Estimation Of Total Energy Expenditure Research Articles

Total Energy Expenditure in Healthy Ambulatory Older Adults Aged ≥80 Years: A Doubly Labelled Water Study

Introduction: The life expectancy of older adults continues to increase; however, knowledge regarding their total energy requirements is lacking. This study aimed to compare the total energy expenditure (TEE) of older adults ≥80 years measured using doubly labelled water (DLW), with estimated TEE. The hypothesis was that the Mifflin, Ikeda, and Livingston equations will more closely estimate energy requirements than the commonly used Schofield equation. Methods: Resting metabolic rate (RMR) and TEE were measured using the reference methods of indirect calorimetry and DLW, respectively. Bland-Altman plots compared measured RMR and TEE with predicted RMR using equations (Mifflin, Ikeda, Livingston, Schofield) and predicted TEE (predicted RMR × physical activity level). Results: Twenty-one older adults (age range 80.7–90.1 years, BMI 26.1 ± 5.5 kg/m2) were included. The Schofield equation demonstrated the greatest bias from measured RMR, overestimating approximately up to double the mean difference (865 ± 662 kJ/day) compared with the three other equations. The Schofield equation exhibited the greatest bias (overestimation of 641 ± 1,066 kJ/day) compared with measured TEE. The other three equations underestimated TEE, with the least bias from Ikeda (37 ± 1,103 kJ/day), followed by Livingston (251 ± 1,108 kJ/day), and Mifflin (354 ± 1,140 kJ/day). Data are mean ± SD. Conclusions: In older adults ≥80 years, the Ikeda, Mifflin, and Livingston equations provide closer estimates of TEE than the widely used Schofield equation. The development of nutrition guidelines therefore should consider the utilization of equations which more accurately reflect age-specific requirements.

An observational study of feeding practice in ventilated patients with spinal cord injury

Cervical spinal cord injuries (CSCI) are frequently complicated by respiratory failure requiring prolonged invasive mechanical ventilation in the intensive care unit (ICU). Providing adequate nutrition may be an important factor in the recovery of respiratory muscle function for ventilator weaning. The aim of this study was to examine the practical implementation of a multi-disciplinary approach to nutrition combining indirect calorimetry and the modified Harris Benedict equation to achieve target rates of nutrition for patients with CSCI. A retrospective observational study was performed by collecting data of normal nutrition practice in a series of adult ventilated patients with CSCI admitted between 2014 and 2017 to the ICU. Administered calories by enteral nutrition and measured total energy expenditure (TEE) by indirect calorimetry were recorded for the first 3-weeks. Calculations were performed to measure the adequacy of calorie administration relative to TEE. Average daily temperatures and minute ventilation were recorded to support evidence for hypermetabolism. TEE estimates using the modified Harris Benedict equation were compared to indirect calorimetry measures for each patient. Sixteen patients were included in the study. Calorie administration rapidly increased to a plateau of 2300-2400kcal per day over the first four days. The median measured TEE by indirect calorimetry was initially high, starting at 3472kcal/day and decreasing to 2784kcal/day at three weeks. However, there was wide variation in energy expenditure amongst patients. Average daily temperatures and minute ventilation were high supporting hypermetabolism. Adequacy of calorie administration to TEE ranged between 76 and 86 percent through the study period. There was relatively wide variation when comparing estimates of TEE using the modified Harris Benedict equation versus indirect calorimetry. A multi-disciplinary approach to nutrition in ventilated patients with CSCI, incorporating indirect calorimetry, achieves target rates of nutrition. Our findings suggest that a hypermetabolic response may be common but variable in this population and subsequently both under and over feeding may be a risk if nutrition targets are not guided by indirect calorimetry. Further prospective research using protocoled indirect calorimetry measures would be beneficial to ascertain accurate energy requirements for this group of patients and also determine whether feeding to target influences weaning off the ventilator.

Prediction of energy expenditure during activities of daily living by a wearable set of inertial sensors

Physical inactivity is responsible for 7–10% of all premature deaths worldwide. Thus, valid, reliable and unobtrusive methods for monitoring activities of daily living (ADL) to predict total energy expenditure (TEE) is desired. Multiple methods exist to quantify TEE, but microelectromechanical systems (MEMSs) are the only method, which has shown promising results and are applicable for long-term monitoring in the field. However, no perfect method exists for predicting TEE on a daily basis. The present study evaluates TEE estimation based on a MEMS (Xsens Link system) taking gender and heart rate into account. Fifteen individuals performed seven ADL wearing the Xsens Link system, a heart rate belt and an oxygen mask. Multiple linear regression models were established for sedentary and dynamic activities and evaluated by leave-one-out cross-validation and compared with indirect calorimetry. The linear regression model showed better prediction for dynamic activities (adjusted R2 0.95±0.16) compared to sedentary activities (adjusted R2 0.61±0.19). The root-mean-square error for the TEE estimation ranged between 0.02 and 0.08 kJ/min/kg for the sedentary and dynamic models, respectively. The study showed a viable approach to predict TEE in ADL compared to previously published results. Further studies are warranted to reduce the number of sensors in the estimation of TEE.

Estimating energy expenditure from wrist and thigh accelerometry in free-living adults: a doubly labelled water study

Background:Many large studies have implemented wrist or thigh accelerometry to capture physical activity, but the accuracy of these measurements to infer activity energy expenditure (AEE) and consequently total energy expenditure (TEE) has not been demonstrated. The purpose of this study was to assess the validity of acceleration intensity at wrist and thigh sites as estimates of AEE and TEE under free-living conditions using a gold-standard criterion.Methods:Measurements for 193 UK adults (105 men, 88 women, aged 40–66 years, BMI 20.4–36.6 kg m−2) were collected with triaxial accelerometers worn on the dominant wrist, non-dominant wrist and thigh in free-living conditions for 9–14 days. In a subsample (50 men, 50 women) TEE was simultaneously assessed with doubly labelled water (DLW). AEE was estimated from non-dominant wrist using an established estimation model, and novel models were derived for dominant wrist and thigh in the non-DLW subsample. Agreement with both AEE and TEE from DLW was evaluated by mean bias, root mean squared error (RMSE), and Pearson correlation.Results:Mean TEE and AEE derived from DLW were 11.6 (2.3) MJ day−1 and 49.8 (16.3) kJ day−1 kg−1. Dominant and non-dominant wrist acceleration were highly correlated in free-living (r = 0.93), but less so with thigh (r = 0.73 and 0.66, respectively). Estimates of AEE were 48.6 (11.8) kJ day−1 kg−1 from dominant wrist, 48.6 (12.3) from non-dominant wrist, and 46.0 (10.1) from thigh; these agreed strongly with AEE (RMSE ~12.2 kJ day−1 kg−1, r ~ 0.71) with small mean biases at the population level (~6%). Only the thigh estimate was statistically significantly different from the criterion. When combining these AEE estimates with estimated REE, agreement was stronger with the criterion (RMSE ~1.0 MJ day−1, r ~ 0.90).Conclusions:In UK adults, acceleration measured at either wrist or thigh can be used to estimate population levels of AEE and TEE in free-living conditions with high precision.

GROWTH AND ENERGETICS OF ARCTIC TERN CHICKS (STERNA-PARADISAEA)

--We studied energy requirements of Arctic Tern chicks (Sterna paradisaea) in Ny ,idesund, Svalbard (79oN, 12oW) with special emphasis on thermoregulatory andactivity costs. We used doubly labeled water to estimate energy expenditure in the field (Ea•w) and made laboratory measurements ofthe different components of total energy requirement Comparison of DLW-estimates with oxygen consumption measurements howed that underestimated total energy expenditure 4.5-16.0% depending on the duration of the experiment. This was probably due to incorporation of isotopes in newly synthesized tissue. Field estimates of total energy expenditure from Ea• • were corrected accordingly. A tern chick model was used to measure operative temperature (T,). At midday T, reached values up to 20oC above ambient emperature (Ta) which ranged from 3.4-9.0oC. Based on the field estimates of Ea•w and Te and the laboratory measurements of basal metabolic rate and thermal conductance, we conclude that there was a considerable nergy saving (456 kJ = 26% of •eq) during the first 10-11 days of life, due to parental brooding. After this period, when the parents stop brooding, the energy required for thermoregulation accounted for only 16% of F_•q. From 10 days after hatching onwards, the energy needed for activity increased considerably, up to 50% of Er,q just before fledging (Day 20). Comparison of the energy budgets of Arctic Tern chicks with the more southerly occurring closely related Common Tern (S. hirundo; Ricklefs and White 1981) revealed only a slightly higher energy expenditure in the Arctic Tern chicks. Received 5 April 1988, accepted 23 November 1988. ENERGY expenditure of chicks living in arctic and antarctic environments has been considered to be dominated by the costs for thermoregulation. Many physiologists have focused on the ability of chicks to cope with low environmental temperatures (e.g. Maher 1964, Norton 1973, Aulie and Steen 1976, Boggs et al. 1977, Pedersen and Steen 1979, Bech et al. 1984, Jargensen and Blix 1985, Taylor 1985, Boersma 1986). However, the abiotic environment of chicks at high latitudes and the contribution of thermoregulatory costs to their total energy expenditure have not been quantified precisely. In addition to estimating thermoregulatory costs in relation to other energy requiring processes, interspecific comparison of closely related species from different latitudes should provide a better understanding of the influence of the polar environment on chick energy require-

MET-values of standardised activities in relation to body fat: studies in pregnant and non-pregnant women

BackgroundPhysical activity is associated with health in women. Published MET-values (MET: metabolic equivalent of task) may assess physical activity and energy expenditure but tend to be too low for subjects with a high total body fat (TBF) content and therefore inappropriate for many contemporary women. The MET-value for an activity is the energy expenditure of a subject performing this activity divided by his/her resting energy expenditure, often assumed to be 4.2 kJ/kg/h. Relationships between TBF and MET have been little studied although overweight and obesity is common in women. Available data indicate that MET-values decrease during pregnancy but more studies in pregnant contemporary women are needed.Subjects and methodsUsing indirect calorimetry we measured energy expenditure and assessed MET-values in women, 22 non-pregnant (BMI: 18–34) and 22 in gestational week 32 (non-pregnant BMI: 18–32) when resting, sitting, cycling (30 and 60 watts), walking (3.2 and 5.6 km/h) and running (8 km/h). Relationships between TBF and MET-values were investigated and used to predict modified MET-values. The potential of such values to improve calculations of total energy expenditure of women was investigated.ResultsThe resting energy expenditure was below 4.2 kJ/kg/h in both groups of women. Women in gestational week 32 had a higher resting energy metabolism (p < 0.001) and 7–15% lower MET-values (p < 0.05) than non-pregnant women. MET-values of all activities were correlated with TBF (p < 0.05) in non-pregnant women and modified MET-values improved estimates of total energy expenditure in such women. In pregnant women, correlations (p ≤ 0.03) between TBF and MET were found for running (8 km/h) and for walking at 5.6 km/h.ConclusionsOur results are relevant when attempts are made to modify the MET-system in contemporary pregnant and non-pregnant women. MET-values were decreased in gestational week 32, mainly due to an increased resting energy metabolism and studies describing how body composition affects the one MET-value (i.e. the resting energy metabolism in kJ/kg/h) during pregnancy are warranted. Studies of how pregnancy and TBF affect MET-values of high intensity activities are also needed. Corrections based on TBF may have a potential to improve the MET-system in non-pregnant women.

Using an Allometric Equation to Accurately Predict the Energy Expenditure of Children and Adolescents With Nonalcoholic Fatty Liver Disease.

Pediatric patients with nonalcoholic fatty liver disease (NAFLD) require targeted nutrition therapy that relies on calculating energy needs. Common energy equations are inaccurate in predicting resting energy expenditure (REE), influencing total energy expenditure (TEE) estimates. Equations based on allometric scaling are simple, accurate, void of subjective activity and/or stress factor bias, and they estimate TEE. To investigate the predictive accuracy of an allometric energy equation (AEE) in predicting TEE of children and adolescents with NAFLD. Retrospective study performed in a single institution. The allometric equation was used to calculate AEE, and the results were compared with TEE calculated using indirect calorimetry data (measured REE) multiplied by an activity factor (AF) of 1.5 or 1.7. Fifty-six patients with a mean age of 13 years were included in this study. The agreement between TEE (using an AF of 1.5) and AEE was -96 kcal/d (confidence interval, -29 to 221). The predictive accuracy of the allometric equation was not different between obese and nonobese patients. Allometric equations allow for accurate estimation of TEE in children with NAFLD.

Application of Bayesian analysis to the doubly labelled water method for total energy expenditure in humans.

RationaleThe doubly labelled water (DLW) method is the reference method for the estimation of free‐living total energy expenditure (TEE). In this method, where both 2H and 18O are employed, different approaches have been adopted to deal with the non‐conformity observed regarding the distribution space for the labels being non‐coincident with total body water. However, the method adopted can have a significant effect on the estimated TEE.MethodsWe proposed a Bayesian reasoning approach to modify an assumed prior distribution for the space ratio using experimental data to derive the TEE. A Bayesian hierarchical approach was also investigated. The dataset was obtained from 59 adults (37 women) who underwent a DLW experiment during which the 2H and 18O enrichments were measured using isotope ratio mass spectrometry (IRMS).ResultsTEE was estimated at 9925 (9106‐11236) [median and interquartile range], 9646 (9167–10540), and 9,638 (9220–10340) kJ·day−1 for women and at 13961 (12851–15347), 13353 (12651–15088) and 13211 (12653–14238) kJ·day−1 for men, using normalized non‐Bayesian, independent Bayesian and hierarchical Bayesian approaches, respectively. A comparison of hierarchical Bayesian with normalized non‐Bayesian methods indicated a marked difference in behaviour between genders. The median difference was −287 kJ·day−1 for women, and −750 kJ·day−1 for men. In men there is an appreciable compression of the TEE distribution obtained from the hierarchical model compared with the normalized non‐Bayesian methods (range of TEE 11234–15431 kJ·day−1 vs 10786–18221 kJ·day−1). An analogous, yet smaller, compression is seen in women (7081–12287 kJ·day−1 vs 6989–13775 kJ·day−1).ConclusionsThe Bayesian analysis is an appealing method to estimate TEE during DLW experiments. The principal advantages over those obtained using the classical least‐squares method is the generation of potentially more useful estimates of TEE, and improved handling of outliers and missing data scenarios, particularly if a hierarchical model is used.

Total energy expenditure of 10- to 12-year-old Japanese children measured using the doubly labeled water method

BackgroundTo establish Japanese children’s estimated energy requirements, total energy expenditure (TEE) data measured using the doubly labeled water (DLW) method is needed. This study aimed to 1) obtain basic TEE data from Japanese children measured using DLW (TEEDLW), 2) compare TEEDLW with TEE estimated by various estimation formulas to calculate their accuracy, and 3) develop a new equation to estimate TEE using body composition and pedometers.MethodsTEE was measured using DLW in 56 10- to 12-year-old Japanese children (33 boys, 23 girls). Physical activity level (PAL) was calculated by dividing TEEDLW by estimated resting energy expenditure. To assess their physical activity, participants wore pedometers during the 7-d DLW period. Total body water was calculated from 2H and 18O; fat-free mass (FFM) and fat mass (FM) were then determined.ResultsIn boys and girls of normal weight, TEEDLW was 2067 ± 230 kcal/d and 1830 ± 262 kcal/d, respectively. Average PAL was 1.58 ± 0.17. FFM was strongly related to TEE (r = 0.702, p < 0.01). After adjusting for FFM and FM, step count was significantly associated with TEE (r = 0.707, p < 0.01). The TEE estimation formula used in the Dietary Reference Intakes (DRI) for the United States and Canada estimated TEEDLW with high accuracy (bias: 2.0%) in both sexes. We developed new equations for TEE consisting of FFM and step count, which accounted for 68% and 65% of TEE variance in boys and girls, respectively: boys, 47.1 × FFM (kg) + 0.0568 × step count (steps/d) – 122, and girls, 55.5 × FFM (kg) + 0.0315 × step count (steps/d) - 117.ConclusionsThe TEE in 10- to 12-year-old Japanese children measured using DLW was approximately 7% lower for boys and 12% lower for girls compared to the current Japanese DRI. If PAL can be accurately determined, the equation in the DRI for the United States and Canada may be applicable to Japanese children. In addition, TEE could be predicted using FFM and step count.

Validation of energy intake from a web-based food recall for children and adolescents.

The purpose of this study was to validate estimated energy intake from a web-based food recall, designed for children and adolescents. We directly compared energy intake to estimates of total energy expenditure, calculated from accelerometer outputs, combined with data on weight and sex or resting energy expenditure prediction equations. Children (8–9 years) and adolescents (12–14 years) were recruited through schools in Norway in 2013 (N = 253). Results showed that more than one third (36–37%) were identified as under-reporters of energy. In contrast, only 2–4% were defined as over-reporters of energy. The mean energy intake was under-reported with -1.83 MJ/day for the entire study sample. Increased underestimation was observed for overweight and obese participants, the oldest age group (12–14 years), boys, those with parents/legal guardians with low educational level and those living in non-traditional families. In conclusion, energy intake from the web-based food recall is significantly underestimated compared with total energy expenditure, and should be used with caution in young people.

The crown joules: energetics, ecology, and evolution in humans and other primates.

Biological diversity is metabolic diversity: Differences in anatomy, physiology, life history, and activity reflect differences in energy allocation and expenditure among traits and tasks. Traditional frameworks in primatology, human ecology, public health, and paleoanthropology view daily energy expenditure as being more variable within than between species, changing with activity level but essentially fixed for a given body size. Growing evidence turns this view on its head. Total energy expenditure (kcal/d), varies relatively little within species, despite variation in physical activity; it varies considerably among species even after controlling for the effect of body size. Embracing this emerging paradigm requires rethinking potential trade-offs in energy allocation within and between species, assessing evidence of metabolic acceleration within lineages, and abandoning activity-based estimates of total energy expenditure. Difficult and exciting work lies ahead in the effort to untangle the ecological and evolutionary pressures shaping primate metabolic diversity.

The measurement and estimation of total energy expenditure in Japanese patients with ALS: a doubly labelled water method study

Appropriate nutritional therapy has not been established for patients with amyotrophic lateral sclerosis (ALS). Our objective was to measure the total energy expenditure (TEE) and determine an equation to estimate the energy requirements for Japanese patients with ALS. Twenty-six Japanese patients with ALS participated in the study. The TEE was measured using the doubly labelled water (DLW) method for a 14-day period. Using a range of clinical parameters and multiple regression analyses, we determined an adequate equation to calculate TEE. Results showed that the median value of total energy intake (TEI) was 1581 (interquartile 1278–1782) kcal/d. TEE and TEE/body weight were 1628 kcal/d (1352–1865) and 31.3 kcal/kg (29.2–34.4), respectively. The ratio of TEE/estimated TEE by the Harris-Benedict equation was 1.14 (1.09–1.26). The difference between TEI and TEE was –63 kcal (–221 – 122), and 15 patients (57.7%) showed a negative balance. From regression analyses, we determined an equation to estimate TEE using the resting metabolic rate estimated by the Harris-Benedict equation (RMR-HB) and scores of the revised ALS Functional Rating Scale (ALSFRS-R): TEE = (1.67 × RMR-HB) + (11.8 × ALSFRS-R) – 680 (p < 0.0001). In conclusion, energy expenditure of Japanese patients with ALS was higher than expected, and we proposed a preliminary equation to estimate TEE for future nutritional intervention.

Wearable multisensor and total energy expenditure estimation in young, adult and institutionalized elderly individuals: validation and practical recommendation

Older institutionalized individuals with reduced residual abilities are going to growth in number in the next years. Monitoring the daily energy expenditure may allow a correct dietary intake and an effective physical activity program, thus improving their life quality. Wearable multisensors (WMS) have been developed to estimate energy expenditure (EE), but, if not calibrated, their accuracy may become questionable. This study was aimed at evaluating WMS accuracy in EE estimation in institutionalized elderly people where individual calibration is difficult to perform. Twenty-three participants (age 48 ± 27 years; body mass 66.6 ± 12.7 kg; stature 1.69 ± 0.11 m; mean ± SD) were divided in young (YNG, 60 years; n = 7) individuals. EE at two different exercise intensities during cycling with the upper (UA) or lower limbs (LL) and walking was measured by indirect calorimetry (IC) and estimated by WMS. Estimated EE was always significantly lower than in IC in YNG and AD (P < 0.05). WMS underestimated EE in all conditions and the error increased with physical activity intensity. In YNG and ELD the correlation coefficient between measured and estimated EE improved during walking (R = 0.61 and R = 0.34 in YNG and ELD, respectively). In AD the best correlation occurred during LL (R = 0.78). Without individual calibration, WMS underestimated EE measured by IC during all physical activities, with the lower correlation coefficient in institutionalized individuals. An individual calibration of WMS seems to be mandatory to obtain accurate estimations of EE, especially in institutionalized elderly people.

Accelerometers are they accurate for the estimation of total energy expenditure over activities of daily living in stroke survivors?

The purpose of this study was to examine the accuracy of severals accelorometers commonly used in post stroke studies [1] to estimate the total energy expenditure (TEE) over activities of daily living. Thirty-eight participants (age: 65,7 ± 13,5; BMI 26,7 ± 6; Barthel Index: 69 ± 21) with various aged strokes were recruited and simultaneously monitored with accelerometers Armband Sensewear ® (multisensory device); Stayhealthy ® RT6TM; Actigraph GT3X + B ® (tri axial devices) and portable metabolic system (Cortex Métamax 3B ® ). The devices were placed on the non paretic ankle, hip and wrist as recommended. The participant performed four routine activities (transfers, manual tasks, walk, up and down stairs). TEE estimated by accelerometers was compared to the TEE measured by criterion method. The Armband Sensewear ® device obtained the better accuracy with a mean difference of 2,8% for the sum of all the activities. However, the lower and upper limits of agreement were high, around 100% of the TEE. All of the other devices had a statistic difference with the criterion method. This study reported strongly differences for the accuracy of accelerometers. The Armband Sensewear ® device was the better device even if the dispersion of its estimates was high and lead to caution with its use for estimation of TEE in daily living after stroke.

Application of Micro-Doppler Signatures for Estimation of Total Energy Expenditure in Humans for Walking/Running Activities

We investigate the feasibility of estimating the total energy expenditure (TEE) of a human for walking/running activities with micro-Doppler signatures. Doppler radar can capture micro-Doppler signatures produced from limb motions when a human moves. As the micro-Doppler signatures contain information regarding limb movement, TEE can be estimated by analyzing the Doppler spectrogram. To understand the relationship between the TEE and micro-Doppler signatures, basic arm and leg motions are measured by the Doppler radar, whereas a respiratory gas analyzer measures the volume of exchanged respiratory gas (O2 and CO2) to obtain a reference TEE. The area of micro-Doppler signatures in a spectrogram has been suggested to serve as key information to estimate TEE. For the verification of the suggested approach, TEE was measured for seven human subjects, who performed walking and running activities on a treadmill at five different speeds using both the Doppler radar and the respiratory gas analyzer. We confirm that strong correlations exist between the micro-Doppler area and the TEE. Finally, a regression model for walking and running activities is developed for a person. Then, the model calculates the TEE under two scenarios, and we find that the estimation errors are 13.2% and 12.3%.

Energy Expenditure in Humans and Other Primates: A New Synthesis

This review examines the proximate, ecological, and evolutionary determinants of energy expenditure in humans and primates, with an emphasis on empirical measurements of total energy expenditure (TEE). Body size is the main proximate determinant of TEE, both within and between species; physical activity, genetic variation, and endocrine regulation explain substantially less of the variation in TEE. Basal metabolism is the single largest component of TEE, far exceeding the cost of physical activity, digestion, growth and reproduction, and thermoregulation in most instances. Notably, differences in physical activity do not generally result in corresponding differences in TEE, undermining the utility of activity-based factorial estimates of TEE. Instead, empirical measurements of energy expenditure in humans and other primates suggest that the body adapts dynamically to long-term changes in physical activity, maintaining TEE within an evolved, and relatively narrow, physiological range.

The allocation and interaction model: A new model for predicting total energy expenditure of highly active humans in natural environments.

The purpose of this study was to develop a new model, the Allocation and Interaction Model (AIM), to better predict human total energy expenditure (TEE) among a group of highly active humans living in a variety of natural environments. AIM estimates were tested to determine if it produces more accurate TEE predictions than the Factorial Method. AIM includes metabolic cost terms for basal metabolic rate, thermoregulation, and the thermic effect of food, as well as more accurate activity cost estimations. AIM was tested using doubly labeled water and Flex-Heart Rate (Flex-HR)-measured TEEs of healthy, highly active adults (N = 59) participating in National Outdoor Leadership School semester-long courses. Data from a month-long pilot study (N = 6) were also included. AIM produced TEE estimates that were not significantly different from measured energy expenditure values. Overall, AIM came within 4.1% of measured values; the Factorial Method underestimated by over 25%. At TEEs greater than 3,000 kcalday(-1) , AIM underestimated TEE by 11% compared to 31.6% by the Factorial Method. Also, at TEEs greater than 3,000 kcalday(-1) , the Flex-HR method overestimated TEE by 17%. This analysis demonstrated that AIM is more accurate than the Factorial Method for predicting TEE across a range of climates and physical activity levels. This suggests that AIM should be used in place of the Factorial Method for estimating human TEE. Am. J. Hum. Biol. 28:372-380, 2016. © 2015 Wiley Periodicals, Inc.

Use of Smartphone Accelerometers and Signal Energy for Estimating Energy Expenditure in Daily-Living Conditions

This paper aims to introduce an efficient predictive function for total energy expenditure (TEE) in everyday life using dedicated mass-market sensors similar to those found in widespread smartphones and tablets. Our research encompasses the design of a TEE estimation model using the smartphone accelerometer with a new signal-to-energy transformation function. The main idea of this study consists in using the signal intensity instead of the activity recognition, since the signal intensity of the accelerometer is related to the amplitude of activities. The performance of the proposed function is estimated using a smartphone-based implementation and evaluated compared to references (the scenario associated with compendium MET values, Armband® and Actiheart®) under controlled conditions (CC) for 3.5 hours, and to both devices in free-living conditions (FLC) over a 12-hour monitoring period. The experiments were carried out with 12 volunteers in CC and 30 volunteers in FLC. The TEE mean gap in absolute value between the function and the three references (scenario, Armband® and Actiheart®) was 3.5%, 6.6% and 14.1% in CC, and 14.1% and 15.0% according to Armband® and Actiheart® in FLC, respectively.

Validity of the SenseWear Armband to Assess Energy Expenditure in Graded Walking

Background: Accurate assessments of physical activity and energy expenditure (EE) are needed to advance research on positive and negative graded walking. Purpose: To evaluate the validity of 2 SenseWear Armband monitors (Pro3 and the recently released Mini) during graded walking. Methods: Twenty healthy adults wore both monitors during randomized walking activities on a motorized treadmill at 7 grades (0%, ±5%, ±15%, and ±25%). Estimates of total EE from the monitors were computed using different algorithms and compared with values derived from indirect calorimetry methodology using a 2-way mixed model ANOVA (Device × Condition), correlation analyses and Bland-Altman plots. Results: There was no significant difference in EE between the 2 armbands in any of the conditions examined. Significant main effects for device and condition, as well as a consistent bias, were observed during positive and negative graded walking with a greater over- and under-estimation at higher slope. Conclusions: Both the armbands produced similar EE values and seem to be not accurate in estimation of EE during activities involving uphill and downhill walking. Additional work is needed to understand factors contributing to this discrepancy and to improve the ability of these monitors to accurately measure EE during graded walking.

Evaluation of the SenseWear Mini Armband to Assess Energy Expenditure During Pole Walking

The current study aimed to show the validity of a portable motion sensor, the SenseWear Armband (SWA), for the estimation of energy expenditure during pole walking. Twenty healthy adults (mean ± SD: age 30.1 ± 7.2 year, body mass 66.1 ± 10.6 kg, height 172.4 ± 8.0 cm, BMI 22.1 ± 2.4 kg · m(-2)) wore the armband during randomized pole walking activities at a constant speed (1.25 m · s(-1)) and at seven grades (0%, ± 5%, ± 15% and ± 25%). Estimates of total energy expenditure from the armband were compared with values derived from indirect calorimetry methodology (IC) using a 2-way mixed model ANOVA (Device × Slope), correlation analyses and Bland-Altman plots. Results revealed significant main effects for device, and slope (p < .025) as well as a significant interaction (p < .001). Significant differences between IC and SWA were observed for all conditions (p < .05). SWA generally underestimate the EE values during uphill PW by 0.04 kcal · kg(-1) · min(-1) (p < .05). Whereas, a significant overestimation has been detected during flat and downhill PW by 0.01 and 0.03 kcal · kg(-1) · min(-1) (p < .05), respectively. The Bland-Altman plots revealed bias of the armband compared with the indirect calorimetry at any condition examined. The present data suggest that the armband is not accurate to correctly detect and estimate the energy expenditure during pole walking activities. Therefore, the observed over- and under-estimations warrants more work to improve the ability of SWA to accurately measure EE for these activities.