Comparison of heart rate monitoring with indirect calorimetry for energy expenditure evaluation

PurposeThe purpose of this study was to compare established methods with newly-developed methods for estimating the total energy expenditure (TEE).MethodsThe study subjects comprised 46 individuals, including 16 middle-aged men (mean age 51.4 years), 14 middle-aged women (mean age 49.9 years) and 16 young women (mean age 19.1 years). The TEE was estimated from 24-h heart rate (HR) data using newly-developed software (MoveSense HRAnalyzer 2011a, RC1, Suunto Oy, Vantaa, Finland), and was compared against the TEE determined using doubly labeled water (DLW). Agreement between the two methods was analyzed using Bland and Altman plots.ResultsThe HR method yielded similar TEE values as the DLW method at the group level, with an average of 8.6 kcal/day in the difference in the mean, but with large individual variations. Forty-four (96%) out of 46 subjects fell within ±2SD of the mean difference in TEE comparisons, and there was no tendency towards under- or over-estimation.ConclusionOur results indicate that the current software using HR analysis for the estimation of daily TEE needs further development for use with free-living individuals.     

An investigation of a novel three-dimensional activity monitor to predict free-living energy expenditure

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.     

An investigation of a novel three-dimensional activity monitor to predict free-living energy expenditure

Abstract

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.     

Walking for health in pregnancy: assessment by indirect calorimetry and accelerometry

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.     

Reliability and validity of the Flemish Physical Activity Computerized Questionnaire in adults

The purpose of this study was to investigate the test-retest reliability and concurrent validity of the Flemish Physical Activity Computerized Questionnaire (FPACQ) in employed/unemployed and retired people. The FPACQ was developed to assess detailed information on several dimensions of physical activity and sedentary behavior over a usual week. A triaxial accelerometer, the RT3 Triaxial Research Tracker (RT3), in combination with a written 7-day activity record, was used as the objective criterion measure. In employed/unemployed people, 2-week test-retest reliability for several activity variables calculated from the FPACQ was good to excellent with intraclass correlations (ICCs) ranging from .67 to .99. In retired people ICCs were lower but, except for time spent eating, still fair to excellent, ranging from .57 to .96. Except for time spent in leisure time activities for men and the average energy expenditure related to sports participation in women, correlations between the RT3 and the FPACQ generally supported the relative validity of the FPACQ for employed/unemployed people (r ranging from .37 to .88). Values for retired people were somewhat lower (r ranging from .15 to .85), but most variables still reached at least moderate correlations. Concerning absolute validity, the FPACQ generally overestimated physical activity and underestimated sedentary behavior compared to the RT3. From this study, it can be concluded that the FPACQ is a reliable and reasonably valid questionnaire for assessing different dimensions of physical activity and sedentary behavior.     

Reliability and Validity of the Flemish Physical Activity Computerized Questionnaire in Adults

The purpose of this study was to investigate the test-retest reliability and concurrent validity of the Flemish Physical Activity Computerized Questionnaire (FPACQ) in employed/unemployed and retired people. The FPACQ was developed to assess detailed information on several dimensions of physical activity and sedentary behavior over a usual week. A triaxial accelerometer, the RT3 Triaxial Research Tracker (RT3), in combination with a written 7-day activity record, was used as the objective criterion measure. In employed/unemployed people, 2-week test-retest reliability for several activity variables calculated from the FPACQ was good to excellent with intraclass correlations (ICCs) ranging from .67 to .99. In retired people ICCs were lower but, except for time spent eating, still fair to excellent, ranging from .57 to .96. Except for time spent in leisure time activities for men and the average energy expenditure related to sports participation in women, correlations between the RT3 and the FPACQ generally supported the relative validity of the FPACQ for employed/unemployed people (r ranging from .37 to .88). Values for retired people were somewhat lower (r ranging from .15 to .85), but most variables still reached at least moderate correlations. Concerning absolute validity, the FPACQ generally overestimated physical activity and underestimated sedentary behavior compared to the RT3. From this study, it can be concluded that the FPACQ is a reliable and reasonably valid questionnaire for assessing different dimensions of physical activity and sedentary behavior.     

Accuracy of three Android-based pedometer applications in laboratory and free-living settings

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.     

Validation of Accelerometer-Based Energy Expenditure Prediction Models in Structured and Simulated Free-Living Settings

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.     

Agreement in activity energy expenditure assessed by accelerometer and self-report in adolescents: Variation by sex,age, and weight status

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.     

Comparing the Validity and Output of the GT1M and GT3X Accelerometer in 5- to 9-Year-Old Children

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.     

Agreement in activity energy expenditure assessed by accelerometer and self-report in adolescents: variation by sex, age, and weight status

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.     

Validation of a wireless accelerometer network for energy expenditure measurement

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.     

Concurrent validation of the Actigraph gt3x+, Polar Active accelerometer,Omron HJ-720 and Yamax Digiwalker SW-701 pedometer step counts in lab-based and free-living settings

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.     

Comparing ActiGraph equations for estimating energy expenditure in older adults

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.     

Assessment of energy expenditure in children using the RT3 accelerometer

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 (VO2) 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 R2 = 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.     

中老年肥胖男性身体活动水平与能量消耗特征

以中老年男性肥胖人群为对象,同正常体重人群相比,研究肥胖人群自由生活下的身体活动水平、静息代谢、特定活动下的能耗代谢率、能源底物利用特征,为肥胖机制研究和干预措施制定提供参考。方法:14名50~60岁肥胖男性者(BMI>30)和15名体重正常者(BMI=23)使用加速度计RT3连续7天测量身体活动。之后使用Cortex MetaMax 3 B进行静息代谢和特定身体活动能耗的测量(坐、站、步行3.2 km/h,4.8 km/h,6.4 km/h)。结果:1)肥胖者的每日总能耗、身体活动能耗、中等强度以上活动能耗、中等以上活动的累计时间都显著大于对照组(P<0.05)。调整了体重因素后,肥胖者单位体重每日能耗/kg略低于对照组,而单位体重身体活动能耗显著高于对照组。2)肥胖组静息能耗高于体重正常组,若是以单位体重计算,静息代谢率显著低于体重正常组(P<0.05)。3)在坐、站、走活动中,肥胖组消耗的能量显著高于对照组(P<0.05)。若以公斤体重计算能耗,肥胖组坐姿和站姿的相对能耗略低于对照组,步行的相对能耗两组无差别。4)相同运动下两组人群安静平卧、坐、站、3.2 km/h和4.8 km/h步行时的呼吸交换率没有差异。6.4 km/h步行时,肥胖组的呼吸交换率显著高于体重正常组(P<0.05)。5)用回归统计法分析影响肥胖的危险因素,静息代谢率可以作为预测肥胖的因子。结论:肥胖人群的身体活动量和每日消耗能量不低于体重正常组,造成肥胖的原因很可能与能量消耗有关,较低的静息代谢率是肥胖发生的重要因素。此外,运动中脂肪氧化能力下降也可能是肥胖危险因素。     

Evaluation of Actical equations and thresholds to predict physical activity intensity in young children

This study examined the validity of current Actical activity energy expenditure (AEE) equations and intensity cut-points in preschoolers using AEE and direct observation as criterion measures. Forty 4–6-year-olds (5.3 ± 1.0 years) completed a ~150-min room calorimeter protocol involving age-appropriate sedentary behaviours (SBs), light intensity physical activities (LPAs) and moderate-to-vigorous intensity physical activities (MVPAs). AEE and/or physical activity intensity were calculated using Actical equations and cut-points by Adolph, Evenson, Pfeiffer and Puyau. Predictive validity was examined using paired sample t-tests. Classification accuracy was evaluated using weighted kappas, sensitivity, specificity and area under the receiver operating characteristic curve. The Pfeiffer equation significantly overestimated AEE during SB and underestimated AEE during LPA (P < 0.0125 for both). There was no significant difference between measured and predicted AEEs during MVPA. The Adolph cut-point showed significantly higher accuracy for classifying SB, LPA and MVPA than all others. The available Actical equation does not provide accurate estimates of AEE across all intensities in preschoolers. However, the Pfeiffer equation performed reasonably well for MVPA. Using cut-points of ≤6 counts · 15 s^?1, 7–286 counts · 15 s^?1 and ≥ 287 counts · 15 s^?1 when classifying SB, LPA and MVPA, respectively, is recommended.     

Predicting activity energy expenditure using the Actical activity monitor

This study developed algorithms for predicting activity energy expenditure (AEE) in children (n = 24) and adults (n = 24) from the Actical activity monitor. Each participant performed 10 activities (supine resting, three sitting, three house cleaning, and three locomotion) while wearing monitors on the ankle, hip, and wrist; AEE was computed from oxygen consumption. Regression analysis, used to create AEE prediction equations based on Actical output, varied considerably for both children (R2 = .45-.75; p < .001) and adults (R2 = .14-.85; p < .008). Most of the resulting algorithms accurately predicted accumulated AEE and time within light, moderate, and vigorous intensity categories (p > .05). The Actical monitor may be useful for predicting AEE and time variables at the ankle, hip, or wrist locations.     

Development of an accelerometer-based multivariate model to predict free-living energy expenditure in a large military cohort

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.     

Validity of the ActiGraph GT1M during walking and cycling

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.