, and duration was based on the number of 10‐minute epochs at each intensity level. BF% was assessed using multiple measurements in the Bod Pod. Energy intake was measured using 7‐day weighed diet records during the same week subjects wore the accelerometers. Results: BF% was strongly and inversely associated with iACT and dACT. Controlling for energy intake and body weight strengthened the relationships among iACT, dACT, and BF%. Control of total ACT weakened the association. Discussion: Engaging in higher intensity and/or longer duration ACT is associated with lower BF% compared with lower intensity and/or shorter durations of activity.     

Patterns of Objectively Measured Physical Activity in Normal Weight,Overweight, and Obese Individuals (20–85 Years): A Cross-Sectional Study

Background

The magnitude of the association between physical activity (PA) and obesity has been difficult to establish using questionnaires. The aim of the study was to evaluate patterns of PA across BMI-defined weight categories and to examine the independent contribution of PA on weight status, using accelerometers.

Methods

The study was a cross-sectional population-based study of 3,867 adults and older people aged 20–85 years, living in Norway. PA was assessed for seven consecutive days using the ActiGraph GT1M accelerometer. Anthropometrical data was self-reported and overweight and obesity was defined as having a body mass index (BMI) of 25–<30 and ≥30 kg/m², respectively.

Results

Overweight and obese participants performed less overall PA and PA of at least moderate intensity and took fewer steps, compared to normal weight participants. Although overall PA did not differ between weekdays and weekends, an interaction between BMI category and type of day was present, indicating a larger difference in overall PA between BMI categories on weekends compared to weekdays. Obese participants displayed 19% and 25% lower overall physical activity compared to normal weight participants, on weekdays and weekends, respectively. Participants in the most active quintile of overall PA had a 53% lower risk (OR 0.47, 95% CI: 0.37 to 0.60) for having a BMI above or below 25 kg/m², and a 71% lower risk (OR: 0.29, 95% CI: 0.20 to 0.44) for having a BMI above or below 30 kg/m².

Conclusions

Overweight and obese participants engaged in less overall PA and moderate and vigorous PA compared with normal weight individuals. The weight related differences in overall PA were most pronounced on the weekend and the risk of being overweight or obese decreases across quintiles of PA.     

A New Hand‐Held Indirect Calorimeter to Measure Postprandial Energy Expenditure

Objective: To verify the accuracy of a new hand‐held metabolic rate measuring device (MedGem) in quantifying postprandial energy expenditure (PP EE). MedGem measurements were compared to measurements obtained with a conventional indirect calorimeter (Delta‐Trac). Research Methods and Procedures: The resting metabolic rate of 15 healthy subjects was measured for 20 minutes using Delta‐Trac followed by a 10‐minute measurement period using MedGem. EE was again measured for 7 hours after consumption of a 2510‐kJ breakfast. Measurements were read from the Delta‐Trac for the initial 50 minutes of each hour followed by a single reading from the MedGem after 5 to 10 minutes of measurement. Measured EE was calculated as the average of the total measurement period for Delta‐Trac and for eight readings using MedGem; PP EE was calculated as the average of all measurements obtained after breakfast consumption. Results: There was no difference in resting metabolic rate between the two methods (6455.1 ± 417.6 vs. 6468.5 ± 337.2 kJ/d for Delta‐Trac and MedGem, respectively). Measured EE and PP EE values with Delta‐Trac (7019.1 ± 400.8 and 7099.8 ± 399.2 kJ/d, respectively) and MedGem (6775.6 ± 372.0 and 6819.5 ± 379.9 kJ/d, respectively) were not significantly different. There was no bias detected in any of the measurements made with MedGem compared with those of Delta‐Trac. Discussion: The new hand‐held EE measuring device can accurately track PP EE relative to a conventional indirect calorimetry system and, therefore, provides a new opportunity to assess PP EE in research settings and large‐scale trials.     

Quality Control Methods in Accelerometer Data Processing: Identifying Extreme Counts

Background

Accelerometers are designed to measure plausible human activity, however extremely high count values (EHCV) have been recorded in large-scale studies. Using population data, we develop methodological principles for establishing an EHCV threshold, propose a threshold to define EHCV in the ActiGraph GT1M, determine occurrences of EHCV in a large-scale study, identify device-specific error values, and investigate the influence of varying EHCV thresholds on daily vigorous PA (VPA).

Methods

We estimated quantiles to analyse the distribution of all accelerometer positive count values obtained from 9005 seven-year old children participating in the UK Millennium Cohort Study. A threshold to identify EHCV was derived by differentiating the quantile function. Data were screened for device-specific error count values and EHCV, and a sensitivity analysis conducted to compare daily VPA estimates using three approaches to accounting for EHCV.

Results

Using our proposed threshold of ≥ 11,715 counts/minute to identify EHCV, we found that only 0.7% of all non-zero counts measured in MCS children were EHCV; in 99.7% of these children, EHCV comprised < 1% of total non-zero counts. Only 11 MCS children (0.12% of sample) returned accelerometers that contained negative counts; out of 237 such values, 211 counts were equal to −32,768 in one child. The medians of daily minutes spent in VPA obtained without excluding EHCV, and when using a higher threshold (≥19,442 counts/minute) were, respectively, 6.2% and 4.6% higher than when using our threshold (6.5 minutes; p<0.0001).

Conclusions

Quality control processes should be undertaken during accelerometer fieldwork and prior to analysing data to identify monitors recording error values and EHCV. The proposed threshold will improve the validity of VPA estimates in children’s studies using the ActiGraph GT1M by ensuring only plausible data are analysed. These methods can be applied to define appropriate EHCV thresholds for different accelerometer models.     

Sedentary Behaviors,Physical Activity,and Metabolic Syndrome in Middle‐aged French Subjects

Objective: To study the relationships of time spent in sedentary occupations with the National Cholesterol Education Program—defined metabolic syndrome (MS), taking into account the habitual level of physical activity (PA). Research Methods and Procedures: This was a cross‐sectional analysis in 1902 men and 1932 women 50 to 69 years of age participating in the French Supplementation with Antioxidant Vitamins and Minerals study. We assessed past‐year PA, television watching or computer use, and reading during leisure with the Modifiable Activity Questionnaire. Subjects who performed at least 150 min/wk of moderate‐intensity PA (3 to 6 metabolic equivalent tasks) or 60 min/wk of vigorous PA (>6 metabolic equivalent tasks) were considered as meeting recommended levels. Results: The frequency of most MS components increased with time spent in front of a screen and decreased with increasing PA levels. The likelihood to have MS, adjusted for age, education, and smoking, was decreased by one‐third in subjects meeting moderate PA guidelines and by two‐thirds in subjects meeting vigorous PA recommendations [odds ratio (95% CI), 0.34 (0.17 to 0.66) in women, 0.44 (0.28 to 0.68) in men] compared with those with insufficient PA. Independently of PA levels, time spent in front of a screen was positively associated with the likelihood to have the MS in women [odds ratio (95% CI), 3.30 (2.04 to 5.34)], whereas in both sexes, no association was found with time spent reading. Discussion: The relationship of the MS with a sedentary lifestyle differs according to sex and type of sedentary occupation. These results suggest the need to assess selected indicators of sedentary behavior in preventive programs.     

Development and Validation of a Measurement System for Assessment of Energy Expenditure and Physical Activity in Prader-Willi Syndrome

CHEN, KONG Y., MING SUN, MERLIN G. BUTLER, TRAVIS THOMPSON, AND MICHAEL G. CARLSON. Development and validation of a measurement system for assessment of energy expenditure and physical activity in Prader—Willi syndrome. Obes Res. Objective: The morbid obesity associated with Prader—Willi syndrome (PWS) may result from either excessive energy intake or reduced energy expenditure (EE). In this report, we describe the development and validation of an Activity—Energy Measurement System (AEMS) to measure EE and physical activity components in an environment approximating free-living conditions. Research Methods and Procedures: The AEMS consists of a live-in, whole-room indirect calorimeter equipped with a novel force platform floor system to enable simultaneous measurements of EE, physical activity, and work efficiency during spontaneous activities and standardized exercises. Free-living physical activity and estimated free-living EE are measured using portable triaxial accelerometers individually calibrated in each subject during their stay in the AEMS. Results: Representative data from two PWS patients and two matched control (CTR) subjects displayed EE during their inactive lifestyles. Discussion: This combination of methods will allow the quantification of daily EE and its components, the amount and energy cost of physical activity, and the relationships between body composition and EE, in order to determine their roles in the development and maintenance of the morbid obesity in PWS.     

Estimation of Energy Expenditure from Physical Activity Measures: Determinants of Accuracy

Objective: To describe the determinants, specifically age, body mass index, percentage of body fat, and physical activity (PA) level, associated with over‐ and underestimation of energy expenditure (EE) using PA records and the Stanford Seven‐Day Physical Activity Recall (7DR) compared with doubly labeled water (DLW). Research Methods and Procedures: We collected PA measures on 24 males eating a controlled diet designed to maintain body weight, and we determined EE from DLW and estimated EE from PA records and 7DR. Results: Absolute differences in the estimation of EE between DLW and PA assessment methods were greater for the 7DR (30.6 ± 9.9%) than PA records (7.9 ± 3.2%). In PA records, overestimation of EE was greater with older age and higher body fatness; EE was overestimated by 16.7% among men 50 years and older compared with only 5.3% among men <40 years of age. For percentage of body fat, EE was overestimated by 19.7% among men with a percentage of body fat ≥30% compared with only 5.6% among men with a percentage of body fat <25%. A trend for less overestimation of EE with higher levels of PA (measured by DLW/basal metabolic rate [BMR]) also was observed in the PA records. In the 7DR, the estimates of EE varied widely and no trends were observed by age, percentage of body fat, and PA levels. Discussion: Estimation of EE from the 7DR is considerably more variable than from PA records. Factors related to age and percentage of body fat influenced the accuracy of estimated EE in the PA record. Additional studies are needed to understand factors related to accurate reporting of PA behaviors, which are used to estimate EE in free‐living adults.     

Validation and calibration of an accelerometer in preschool children

Objective: Obesity rates in young children are increasing, and decreased physical activity is likely to be a major contributor to this trend. Studies of physical activity in young children are limited by the lack of valid and acceptable measures. The purpose of this study was to calibrate and validate the ActiGraph accelerometer for use with 3‐ to 5‐year‐old children. Research Methods and Procedures: Thirty preschool children wore an ActiGraph accelerometer (ActiGraph, Fort Walton Beach, FL) and a Cosmed portable metabolic system (Cosmed, Rome, Italy) during a period of rest and while performing three structured physical activities in a laboratory setting. Expired respiratory gases were collected, and oxygen consumption was measured on a breath‐by‐breath basis. Accelerometer data were collected at 15‐second intervals. For cross‐validation, the same children wore the same instruments while participating in unstructured indoor and outdoor activities for 20 minutes each at their preschool. Results: In calibrating the accelerometer, the correlation between V?o ₂ (ml/kg per min) and counts was r = 0.82 across all activities. The only significant variable in the prediction equation was accelerometer counts (R² = 0.90, standard error of the estimate = 4.70). In the cross‐validation, the intraclass correlation coefficient between measured and predicted V?o ₂ was R = 0.57 and the Spearman correlation coefficient was R = 0.66 (p < 0.001). Cut‐off points for moderate‐ and vigorous‐intensity physical activity were identified at 420 counts/15 s (V?o ₂ = 20 mL/kg per min) and 842 counts/15 s (V?o ₂ = 30 mL/kg per min), respectively. When these cutpoints were applied to the cross‐validation data, percentage agreement, kappa, and modified kappa for moderate activity were 0.69, 0.36, and 0.38, respectively. For vigorous activity, the same measures were 0.81, 0.13, and 0.62. Discussion: Accelerometer counts were highly correlated with V?o ₂ in young children. Accelerometers can be appropriately used as a measure of physical activity in this population.     

Levels and Patterns of Objectively Assessed Physical Activity and Compliance with Different Public Health Guidelines in University Students

Background

Physical activity (PA) is associated with health enhancement. The aim of this study was to assess: 1) levels and patterns of PA in university students by using accelerometers; and 2) the percentage of fulfilment of PA recommendations for adults, according to different public health guidelines.

Methods

Observational cross-sectional study (Cuenca’s Adults Study) involving 296 (206 women) healthy Spanish university students aged 18–25 years old. Participants wore the ActiGraph GT1M accelerometer for seven consecutive days. Total PA, steps and time spent in sedentary time, light, moderate, vigorous, and moderate to vigorous PA (MVPA) was assessed, and the prevalence of sufficient PA was calculated according to various public health guidelines.

Results

No sex differences in total PA were found. University students were more sedentary during weekend days than weekdays (p<0.05). Only 30.3% of participants accumulated 30 min/day at least five days a week of MVPA. A total of 5.4% of students met the recommendation of 150 min/week of MVPA or 75 min/week of vigorous PA, in PA bouts of at least 10 min. using the same definition, but on five or more days a week, only 0.5% students were found to meet the recommendation. In addition, only 0.5% of students met the recommendation of 30 min/day of MVPA, at least five days a week and in bouts of at least 10 min. Finally, 28.1% of the students met the recommendation of 10,000 steps/day.

Conclusions

Our study shows a high incidence of sedentary time in university students. The number of students meeting PA recommendations significantly differed depending on the recommendation proposed. Specific strategies to promote PA in this population are necessary as well as an agreement as to which PA guidelines should be used.