Accuracy of a combined heart rate and motion sensor for assessing energy expenditure in free-living adults during a double-blind crossover caffeine trial using doubly labeled water as the reference method

No association between vascular aging and sarcopenia in healthy participants

BACKGROUND & AIMS

Several reports inform an association between vascular aging and sarcopenia. However, both conditions appear along with aging. Therefore, their association may be circumstantial and not casually linked. Our aim was to determine if individuals with higher-than-expected vascular aging have a higher frequency of sarcopenia.

METHODS

In 802 participants we calculated the association between pulse wave pressure and carotid intima media thickness and age and blood pressure, to derive predictive regression equations. In 161 of these participants we measured body composition by double beam X ray absorptiometry (DEXA), hand grip strength, rectus femoris thickness by ultrasound, activity energy expenditure by actigraphy and peak oxygen consumption and workload in an incremental exercise test. We calculated their expected values for pulse wave velocity and carotid intima media thickness and compared muscle mass and function between those with higher or lower than expected parameters. In 60 of these participants, we measured body composition sequentially to assess its change over time.

RESULTS

Age and blood pressure predicted the variance of pulse wave velocity and carotid intima media thickness with R2 values of 0.94-0.97 and 0.54 to 0.66, respectively. No differences in the frequency of sarcopenia and in muscle mass and strength were observed between participants with higher or lower than expected pulse wave velocity and carotid intima media thickness. In the group with sequential assessments, no differences in the change of muscle mass over time were observed in participants with and without accelerated vascular aging.

CONCLUSIONS

We were not able to find an association between vascular aging and sarcopenia.

Highlighting Unseen Activity Through 48-Hour Continuous Measurement in Subacute Stroke Rehabilitation: Preliminary Cohort Study

BACKGROUND

Motor impairments not only lead to a significant reduction in patient activity levels but also trigger a further deterioration in motor function due to deconditioning, which is an issue that is particularly pronounced during hospitalization. This deconditioning can be countered by sustaining appropriate activity levels. Activities that occur outside of scheduled programs, often overlooked, are critical in this context. Wearable technology, such as smart clothing, provides a means to monitor these activities.

OBJECTIVE

This study aimed to observe activity levels in patients who had strokes during the subacute phase, focusing on both scheduled training sessions and other nontraining times in an inpatient rehabilitation environment. A smart clothing system is used to simultaneously measure heart rate and acceleration, offering insights into both the amount and intensity of the physical activity.

METHODS

In this preliminary cohort study, 11 individuals undergoing subacute stroke rehabilitation were enrolled. The 48-hour continuous measurement system, deployed at admission and reassessed 4 weeks later, monitored accelerometry data for physical activity (quantified with a moving SD of acceleration [MSDA]) and heart rate for intensity (quantified with percent heart rate reserve). The measurements were performed using a wearable activity monitoring system, the hitoe (NTT Corporation and Toray Industries, Inc) system comprising a measuring garment (wear or strap) with integrated electrodes, a data transmitter, and a smartphone. The Functional Independence Measure was used to assess the patients' daily activity levels. This study explored factors such as differences in activity during training and nontraining periods, correlations with activities of daily living (ADLs) and age, and changes observed after 4 weeks.

RESULTS

A significant increase was found in the daily total MSDA after the 4-week program, with the average percent heart rate reserve remaining consistent. Physical activity during training positively correlated with ADL levels both at admission (ρ=0.86, P<.001) and 4 weeks post admission (ρ=0.96, P<.001), whereas the correlation between age and MSDA was not significant during training periods at admission (ρ=-0.41, P=.21) or 4 weeks post admission (ρ=-0.25, P=.45). Conversely, nontraining activity showed a negative correlation with age, with significant negative correlations with age at admission (ρ=-0.82, P=.002) and 4 weeks post admission (ρ=-0.73, P=.01).

CONCLUSIONS

Inpatient rehabilitation activity levels were positively correlated with ADL levels. Further analysis revealed a strong positive correlation between scheduled training activities and ADL levels, whereas nontraining activities showed no such correlation. Instead, a negative correlation between nontraining activities and age was observed. These observations suggest the importance of providing activity opportunities for older patients, while it may also suggest the need for adjusting the activity amount to accommodate the potentially limited fitness levels of this demographic. Future studies with larger patient groups are warranted to validate and further elucidate these findings.

Individually optimized estimation of energy expenditure in rescue workers using a tri-axial accelerometer and heart rate monitor

Objectives: This study aimed to provide an improved energy expenditure estimation for heavy-load physical labor using accelerometer data and heart rate (HR) measured by wearables and to support food preparation and supply management for disaster relief and rescue operations as an expedition team. Methods: To achieve an individually optimized estimation for energy expenditure, a model equation parameter was determined based on the measurements of physical activity and HR during simulated rescue operations. The metabolic equivalent of task (MET), which was measured by using a tri-axial accelerometer and individual HR, was used, where two (minimum and maximum) or three (minimum, intermediate, and maximum) representative reference points were selected for each individual model fitting. In demonstrating the applicability of our approach in a realistic situation, accelerometer-based METs and HR of 30 males were measured using the tri-axial accelerometer and wearable HR during simulated rescue operations over 2 days. Results: Data sets of 27 rescue operations (age:34.2 ± 7.5 years; body mass index (BMI):22.9 ± 1.5 kg/m2) were used for the energy expenditure estimation after excluding three rescue workers due to their activity type and insufficient HR measurement. Using the combined approach with a tri-axial accelerometer and HR, the total energy expenditure increased by 143% for two points and 133% for three points, compared with the estimated total energy expenditure using only the accelerometer-based method. Conclusion: The use of wearables provided a reasonable estimation of energy expenditure for physical workers with heavy equipment. The application of our approach to disaster relief and rescue operations can provide important insights into nutrition and healthcare management.

Quality Evaluation of Free-living Validation Studies for the Assessment of 24-Hour Physical Behavior in Adults via Wearables: Systematic Review

Background

Wearable technology is a leading fitness trend in the growing commercial industry and an established method for collecting 24-hour physical behavior data in research studies. High-quality free-living validation studies are required to enable both researchers and consumers to make guided decisions on which study to rely on and which device to use. However, reviews focusing on the quality of free-living validation studies in adults are lacking.

Objective

This study aimed to raise researchers’ and consumers’ attention to the quality of published validation protocols while aiming to identify and compare specific consistencies or inconsistencies between protocols. We aimed to provide a comprehensive and historical overview of which wearable devices have been validated for which purpose and whether they show promise for use in further studies.

Methods

Peer-reviewed validation studies from electronic databases, as well as backward and forward citation searches (1970 to July 2021), with the following, required indicators were included: protocol must include real-life conditions, outcome must belong to one dimension of the 24-hour physical behavior construct (intensity, posture or activity type, and biological state), the protocol must include a criterion measure, and study results must be published in English-language journals. The risk of bias was evaluated using the Quality Assessment of Diagnostic Accuracy Studies-2 tool with 9 questions separated into 4 domains (patient selection or study design, index measure, criterion measure, and flow and time).

Results

Of the 13,285 unique search results, 222 (1.67%) articles were included. Most studies (153/237, 64.6%) validated an intensity measure outcome such as energy expenditure. However, only 19.8% (47/237) validated biological state and 15.6% (37/237) validated posture or activity-type outcomes. Across all studies, 163 different wearables were identified. Of these, 58.9% (96/163) were validated only once. ActiGraph GT3X/GT3X+ (36/163, 22.1%), Fitbit Flex (20/163, 12.3%), and ActivPAL (12/163, 7.4%) were used most often in the included studies. The percentage of participants meeting the quality criteria ranged from 38.8% (92/237) to 92.4% (219/237). On the basis of our classification tree to evaluate the overall study quality, 4.6% (11/237) of studies were classified as low risk. Furthermore, 16% (38/237) of studies were classified as having some concerns, and 72.9% (173/237) of studies were classified as high risk.

Conclusions

Overall, free-living validation studies of wearables are characterized by low methodological quality, large variability in design, and focus on intensity. Future research should strongly aim at biological state and posture or activity outcomes and strive for standardized protocols embedded in a validation framework. Standardized protocols for free-living validation embedded in a framework are urgently needed to inform and guide stakeholders (eg, manufacturers, scientists, and consumers) in selecting wearables for self-tracking purposes, applying wearables in health studies, and fostering innovation to achieve improved validity.

5 days of time-restricted feeding increases fat oxidation rate but not affect postprandial lipemia: a crossover trial

Studies have revealed that time-restricted feeding affects the fat oxidation rate; however, its effects on the fat oxidation rate and hyperlipidemia following high-fat meals are unclear. This study investigated the effects of 5-day time-restricted feeding on the fat oxidation rate and postprandial lipemia following high fat meals. In this random crossover experimental study, eight healthy male adults were included each in the 5-day time-restricted feeding trial and the control trial. The meals of the time-restricted feeding trial were provided at 12:00, 16:00, and 20:00. The meals of the control trial were provided at 08:00, 14:00, and 20:00. The contents of the meals of both trials were the same, and the calories of the meals met the 24-h energy requirement of the participants. After 5 days of the intervention, the participants consumed high-fat meals on the sixth day, and their physiological changes were determined. The fasting fat oxidation rate (p < 0.001) and postprandial fat oxidation rate (p = 0.019) of the time-restricted feeding trial were significantly higher than those of the control trial. The 24-h energy consumption and postprandial triglyceride, blood glucose, insulin, glycerol, and free fatty acid concentrations of the two trials showed no significant differences (p > 0.05). The results revealed that 5 days of time-restricted feeding effectively increased the fasting and postprandial fat oxidation rate, but it did not affect postprandial lipemia.

Association of diurnal calorie trajectory with all-cause mortality: Findings from the National Health and Nutrition Examination Survey

BACKGROUND & AIMS

The effect of diurnal variation in energy intake on mortality has not been reported. We investigated the effect of diurnal calorie trajectory on all-cause mortality using data from the National Health and Nutrition Examination Survey (NHANES).

METHODS

Participants in the NHANES from 1999 to 2010 were analyzed. We calculated daily energy intake and the two-hourly calorie intake according to dietary interview questionnaires, in which timing of meals, as well as energy and nutritional components of each food were recorded. The daily energy intake and the two-hourly calorie intake were divided by body weight to determine tertiles of daily energy intake and diurnal calorie trajectories, respectively. Three diurnal calorie trajectories (reference group, excess dinner, and high-calorie) were identified. The mortality data were linked to the National Death Index through the end of 2011. Cox proportional hazards models were used to compare the overall mortality among different groups.

RESULTS

Among the 14,356 participants included in our analyses, 886 (6.2%) of them died after a median follow-up of 4.4 years. Daily energy intake tertiles were not associated with all-cause mortality in the fully adjusted model. In contrast, high-calorie trajectory was associated with a higher risk of mortality (hazard ratio 3.128, 95% CI 1.175 to 8.330, p = 0.024) compared with the reference group after adjustment for relevant factors.

CONCLUSIONS

A diurnal high-calorie trajectory was associated with a higher risk of mortality, compared with the reference group. The effect of a large evening meal on mortality merits further investigation.

Nonexercise Activity Thermogenesis-Induced Energy Shortage Improves Postprandial Lipemia and Fat Oxidation

(1) Background: This study investigated the effect of nonexercise activity thermogenesis on postprandial triglyceride (TG) concentrations; (2) Methods: Ten healthy males completed a sedentary trial (ST) and a physical activity trial (PA) in a random order separated by at least 7 days. After each intervention on day 1, the participants consumed a high-fat test meal on the next day. The blood samples and gas sample were observed in the fasted state and for 4 h after consuming the oral fat tolerance test; (3) Results: The postprandial TG concentrations of total (AUC) (p = 0.008) and incremental area under the curve (IAUC) (p = 0.023) in the plasma of participants in the PA trial were significantly lower than those in the plasma of participants in the ST trial. The postprandial fat oxidation rate AUC of the PA trial was significantly higher than that of the ST trial (p = 0.009); (4) Conclusions: The results of this study indicated that nonexercise energy expenditure decrease the postprandial TG concentration and increase the fat oxidation the next day.

Feasibility and Validity of the Actiheart Activity Monitor in Children Who Were Hospitalized With Cancer Coadmitted With Classmates: A RESPECT Study

PURPOSE

We investigated the feasibility of the Actiheart monitor to determine total daily energy expenditure and the validity of the Actiheart step test as an accurate estimate of peak oxygen uptake.

METHODS

(Equation is included in full-text article.)O2 peak was estimated with the Actiheart step test and compared with a cardiopulmonary exercise test. Total daily energy expenditure was measured using the Actiheart monitor on days with and without classmate coadmission.

RESULTS

Of 26 eligible measurement periods (15 children), 89% participated and 91% could participate safely; however, 35% fulfilled demands for valid monitoring. The percentage of children not completing the monitoring period was 10% (attrition) and adherence to classmate visits was 84%. Forty-eight percent of the measurement periods provided data, and only 27% was calibrated data. Actiheart step test significantly overestimated (Equation is included in full-text article.)O2 peak compared with the Cardio Pulmonary Exercise Test.

CONCLUSION

Measuring total daily energy expenditure using Actiheart is not feasible, nor implementable in children with cancer. Furthermore, the Actiheart step test is not a valid test to estimate (Equation is included in full-text article.)O2 peak in children with cancer.

A novel scaling methodology to reduce the biases associated with missing data from commercial activity monitors

Background

Commercial physical activity monitors have wide utility in the assessment of physical activity in research and clinical settings, however, the removal of devices results in missing data and has the potential to bias study conclusions. This study aimed to evaluate methods to address missingness in data collected from commercial activity monitors.

Methods

This study utilised 1526 days of near complete data from 109 adults participating in a European weight loss maintenance study (NoHoW). We conducted simulation experiments to test a novel scaling methodology (NoHoW method) and alternative imputation strategies (overall/individual mean imputation, overall/individual multiple imputation, Kalman imputation and random forest imputation). Methods were compared for hourly, daily and 14-day physical activity estimates for steps, total daily energy expenditure (TDEE) and time in physical activity categories. In a second simulation study, individual multiple imputation, Kalman imputation and the NoHoW method were tested at different positions and quantities of missingness. Equivalence testing and root mean squared error (RMSE) were used to evaluate the ability of each of the strategies relative to the true data.

Results

The NoHoW method, Kalman imputation and multiple imputation methods remained statistically equivalent (p<0.05) for all physical activity metrics at the 14-day level. In the second simulation study, RMSE tended to increase with increased missingness. Multiple imputation showed the smallest RMSE for Steps and TDEE at lower levels of missingness (<19%) and the Kalman and NoHoW methods were generally superior for imputing time in physical activity categories.

Conclusion

Individual centred imputation approaches (NoHoW method, Kalman imputation and individual Multiple imputation) offer an effective means to reduce the biases associated with missing data from activity monitors and maximise data retention.

Validity of Wrist-Worn photoplethysmography devices to measure heart rate: A systematic review and meta-analysis

Heart rate (HR), when combined with accelerometry, can dramatically improve estimates of energy expenditure and sleep. Advancements in technology, via the development and introduction of small, low-cost photoplethysmography devices embedded within wrist-worn consumer wearables, have made the collection of heart rate (HR) under free-living conditions more feasible. This systematic review and meta-analysis compared the validity of wrist-worn HR estimates to a criterion measure of HR (electrocardiography ECG or chest strap). Searches of PubMed/Medline, Web of Science, EBSCOhost, PsycINFO, and EMBASE resulted in a total of 44 articles representing 738 effect sizes across 15 different brands. Multi-level random effects meta-analyses resulted in a small mean difference (beats per min, bpm) of -0.40 bpm (95 confidence interval (CI) -1.64 to 0.83) during sleep, -0.01 bpm (-0.02 to 0.00) during rest, -0.51 bpm (-1.60 to 0.58) during treadmill activities (walking to running), while the mean difference was larger during resistance training (-7.26 bpm, -10.46 to -4.07) and cycling (-4.55 bpm, -7.24 to -1.87). Mean difference increased by 3 bpm (2.5 to 3.5) per 10 bpm increase of HR for resistance training. Wrist-worn devices that measure HR demonstrate acceptable validity compared to a criterion measure of HR for most common activities.

Association between activity energy expenditure and peak oxygen consumption with sarcopenia

Background

Sedentariness may be an important risk factor for sarcopenia. The aim of this work was to assess the association between muscle mass and strength and markers of usual physical activity such as activity energy expenditure and peak oxygen uptake.

Methods

Young and old participants were assessed measuring body composition by DEXA (double beam X ray absorptiometry), handgrip strength, peak oxygen consumption and workload during an exercise calorimetry in a braked cycle ergometer and a 72 h activity energy expenditure using Actiheart actigraphs. A heart rate/energy expenditure curve derived from the exercise calorimetry was used to calibrate each actigraph. Sarcopenia was defined as having an appendicular fat free mass index below 7.5 kg/m² and 5.6 kg/m² in men and women respectively, or a handgrip strength z score below 1, using local normal data or having both parameters below the cutoff points.

Results

We analyzed data from 192 assessments performed in participants aged 22 to 88 years (106 women). Sarcopenic participants (as determined by muscle mass, strength or both) had a significantly lower peak oxygen uptake and work load and a significantly lower activity energy expenditure. When analyzing lean mass and strength as continuous variables, peak oxygen consumption was a significant predictor of fat free mass in men. Among women, the association was observed only when percentage of muscle mass was expressed as a z score.

Conclusions

Activity energy expenditure and peak oxygen consumption are associated with a lower muscle mass and the presence of sarcopenia and should be considered as risk factors for this condition.

Accuracy in Wrist-Worn, Sensor-Based Measurements of Heart Rate and Energy Expenditure in a Diverse Cohort

The ability to measure physical activity through wrist-worn devices provides an opportunity for cardiovascular medicine. However, the accuracy of commercial devices is largely unknown. The aim of this work is to assess the accuracy of seven commercially available wrist-worn devices in estimating heart rate (HR) and energy expenditure (EE) and to propose a wearable sensor evaluation framework. We evaluated the Apple Watch, Basis Peak, Fitbit Surge, Microsoft Band, Mio Alpha 2, PulseOn, and Samsung Gear S2. Participants wore devices while being simultaneously assessed with continuous telemetry and indirect calorimetry while sitting, walking, running, and cycling. Sixty volunteers (29 male, 31 female, age 38 ± 11 years) of diverse age, height, weight, skin tone, and fitness level were selected. Error in HR and EE was computed for each subject/device/activity combination. Devices reported the lowest error for cycling and the highest for walking. Device error was higher for males, greater body mass index, darker skin tone, and walking. Six of the devices achieved a median error for HR below 5% during cycling. No device achieved an error in EE below 20 percent. The Apple Watch achieved the lowest overall error in both HR and EE, while the Samsung Gear S2 reported the highest. In conclusion, most wrist-worn devices adequately measure HR in laboratory-based activities, but poorly estimate EE, suggesting caution in the use of EE measurements as part of health improvement programs. We propose reference standards for the validation of consumer health devices (http://precision.stanford.edu/).

Usefulness of motion sensors to estimate energy expenditure in children and adults: a narrative review of studies using DLW

It is well documented that meeting moderate-to-vigorous physical activity guidelines of 150 min per week is protective against chronic disease, and this is likely explained by higher energy expenditure (EE). In opposition, sedentary behavior (low EE) seems to impair health outcomes. There are gold standard methods to measure EE such as the doubly labeled water (DLW) or calorimetry. These methods are highly expensive and rely on complex techniques. Motion sensors present a good alternative to estimate EE and have been validated against these reference methods. This review summarizes findings from previous reviews and the most recently published studies on the validity of different motion sensors to estimate physical activity energy expenditure (PAEE) and total energy expenditure (TEE) against DLW, and whether adding other indicators may improve these estimations in children and adults. Regardless of the recognized validity of motion sensors to estimate PAEE and TEE at the group level, individual bias is very high even when combining biometric or physiological indicators. In children, accelerometers explained 13% of DLW's PAEE variance and 31% of TEE variance. In adults, DLW's explained variance was higher, 29 and 44% for PAEE and TEE, respectively. There is no ideal device, but identifying postures seems to be relevant for both children and adults' PAEE estimates. The variance associated with the number of methodological choices that these devices require invite investigators to work with the raw data in order to standardize all these procedures and potentiate the accelerometer signal-derived information. Models that consider biometric covariates seem only to improve TEE estimations, but adding heart rate enhances PAEE estimations in both children and adults.

Validity of GT3X and Actiheart to estimate sedentary time and breaks using ActivPAL as the reference in free-living conditions

Sedentary time, specifically sitting/reclining, is a risk factor for many non-communicable diseases and premature mortality. Inclinometers have been used as a valid measurement of sedentary time and its patterns; however, there is a lack of information regarding the validity of alternative accelerometry and heart rate methods. The validity of GT3X and Actiheart in estimating changes in daily sedentary time and breaks, during free-living settings, using ActivPAL as the reference was examined. A crossover randomized control trial of an intervention that aimed to reduce ∼3 h/day of sitting time included 10 overweight/obese adults (37-65 years). Participants had a total of 74 valid days for the three devices (29 controls; 45 interventions). For ActivPAL, sedentary time was measured directly based upon posture (sitting/reclining); Actiheart, the presumed MET cutpoint for sedentary time (<1.5 METs) based on accelerometry+heart rate; GT3X, the traditional <100countsmin(-1). A break in sedentary time was defined as when the participants were above the aforementioned cutoffs. GT3X overestimated and Actiheart underestimated sedentary time (bias=135min; bias=-156min, respectively) and both methods overestimated breaks in sedentary time (bias=78; bias=235 breaks, respectively). The GT3X method was in better agreement with the ActivPAL sedentary time (r2=0.70; concordance correlation coefficient (CCC)=0.56) than the Actiheart (r2=0.24; CCC=0.31). The present results highlight the magnitude of potential errors in estimating sedentary time and breaks from common alternative methods other than ActivPAL. Because misclassification errors from the commonly used surrogates are potentially large, this raises concern that alternative methods used in many epidemiological observations may have underestimated the true effects caused by too much sitting (ClinicalTrials.govID:NCT02007681).