Activity Energy Expenditure Research Articles

Energy Availability in Female Collegiate Beach Volleyball Athletes.

Willingham, BD, Daou, M, VanArsdale, J, Thomas, M, and Saracino, PG. Energy availability in female collegiate beach volleyball athletes. J Strength Cond Res 38(11): 1941-1950, 2024-Low energy availability (LEA) is a present risk for many female athletes. Yet, the literature on LEA is often reliant on single, short-term, snapshots, which may not be reflective of the chronic energy balance surrounding female athletes in sport. Therefore, the purpose of this study was to establish the current prevalence of LEA in female collegiate beach volleyball athletes during the preseason and across the competitive season. One-way repeated measures analysis of variance was used to compare measures of EA (i.e., dietary intake, activity energy expenditure [EE], body composition) and EE (i.e., resting metabolic rate and thermic effect of feeding) at 4 timepoints-once in the preseason (i.e., Fall), and 3 times across the 10-week competitive season in Spring (i.e., week 1, week 5, and week 9). Significance was set at p ≤ 0.05. Although mean EA was in the subclinical zone (i.e., 30-45 kcal·kg FFM-1·d-1) at each timepoint, the prevalence of LEA for individuals was 30.8% in the preseason, 37.5% at week 1, 25.0% at week 5, and 62.5% at week 9. Further, carbohydrate intake was below the recommended range for power athletes at each timepoint, suggesting that female beach volleyball athletes with LEA may benefit from increasing carbohydrate intake. Despite no statistical differences in body mass across the season (p = 0.577), there was a trend for increasing fat-free mass (p = 0.062) as the season progressed. Importantly, LEA is not a team-wide condition but an individual one. Therefore, approaches to mitigate LEA should be individualized.

Modulators of Energy Expenditure Accuracy in Adults with Overweight or Obesity: E-MECHANIC Secondary Analyses.

American College of Sports Medicine (ACSM) metabolic equations are used to estimate energy expenditure (EE) of physical activity and prescribe aerobic exercise to meet EE requirements. Limited evidence supports their accuracy in sedentary adults with overweight or obesity during controlled exercise interventions. The purpose of this study was to compare EE estimated by the ACSM walking equation versus EE measured by indirect calorimetry during a 24-week aerobic exercise intervention, and identify potential modulators for their accuracy. Data from the exercising groups (8 or 20 kcal·kg body weight-1·week-1) of the E-MECHANIC study were utilized in this ancillary analysis (N = 103). Every 2 weeks for the initial 8 weeks and monthly thereafter, EE was measured via indirect calorimetry during absolute (2 mph, 0% grade) and relative (65-85% VO2peak) workload exercise. Resting metabolic rate, VO2peak, and body composition were assessed at baseline and follow-up. An EE offset factor (EOF) was calculated to express measured EE as a percentage of the estimated EE at each workload (EOF < 100% represents an overestimation of ACSM estimated EE). The accuracy of the equation decreased with increasing exercise workload (0.44%, 9.2%, and 20.3% overestimation at absolute, relative, and maximal workloads, respectively, at baseline) and overestimation of EE was greater after the exercise intervention. Furthermore, race, sex, age, fat mass, and VO2peak were identified as modulators for equation accuracy. Greater overestimation of EE was observed in Black compared to white females, particularly at lower exercise workloads. These findings support future efforts to improve the accuracy of metabolic equations, especially in diverse populations. Researchers should account for exercise efficiency adaptations when using metabolic equations to prescribe exercise precisely.

Combined associations of physical activity, diet quality and their changes over time with mortality: findings from the EPIC-Norfolk study, United Kingdom

BackgroundPhysical activity (PA) and diet quality have each been shown to be inversely associated with mortality but their combined impact on longevity has been less explored, particularly when considering their changes over time. This study aimed to examine the separate and combined associations of PA, diet quality and their changes over time with mortality outcomes.MethodsA prospective cohort study was performed on 9349 adults aged 40 to 79 years from the population-based European Prospective Investigation into Cancer in Norfolk Study, with repeated measurements of PA and diet (from 1993 till 2004) and subsequent follow-up till 2022 (median follow-up 18.8 years). Validated questionnaires were used to derive physical activity energy expenditure (PAEE) as a proxy of total PA and adherence to the Mediterranean diet score (MDS, range 0–15 points) as an indicator of overall diet quality, and their changes over time (∆PAEE and ∆MDS). Cox regression models adjusted for potential confounders and mediators were used to estimate hazard ratios (HRs) and 95% CIs.ResultsOver 149,681 person-years of follow-up, there were 3534 deaths. In adjusted models, for each 1-SD difference in baseline PAEE (4.64 kJ/kg/day), ∆PAEE (0.65 kJ/kg/day per year), baseline MDS (1.30 points) and ∆MDS (0.32 points per year), HRs (95% CI) for all-cause mortality were 0.90 (0.86 to 0.94), 0.89 (0.85 to 0.93), 0.95 (0.91 to 0.99) and 0.93 (0.90 to 0.97), respectively. Compared with participants with sustained low PAEE (< 5 kJ/kg/day) and low MDS (< 8.5 points), those with sustained high PAEE and high MDS had lower all-cause mortality (HR 0.78; 95% CI: 0.68–0.91), as did those who improved both PAEE and MDS (0.60; 0.44–0.82). There was no evidence of interaction between PA and diet quality exposures on mortality risk. Population impact estimates suggested that if all participants had maintained high levels of PA and diet quality consistently, cumulative adjusted mortality rate would have been 8.8% (95% CI: 2.4 to 15.3%) lower.ConclusionsThese findings suggest that adopting and maintaining higher levels of PA and diet quality are associated with lower mortality. Significant public health benefits could be realised by enabling active living and healthy eating through adulthood.

Physical activity, metabolites, and breast cancer associations.

The effects of usual physical activity on physiology and disease prevention are not fully understood. We examined the associations between physical activity, metabolites, and breast cancer risk. Physical activity levels were assessed using doubly labeled water, accelerometers, and 24-hr recalls in the IDATA study (N = 707 participants, ages 50-74 years, 51% women), with 1-6 assessments over 12 months and two blood sample collections. Partial Spearman correlations were used to estimate associations between physical activity and 843 serum metabolites, corrected for multiple testing. Conditional logistic regression models were used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) of metabolites with postmenopausal breast cancer in a nested case-control study (621 cases, 621 controls), all statistical tests were 2-sided. Physical activity was associated with 164 metabolites spanning numerous pathways, including amino acid and fatty acid metabolism. Twelve of these metabolites were also associated with breast cancer risk, ten of which supported a protective role of physical activity. Notably, higher physical activity was associated with lower 16alpha-hydroxy DHEA 3-sulfate (androgen) and adipoylcarnitine (fatty acid), both of which were associated with increased breast cancer risk (OR per 1 standard deviation (SD)=1.34, 95% CI = 1.16-1.55 and 1.26,1.11-1.42, respectively). Higher physical activity energy expenditure was also associated with lower sphingomyelin (d18:1/20:1, d18:2/20:0), which was associated with a reduced breast cancer risk (0.82,0.73-0.93). Physical activity is associated with a broad range of metabolites, many of which are consistent with a protective effect against breast cancer. Our findings highlight potential metabolic pathways for cancer prevention.

Prediction Of Energy Expenditure Of Physical Activities During Balneotherapy Using Heart Rates

Prediction Of Energy Expenditure Of Physical Activities During Balneotherapy Using Heart Rates

Risk for low energy availability, disordered eating and sleep disturbance among female football players.

Low energy availability (LEA) and mental health issues are prevalent among female athletes and can have adverse effects on health and sports performance. This study aimed to assess energy availability and, mental health status (depression, anxiety, sleep deprivation, drug misuse, alcohol misuse, and disordered eating) among female football players. Despite the availability of validated tools for the triads and REDs, few studies have focused on the prevalence of LEA and mental health in female football players. Furthermore, limited information is available on LEA and its consequences in India. Professional female football players (n=25) aged 19-30 years were recruited using incidental sampling. LEA was estimated based on energy availability [energy intake - activity energy expenditure] and LEA female questionnaire (LEAF-Q). Sports mental health assessment tool-1 (SMHAT-1) was used to assess the mental health status. Descriptive statistics and chi square test were used to test the hypotheses. According to the factorial method and LEAF-Q, 24% and 12% of players had LEA, respectively. LEA symptoms, such as decreased gastrointestinal and menstrual function, were observed in 16% of participants, while 8% had a history of injury. 44% of the participants exhibited poor mental health. Sleep disturbance (12%) and disordered eating (44%), were among the most common mental health issues. No significant difference was found between LEA, disordered eating, and sleep disturbance. Female football players were more likely to develop LEA and mental health disorders, such as disordered eating and sleep disturbance. LEA was not linked with disordered eating or sleep disturbance. Early detection of LEA and effective intervention enhances the health and performance of female football players.

Improving physical and mental health in women with breast cancer undergoing anthracycline-based chemotherapy through wearable device-based aerobic exercise: a randomized controlled trial.

Aimed to assess the impact of wearable device-based aerobic exercise on the physical and mental well-being of women with breast cancer (BC) undergoing chemotherapy. Forty adult women with BC who underwent anthracycline-based chemotherapy were randomly allocated to the exercise group (n = 21) or the control group (n = 19). Both groups received standard health education and oncology care. In addition, the exercise group wore wearable devices to engage in moderate to high-intensity (50-90% HRmax) aerobic exercise during chemotherapy, while the control group did not carry out exercise intervention. Health-related physical fitness level, physical activity energy expenditure (PAEE), anxiety and depression scores, sleep quality, cancer-related fatigue, and overall quality of life (QoL), were assessed both before (prior to the first chemotherapy session) and after (prior to the fifth chemotherapy session) the exercise intervention. Exercise-related adverse events, exercise compliance, number and severity of gastrointestinal reactions and myelosuppression occurred were recorded during the exercise intervention. After the intervention, compared to the control group, the exercise group (1) had significantly higher relative VO2peak (p = 0.003) and handgrip strength (p < 0.001); (2) had significantly higher PAEE (p < 0.001); (3) had a significantly lower scores in anxiety (p = 0.007), depression (p = 0.028), sleep quality in domains of subjective sleep quality (p = 0.010), sleep disturbances (p = 0.004), daytime dysfunction (p = 0.007), cancer-related fatigue in domains of physical (p < 0.001) and affective (p < 0.001); and (4) had a significantly lower scores in QoL in domains of physical well-being (p < 0.001) and emotional well-being (p = 0.019), while a significantly higher scores in functional well-being (p < 0.001). Patients in the exercise group experienced less severe gastrointestinal reactions (p = 0.028) and myelosuppressive symptoms (p < 0.001) than that in the control group. Patients in the exercise group had no serious exercise-related adverse events, with a mean exercise adherence of 81.8%. Wearable device-based aerobic exercise during chemotherapy can be an effective adjunctive therapy to improve physical and mental health in BC patients. https://www.chictr.org.cn/showproj.html?proj=200247, Identifier: ChiCTR2300073667.

502 Cat and mouse: The effect of consuming four different diet formants (intact mice, raw, canned wet and kibble) on energy expended to consume a meal and immediately post-prandial in domestic cats

Abstract Cats are obligate carnivores; however, we feed them a variety of different diet formats without a clear understanding of feeding behavior and metabolism among diet formats. Whole-prey or raw diets may mimic a more natural diet and require more energy to consume. However, there is currently a dearth of literature examining feline energy expenditure (EE) during the consumption of and immediate post-prandial period when fed different diet formats. The present study aimed to investigate differences in the energetics of adult cats consuming four different diet formats in isocaloric offerings: raw intact mice, commercial raw, canned wet, and kibble diets. Adult neutered male cats [n = 12; body weight (BW) = 4.82 ± 0.164 kg) were used in a 4 x 4 replicated Latin square design and adapted to consuming each diet format before the initiation of the study. Following a 2-d adaptation period, cats were fed 25% of their daily caloric requirement (50.77 ± 1.549 kcal) in indirect calorimetry chambers in which VO2 and VCO2 exchange were measured. Energy expenditure (kcal/BW0.67 kg) was calculated for the consumption period, 15 min immediately post-prandial and 2 h post-prandial. Respiratory gases were measured for one fasted reading, followed by the first feeding. During each feeding, measurements were taken during the consumption period and 15 min post-prandial. For the following 2 h, respiratory gases were measured every 25 min for an additional 4 measures of respiratory gases. All data were analyzed using a generalized linear mixed model considering the effects of treatment, time and their interaction as fixed, and the effects of cat and period as random. A spatial power covariance structure was used to model repeated measures. Significance was considered at P &amp;lt; 0.05 and Tukey’s post-hoc test was performed to separate means. Energy expenditure during consumption and 15 min post-prandial was similar among treatments, and EE for 15 min post-prandial was greater than EE during consumption (P &amp;lt; 0.001). During the 2 h post-prandial, EE for the mice diet was greater than the kibble and canned wet diets (P &amp;lt; 0.001), while EE for the raw diet was only greater than the kibble diet (P &amp;lt; 0.001). Energy expenditure was similar between the kibble and canned wet diets (P = 0.919) and between the mice and raw diets (P = 0.598). Among all treatments and time periods, the mouse diet had the greatest mean EE. An increase in EE during the feeding period and post-prandial could benefit sedentary indoor cats who may be in positive energy balance. Feeding cats a naturalistic diet, such as intact mice or a raw diet, may increase activity levels and EE, but the longer-term effects of these feeding formats on energy balance need to be explored.

Composite activity type and stride-specific energy expenditure estimation model for thigh-worn accelerometry

BackgroundAccurately measuring energy expenditure during physical activity outside of the laboratory is challenging, especially on a large scale. Thigh-worn accelerometers have gained popularity due to the possibility to accurately detect physical activity types. The use of machine learning techniques for activity classification and energy expenditure prediction may improve accuracy over current methods. Here, we developed a novel composite energy expenditure estimation model by combining an activity classification model with a stride specific energy expenditure model for walking, running, and cycling.MethodsWe first trained a supervised deep learning activity classification model using pooled data from available adult accelerometer datasets. The composite energy expenditure model was then developed and validated using additional data based on a sample of 69 healthy adult participants (49% female; age = 25.2 ± 5.8 years) who completed a standardised activity protocol with indirect calorimetry as the reference measure.ResultsThe activity classification model showed an overall accuracy of 99.7% across all five activity types during validation. The composite model for estimating energy expenditure achieved a mean absolute percentage error of 10.9%. For running, walking, and cycling, the composite model achieved a mean absolute percentage error of 6.6%, 7.9% and 16.1%, respectively.ConclusionsThe integration of thigh-worn accelerometers with machine learning models provides a highly accurate method for classifying physical activity types and estimating energy expenditure. Our novel composite model approach improves the accuracy of energy expenditure measurements and supports better monitoring and assessment methods in non-laboratory settings.

Examining the Cycle of Physical Frailty in Falls Clinic Attendees Through Structural Equation Modeling.

In 1998, Fried and Walston introduced the Cycle of Frailty (CF) as a foundational concept for defining the physical frailty phenotype (FP). While the FP has been extensively validated, the CF hypothesis lacks equivalent support. This study aimed to internally validate the CF using structural equation modeling (SEM) in a clinical dataset of adults aged 50 or older attending an outpatient falls clinic. Measures included: age, morbidity, nutrition, sarcopenia by bioelectrical impedance, VO2max, handgrip strength, basal metabolic rate (BMR), 5-times chair stand test (5CST), physical activity, and total energy expenditure (TEE). The SEM, incorporating CF hypothesized causal pathways, was tested using IBM® SPSS® Amos 27.0.0 (maximum likelihood method) with a sample of 102 adults (mean age 69.8 years, 58.8% women). Overall, the SEM was supported by the data (χ2 = 44.4, df = 37, p = 0.189), with significant (p < 0.05) regression weights for morbidity→sarcopenia, age→sarcopenia, sarcopenia→VO2max, sarcopenia→handgrip strength, handgrip strength→5CST, physical activity→TEE, TEE→nutrition, and BMR→TEE. However, nutrition→sarcopenia, sarcopenia→BMR, VO2max→5CST, and 5CST→physical activity were not significant. Although the SEM was limited by inclusion of surrogate CF measures (e.g., 5CST instead of gait speed, VO2max based on age-predicted maximal/resting heart rate), it provided some internal support for the CF hypothesis.

Energy Expenditure in Humans: Principles, Methods, and Changes Throughout the Life Course.

Humans require energy to sustain their daily activities throughout their lives. This narrative review aims to (a) summarize principles and methods for studying human energy expenditure, (b) discuss the main determinants of energy expenditure, and (c) discuss the changes in energy expenditure throughout the human life course. Total daily energy expenditure is mainly composed of resting energy expenditure, physical activity energy expenditure, and the thermic effect of food. Total daily energy expenditure and its components are estimated using variations of the indirect calorimetry method. The relative contributions of organs and tissues determine the energy expenditure under different physiological conditions. Evidence shows that energy expenditure varies along the human life course, at least in part due to changes in body composition, the mass and specific metabolic rate of organs and tissues, and levels of physical activity. This information is crucial to estimate human energy requirements for maintaining health throughout the life course.

Validation of activity trackers to estimate energy expenditure in older adults with cardiovascular risk factors.

To compare different types of activity trackers recording physical activity energy expenditure (PAEE) and examine their criterion validity against indirect calorimetry (IC) as the gold standard in adults over 60 years of age with a special focus on women with cardiovascular risk. Synchronous registrations of PAEE were performed with up to four different devices to determine criterion validity against IC while participants performed a protocol of simulated activities in a laboratory setting. Thirty-four participants (25 women, 9 men) with at least a light cardiac risk performed a protocol of simulated activities in a laboratory setting (daily living activities, cycle ergometer test). PAEE was simultaneously assessed by IC, two research-grade activity trackers (ActiGraph-wGT3X-BT and Actiheart-4) and two consumer-level activity trackers (OMRON pedometer and Fitbit Charge-3). Tracker-derived PAEE was compared with PAEE calculated from IC descriptively and by Bland-Altman plots. The ActiGraph (0.7 ± 0.4 kcal/min), the Actiheart (1.1 ± 0.6 kcal/min) and the OMRON (0.8 ± 0.6 kcal/min) underestimated, while the Fitbit (3.4 ± 1.2 kcal/min) overestimated PAEE compared to IC-PAEE (2.0 ± 0.5 kcal/min). The Bland-Altman limits of agreement (LoA) against IC were +0.5/+2.2 kcal/min for the ActiGraph, -0.3/+2.1 kcal/min for the Actiheart, -3.7/+1.0 kcal/min for the Fitbit, and -0.5/+2.9 kcal/min for the OMRON. The magnitude of the deviation varied considerably depending on the activity (e.g. walking, cleaning, cycle ergometer test). The research-grade activity trackers estimated PAEE with higher validity than the commercially available activity trackers. The partly very wide LoA have to be critically considered when assessing PAEE in the context of health service research, as individual Physical Activity behaviour may be under- or overestimated.

Components of Total Energy Expenditure in Healthy and Critically Ill Children: A Comprehensive Review.

Total energy expenditure (TEE) is the total energy expended by an individual to sustain life, activities, and growth. TEE is formed by four components: resting energy expenditure (REE), activity energy expenditure (AEE), growth-related energy expenditure (GEE), and the thermic effect of feeding (TEF). Some energy expenditure (EE) components may change throughout childhood and cannot be reliably estimated using prediction formulae. To summarize measured TEE components as reported in the literature in healthy and critically ill children. We searched MEDLINE, EMBASE, and CINAHL for studies published between 1946 and 7 September 2023. The primary outcome was energy expenditure. Included studies were published in English and measured one or more of TEE, AEE, GEE, and TEF with Indirect Calorimetry or Doubly Labeled Water in participants between 1 month and 18 years of age. We excluded studies reporting only REE or using predictive equations. Following abstraction, reported values were converted into kcal/kg/day or kcal/day as possible. Weighted mean values were calculated using median or means of EE measurements. We found 138 studies, 8163 patients, and 16,636 eligible measurements. The median (IQR) study sample size was 20 (12, 35) patients. TEE was the most evaluated component. The median (IQR) TEE in infants was 73.1 (67.0, 76.5), in children 78.0 (66.0, 81.3), and in adolescents was 44.2 (41.8, 51.9) kcal/kg/day. Very few studies reported on GEE and TEF. This is one of the first studies that summarizes components of total energy expenditure in different pediatric age groups in healthy and critically ill children. Growth- and feeding-associated energy expenditure are poorly reported in healthy children, while all components of TEE (except REE) are poorly reported in critically ill children.

Daily energy expenditure and water turnover in female netball players from the Netball Super League: A doubly labeled water observation study.

To establish the criterion-assessed energy and fluid requirements of female netball players, 13 adult players from a senior Netball Super League squad were assessed over 14 days in a cross-sectional design, representing a two- and one-match microcycle, respectively. Total energy expenditure (TEE) and water turnover (WT) were measured by doubly labeled water. Resting and activity energy expenditure were measured by indirect calorimetry and Actiheart, respectively. Mean 14-day TEE was 13.46±1.20MJday-1 (95% CI, 12.63-14.39MJday-1). Resting energy expenditure was 6.53±0.60MJday-1 (95% CI, 6.17-6.89MJday-1). Physical activity level was 2.07±0.19 arbitrary units (AU) (95% CI, 1.95-2.18 AU). Mean WT was 4.1±0.9Lday-1 (95% CI, 3.6-4.7Lday-1). Match days led to significantly greater TEE than training (+2.85±0.70MJday-1; 95% CI, +1.00- +4.70MJday-1; p=0.002) and rest (+4.85±0.70MJday-1; 95% CI, +3.13-+6.56MJday-1; p<0.001) days. Matches led to significantly greater energy expenditure (+1.85±1.27MJ; 95% CI, +0.95-+2.76MJday-1; p=0.001) than court-based training sessions. There was no significant difference in TEE (+0.03±0.35MJday-1; 95% CI, -0.74-+0.80MJday-1; p=0.936) across weeks. Calibrated Actiheart 5 monitors underestimated TEE (-1.92±1.21MJday-1). Energy and fluid turnover were greatest on match days, followed by training and rest days, with no difference across weeks. This study provides criterion-assessed energy and fluid requirements to inform dietary guidance for female netball players.

Validity of predictive equations for total energy expenditure against doubly labeled water

Variations in physical activity energy expenditure can make accurate prediction of total energy expenditure (TEE) challenging. The purpose of the present study was to determine the accuracy of available equations to predict TEE in individuals varying in physical activity (PA) levels. TEE was measured by DLW in 56 adults varying in PA levels which were monitored by accelerometry. Ten different models were used to predict TEE and their accuracy and precision were evaluated, considering the effect of sex and PA. The models generally underestimated the TEE in this population. An equation published by Plucker was the most accurate in predicting the TEE in our entire sample. The Pontzer and Vinken models were the most accurate for those with lower PA levels. Despite the levels of accuracy of some equations, there were sizable errors (low precision) at an individual level. Future studies are needed to develop and validate these equations.

No association between vascular aging and sarcopenia in healthy participants

Background & AimsSeveral 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. MethodsIn 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. ResultsAge and blood pressure predicted the variance of pulse wave velocity and carotid intima media thickness with R2 values of 0.94 to 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. ConclusionsWe were not able to find an association between vascular aging and sarcopenia

Correlation between Muscle Mass and Physical Activity Level in Older Adults at Risk of Falling: The FITNESS Study

BackgroundThe study investigates the correlation between muscle mass and physical activity level measured objectively and subjectively in older adults who fall or are at high risk of falling.MethodsFITNESS (Fall Interest to Target Newly Sarcopenic Society) is a multi-center (French university hospitals of Angers, Lille, Limoges and Orléans), cross-sectional, observational study of routine care within a French multidisciplinary hospital consultation. Inclusion criteria were ≥ 75 years old, living at home and consulting for fall or gait disorder. A standardized geriatric assessment, muscle mass evaluation by impedancemetry, physical activity by continuous actimetry (5 days) and Incidental and Planned Exercise Questionnaire (IPEQ) were performed at patient inclusion.Results170 people aged 75 and over were included in the FITNESS study (mean age 82.9 ± 4.7 years, women 72.9%). Muscle mass (whole body and lower limbs) correlated with active energy expenditure (AEE, ρ whole body = 0.32, p-value < 0.001; ρ lower limbs = 0.25, p-value = 0.003), but not with number of daily steps, nor with IPEQ score. Multivariate analysis of whole-body muscle mass showed a positive and significant association with AEE and albumin levels and for lower limb muscle mass, a positive association with AEE and Charlson.ConclusionThis study suggests that in the particular population of older adults who fall and/or are at high risk of falling, loss of muscle mass correlates with reduced physical activity. So subjects who fall or at high risk of falling constitute a special group for whom the fight against sedentary lifestyles and the maintenance of physical activity should be a dual priority.

A CNN Model for Physical Activity Recognition and Energy Expenditure Estimation from an Eyeglass-Mounted Wearable Sensor.

Metabolic syndrome poses a significant health challenge worldwide, prompting the need for comprehensive strategies integrating physical activity monitoring and energy expenditure. Wearable sensor devices have been used both for energy intake and energy expenditure (EE) estimation. Traditionally, sensors are attached to the hip or wrist. The primary aim of this research is to investigate the use of an eyeglass-mounted wearable energy intake sensor (Automatic Ingestion Monitor v2, AIM-2) for simultaneous recognition of physical activity (PAR) and estimation of steady-state EE as compared to a traditional hip-worn device. Study data were collected from six participants performing six structured activities, with the reference EE measured using indirect calorimetry (COSMED K5) and reported as metabolic equivalents of tasks (METs). Next, a novel deep convolutional neural network-based multitasking model (Multitasking-CNN) was developed for PAR and EE estimation. The Multitasking-CNN was trained with a two-step progressive training approach for higher accuracy, where in the first step the model for PAR was trained, and in the second step the model was fine-tuned for EE estimation. Finally, the performance of Multitasking-CNN on AIM-2 attached to eyeglasses was compared to the ActiGraph GT9X (AG) attached to the right hip. On the AIM-2 data, Multitasking-CNN achieved a maximum of 95% testing accuracy of PAR, a minimum of 0.59 METs mean square error (MSE), and 11% mean absolute percentage error (MAPE) in EE estimation. Conversely, on AG data, the Multitasking-CNN model achieved a maximum of 82% testing accuracy in PAR, a minimum of 0.73 METs MSE, and 13% MAPE in EE estimation. These results suggest the feasibility of using an eyeglass-mounted sensor for both PAR and EE estimation.

Effects of the COVID-19 associated United Kingdom lockdown on physical activity in older adults at high risk of cardiovascular disease: a mixed methods perspective from the MedEx-UK multicenter trial.

Physical inactivity and sedentary behaviour are linked to increased risk of cardiovascular disease, infections and dementia, as well as placing a significant economic burden on healthcare systems. The implementation of COVID-19 pandemic lockdown measures aimed at reducing virus transmission posed challenges to the opportunity to be physically active. This study investigates how the first UK COVID-19 lockdown affected objectively measured physical activity in older adults at higher risk of cardiovascular disease. We studied 48 individuals aged 55-74 years (81.3% female) with self-reported PA levels < 90 min/week and a QRISK2 score ≥ 10 (indicative of a ≥ 10% risk of a major cardiovascular event in the next 10 years) without mild cognitive impairment or dementia. Physical activity data was collected using objective wrist-based activity monitors and analysed across three time periods, usual activity (pre-pandemic), the precautionary phase when the UK began advising on limiting social contact and finally during the first UK lockdown period was collected (27 January 2020 and 07 June 2020). Data was analysed using linear mixed effects model was used to investigate PA levels over the measured 12-week period. Effects of BMI, age, deprivation score and baseline PA levels on PA across the three measurement periods were also examined. Focus-group and individual interviews were conducted, and data were thematically analysed. Average daily step count (-34% lower, p < 0.001) and active energy expenditure (-26% lower, p < 0.001) were significantly lower during the precautionary period compared with the usual activity period. Physical activity remained low during the UK lockdown period. Participants with a lower BMI engaged in significantly more (+45% higher daily steps p < 0.001) physical activity and those over 70 years old were more physically active than those under 70 years across the 12-week period (+23% higher daily steps p < 0.007). The risk of COVID-19 infection and restrictions because of lockdown measures meant some individuals had to find alternative methods to staying physical active. Participants described a lack of access to facilities and concerns over health related to COVID-19 as barriers to engaging in physical activity during lockdown. For some, this resulted in a shift towards less structured activities such as gardening or going for a walk. The data presented shows that lockdown measures during the COVID-19 pandemic significantly reduced physical activity among older individuals at risk of cardiovascular disease, particularly those with a higher body mass index. To support this population group in staying active during future lockdowns, a multifaceted strategy is needed, emphasizing psychosocial benefits and home-based physical activity. The MedEx-UK study was pre-registered with ClinicalTrials.gov (NCT03673722).

Energy Expenditure Validation of an Exergame Platform: Ring Fit Adventure Use in Adults with Overweight and Obesity.

Objective: This study aims at comparing the energy expenditure (EE) and heart rate (HR) data from Ring Fit Adventure (RFA) with those from indirect calorimetry (COSMED) and a heart rate monitor (Polar FT7). A secondary goal is to evaluate self-reported enjoyment and perceived effort levels. Materials and Methods: Thirty participants (age = 21.8 ± 2.2; body mass index = 31.8 ± 4.4) were recruited for two laboratory visits. The first visit involved baseline measurements. In the second visit, participants performed a 55-minute ad libitum exercise session with the RFA in adventure mode with moderate difficulty. During this session, EE, HR, perceived effort, and enjoyment of physical activity were recorded. Results: Although no statistically significant overestimation of EE was found between the RFA and the metabolic cart, two-way analysis of variance results show a main effect of condition (RFA vs. Polar FT7) on HR (122.8 ± 20.1 bpm and 129.0 ± 18.6 bpm; P = 0.007; ᶯp2 = 0.235). Based on comprehensive statistical evaluations, including the mean absolute percent error, intraclass correlations, typical error of measurement, and limits of agreement, the data suggest that the RFA provides reliable estimates for EE and HR. Overall, participants enjoyed the game considerably (71.3 ± 5.9/80 arbitrary units), and their reported perceived exertion was low. Conclusion: This study underscores that the RFA values are relatively accurate and precise, and thus it can be safely suggested for individuals with overweight and obesity to adopt an active lifestyle.