Miguel A. Calabro

Accuracy of Armband Monitors for Measuring Daily Energy Expenditure in Healthy Adults

INTRODUCTION There is a need to develop accurate devices for measuring daily energy expenditure under free-living conditions, particularly given our current obesity epidemic. PURPOSE The purpose of the present study was to evaluate the validity of energy expenditure estimates from two portable armband devices, the SenseWear Pro3 Armband (SWA) monitor and the SenseWear Mini Armband (Mini) monitor, under free-living conditions. METHODS Participants in the study (30 healthy adults aged 24-60 yr) wore both monitors for 14 consecutive days, including while sleeping. Criterion values for total energy expenditure (TEE) were determined using doubly labeled water (DLW), the established criterion standard method for free-living energy expenditure assessment. RESULTS The average TEE estimates were within 112 kcal·d−¹ for the SWA and within 22 kcal·d−¹ for the Mini, but the absolute error rates (computed as the average absolute value of the individual errors) were similar for the two monitors (SWA = 8.1% ± 6.8%, Mini = 8.3% ± 6.5%). Using intraclass correlation (ICC) analysis, significant agreements were found between the SWA and DLW estimates of energy expenditure (ICC = 0.80, 95% CI = 0.89-0.70) and between the Mini and DLW (ICC = 0.85, 95% CI = 0.92-0.76). Graphical plots of the DLW TEE values against the difference between DLW and monitor estimates of TEE showed that the agreement was consistent across a range of TEE values. CONCLUSIONS The SenseWear Pro3 and the SenseWear Mini armbands show promise for accurately measuring daily energy expenditure under free-living conditions. However, more work is needed to improve the ability of these monitors to accurately measure energy expenditure at higher levels of expenditure.

Validation of the SenseWear Pro Armband Algorithms in Children

INTRODUCTION The SenseWear Pro Armband (SWA) has been shown to be a valid and practical tool to assess energy expenditure (EE) in adults. However, recent studies have reported significant errors in EE estimates when the algorithms are applied to children. The purpose of this study was to assess the validity of recently developed algorithms developed to take into account childrens unique movement patterns. METHODS Twenty-one healthy children (14 boys and 7 girls), averaging 9.4 (1.3) yr of age, participated in a range of activities while being monitored with the SWA and a metabolic analyzer. The activity protocol lasted 41 min and included resting, coloring, playing computer games, walking on a treadmill (2, 2.5, and 3 mph), and stationary bicycling. RESULTS The original algorithms overestimated EE by 32%, but average error with the newly developed algorithm was only 1.7%. There were no significant differences in overall estimates of EE across the 41-min trial (P > 0.05), but there was some variability in agreement for specific activities (average absolute difference in EE estimates was 13%). The average errors in EE estimates with the new algorithms were -20.7%, -4.0%, -4.9%, -0.9%, 0.6%, 3.5%, and -25.1% for resting, coloring, computer games, walking on a treadmill (2, 2.5, and 3 mph), and biking, respectively. Biking was the only activity with significant differences in EE estimations (P < 0.001). Average minute-by-minute correlations across individuals was r = 0.71 +/- 1.3 indicating that the relationships were consistent across individuals. CONCLUSIONS The newly developed algorithms demonstrate improved accuracy for assessing EE for typical activities in children-including accurate estimation of light activities.

Stride rate recommendations for moderate-intensity walking.

UNLABELLED Current physical activity guidelines recommend physical activity of at least moderate intensity to gain health benefits. Previous studies have recommended a moderate-intensity walking cadence of 100 steps per minute for adults, but the influence of height or stride length has not been investigated. PURPOSE the purpose of the current study was to determine the role of height and stride length in moderate-intensity walking cadence in adults. METHODS seventy-five adults completed three treadmill walking trials and three overground walking trials at slow, medium, and fast walking speeds while V˙O2 was measured using indirect calorimetry. Five stride length-related variables were also measured. RESULTS mixed model regression analysis demonstrated that height explained as much variability in walking intensity at a given cadence as did two different measures of leg length and two different stride length tests. CONCLUSIONS the previous general recommendations of 100 steps per minute were supported for use where a simple public health message is needed. Depending on height, moderate-intensity walking cadence can vary by more than 20 steps per minute, from 90 to 113 steps per minute for adults 198 to 152 cm tall, respectively. Height should therefore be taken into consideration for more precise evaluation or prescription of walking cadence in adults to provide health benefits.

Validation of Pattern-Recognition Monitors in Children Using Doubly Labeled Water.

PURPOSE Accurate assessments of physical activity and energy expenditure (EE) are needed to advance research on childhood obesity prevention. The objective of this study is to evaluate the validity of two SenseWear Armband monitors (the Pro3 (SWA) and the recently released Mini) (BodyMedia Inc., Pittsburgh, PA) under free-living conditions in a youth population. METHODS Twenty-eight healthy children age 10-16 yr wore both monitors for 14 consecutive days, including sleeping time. Estimates of total EE from the monitors were computed using two different algorithms (version 2.2, available in the SenseWear software 6.1 and 7.0, and the newly developed 5.0 algorithms). The EE estimates were compared with estimates derived from doubly labeled water (DLW) methodology using a three-way mixed model ANOVA (sex × monitor × algorithm), correlation analyses, and Bland-Altman plots. RESULTS The mixed-model ANOVA revealed nonsignificant gender and monitor main effects but a significant main effect for algorithm (P < 0.001). The mean absolute percentage error values were considerably lower with the 5.0 (SWA: 10.9%; Mini: 11.7%) than for the 2.2 algorithm (SWA: 20.7%; Mini: 18.3%). Correlations were high for all comparisons (>0.90), but the Bland-Altman plots revealed consistent bias (greater overestimation at higher EE values). The variance in the differences between methods that was attributable to the mean level of EE ranged from R(2) = 0.17 to R(2) = 0.44. The magnitude of random error (estimated as the SD of the residuals) ranged from 227 to 299 kcal, but values tended to be lower with the 2.2 algorithm and with the Mini monitor. CONCLUSIONS The newly developed SenseWear Armband 5.0 algorithms outperformed the version 2.2 algorithms for group comparisons, but additional work is needed to understand factors contributing to large individual variability.

Validity of 24-h physical activity recall: physical activity measurement survey.

PURPOSE The primary purpose of this study was to evaluate the validity of an interviewer-administered, 24-h physical activity recall (PAR) compared with that of the SenseWear Armband (SWA) for estimation of energy expenditure (EE) and moderate-to-vigorous physical activity (MVPA) in a representative sample of adults. A secondary goal was to compare measurement errors for various demographic subgroups (gender, age, and weight status). METHODS A sample of 1347 adults (20-71 yr, 786 females) wore an SWA for a single day and then completed a PAR, recalling the previous days physical activity. The participants each performed two trials on two randomly selected days across a 2-yr time span. The EE and MVPA values for each participant were averaged across the 2 d. Group-level and individual-level agreement were evaluated using 95% equivalence testing and mean absolute percent error, respectively. Results were further examined for subgroups by gender, age, and body mass index. RESULTS The PAR yielded equivalent estimates of EE (compared with those in the SWA) for almost all demographic subgroups, but none of the comparisons for MVPA were equivalent. Smaller mean absolute percent error values were observed for EE (ranges from 10.3% to 15.0%) than those for MVPA (ranges from 68.6% to 269.5%) across all comparisons. The PAR yielded underestimates of MVPA for younger, less obese people but overestimates for older, more obese people. CONCLUSIONS For EE measurement, the PAR demonstrated good agreement relative to the SWA. However, the use of PAR may result in biased estimates of MVPA both at the group and individual level in adults.

Objective and subjective measurement of energy expenditure in older adults: a doubly labeled water study

Background/Objectives:Objective and subjective measurement instruments have been used to estimate energy expenditure (EE) as alternatives to the doubly labeled water (DLW) methodology, but their relative validity for older adults remains uncertain. The purpose of this study was to validate an objective monitor (SenseWear Mini Armband) and a self-report instrument (7-Day Physical Activity Recall, 7D-PAR) relative to the DLW under free-living conditions in older adults.Subjects/Methods:Twenty-nine older adults (60–78 years) each wore the Mini for 14 consecutive days and completed two 7D-PARs after each week. For each measurement method, activity EE (AEE) was calculated as total EE (TEE)—measured resting metabolic rate (RMR)—diet induced thermogenesis (10% of TEE). TEE and AEE from the Mini and 7D-PAR were each compared with values from the DLW.Results:Equivalence testing indicated that estimates of TEE from the Mini and the 7D-PAR were statistically equivalent to those measured with DLW; however, differences were evident for estimates of AEE. The Mini had smaller mean absolute percent error for TEE (8.0%) and AEE (28.4%) compared with the 7D-PAR (13.8 and 84.5%, respectively) and less systematic bias in the estimates.Conclusions:The Mini and 7D-PAR provided reasonably valid estimates of TEE but large errors in estimating AEE. The Mini and 7D-PAR have the potential to accurately estimate TEE for older adults.