A novel approach for measuring energy expenditure of a single sit-to-stand movement

Factors influencing physical activity levels in elderly community-dwelling convalescent stroke survivors: A cross-sectional study

AIM

This study aimed to investigate factors affecting physical activity (PA) among elderly stroke survivors living in the community and assess the mediating role of exercise planning in the relationship between exercise self-efficacy and PA.

METHODS

300 participants were surveyed using questionnaires and scales, with data analyzed using SPSS 26.0.

RESULTS

Univariate analysis identified sociological, disease-related factors, exercise self-efficacy, and exercise planning as influencing PA. Ordered logistic regression showed significant associations between PA, exercise self-efficacy (OR 1.093, 95 % CI 1.055-1.133, P < 0.001), and exercise planning (OR 1.296, 95 % CI 1.202-1.398, P < 0.001). Exercise planning partially mediated the relationship between exercise self-efficacy and PA, accounting for 64.86 % of the total effect.

CONCLUSIONS

Multiple factors, including sociological and disease-related ones, as well as exercise self-efficacy and planning, influence PA in elderly stroke survivors. Exercise planning partially mediates the relationship between exercise self-efficacy and PA.

Test-retest reliability of Latin American Group for Maturity (GDLAM) protocol in older women

Functional autonomy (FA) is a critical factor in determining the quality of life of older adults (OA), especially in the case of older women (OW), as they face a decline in FA in their later years of life. FA should be assessed early, using valid, reliable, and low-cost tests. This study evaluated the test-retest reliability of GDLAM and GDLAM autonomy index (GI) in OW. Thirty-nine OW (71.2 ± 6.50 years) participated in the study. A repeated measures design was used to compare the interday test-retest reliability of the five GDLAM tests (seconds) and the GI (points). The five tests represent activities of daily living, such as dressing or wandering around the house, while the GI provides a weighting of the results of the five tests. The analysis consisted of the intraclass correlation coefficient (ICC), standard error of measurement (SEM), and coefficient of variation (CV). A CV ≤ 10% and an ICC ≥ 0.80 were considered acceptable reliability, whereas a CV ≤ 5% and an ICC ≥ 0.90 were considered high reliability. The outcome of the five tests, represented by the GI, showed high interday test-retest reliability (CV = 6.00% and ICC = 0.91). The results of this study demonstrate that the five tests of the GDLAM protocol and the GI have high interday test-retest reliability and good interday reproducibility. From a practical point of view, the GDLAM protocol allows the assessment of FA of community-dwelling OW, providing background for early diagnosis and, with it, the possibility of developing an individualized physical exercise prescription.

Estimating Energy Cost of Body Weight Resistance Exercise Using a Multistage Exercise Test

ABSTRACT

Nakagata, T, Yamada, Y, and Naito, H. Estimating energy cost of body weight resistance exercise using a multistage exercise test. J Strength Cond Res 36(5): 1290-1296, 2022-The purpose of this study was to examine energy cost of body weight resistance exercises with slow movement in young men using a multistage exercise test. Fifteen men aged 21-29 years performed 3 exercises (heel-raise, squat, and push-up) at different frequencies (1, 2, 3, 4, 5, and 6 repetitions·min-1). Oxygen consumption was measured using indirect calorimetry; we then computed a simple linear regression between aerobic energy expenditure (EE) and repetition frequency. The slope coefficient in the regression represents the energy cost of those exercises; we compared the extrapolated EE for a frequency of 10 repetitions·min-1. Gross EE increased linearly with repetition frequency in all subjects (y = ax + b). Energy cost was significantly greater in the case of the push-up than in the case of the squat {squat: 0.50 ± 0.14 (95% confidence interval [CI], 0.42-0.58); push-up: 0.77 ± 0.20 kcal (95% CI, 0.66-0.88); and the heel-raise elicited the lowest energy cost: 0.13 ± 0.04 kcal (95% CI, 0.11-0.15)}. Extrapolated EE at 10 repetitions·min-1 was 2.7 ± 0.5 kcal (2.3 metabolic equivalents [METs]), 6.3 ± 1.4 kcal (5.4 METs), and 9.2 ± 2.1 kcal (7.8 METs), respectively, according to the regression based on aerobic EE. These results will be useful for health professionals in prescribing resistance exercise programs improving muscle fitness and considering for weight management.

Cardiometabolic and neuromuscular analyses of the sit-to-stand transition to question its role in reducing sedentary patterns

To counteract the detrimental health effect of sitting all day long, it has been suggested to regularly break sitting time by standing. However, while the difference in energy expenditure, neuromuscular and/or cardiovascular demand of various postures from lying, sitting, and standing is well documented, little is known regarding the dynamic changes occurring during the sit-to-stand transition itself. The aim of the present study was then to describe the cardiometabolic and neuromuscular responses from sitting to standing and specifically during the time-course of this transition. Twelve healthy young participants were asked to perform standardized raises from sitting posture, while cardiometabolic (cardiorespiratory and hemodynamic variables) and neuromuscular (calf muscles' myoelectrical activity, spinal and supraspinal excitabilities) parameters were monitored. As a result, while there was a rapid adaptation for all the systems after rising, the neuromuscular system displayed the faster adaptation (~ 10 s), then hemodynamic (~ 10 to 20 s) and finally the metabolic variables (~ 30 to 40 s). Oxygen uptake, energy expenditure, ventilation, and heart rate were significantly higher and stroke volume significantly lower during standing period compared to sitting one. In calf muscles, spinal excitability (H-reflexes), was lowered by the sit-to-stand condition, while supraspinal drive (V-wave) was similar, indicating different cortico-spinal balance from sitting to standing. Although very heterogenous among participants in terms of magnitude, the present results showed a rapid adaptation for all the systems after rising and the health benefit, notably in terms of energy expenditure, appears rather modest, even if non negligeable.

Test-Retest Reliability of Functional Electromechanical Dynamometer on Five Sit-to-Stand Measures in Healthy Young Adults

Background: The purpose of this study was to determine the reliability for the strength and movement velocity of the concentric phase from the five Sit-to-Stand (5STS), using three incremental loads measured by a functional electromechanical dynamometer (FEMD) in healthy young adults. Methods: The average and peak strength and velocity values of sixteen healthy adults (mean ± standard deviation (SD): age = 22.81 ± 2.13 years) were recorded at 5, 10 and 15 kg. To evaluate the reliability of FEMD, the intraclass correlation coefficient (ICC), standard error of measurement (SEM) and coefficient of variation (CV) were obtained. Results: Reliability was high for the 10 kg (CV range: 3.70–4.18%, ICC range: 0.95–0.98) and 15 kg conditions (CV range: 1.64–3.02%, ICC: 0.99) at average and peak strength, and reliability was high for the 5 kg (CV range: 1.71–2.84%, ICC range: 0.96–0.99), 10 kg (CV range: 0.74–1.84%, ICC range: 0.99–1.00) and 15 kg conditions (CV range: 0.79–3.11%, ICC range: 0.99–1.00) at average and peak velocity. Conclusions: The findings of this study demonstrate that FEMD is a reliable instrument to measure the average and peak strength and velocity values during the five STS in healthy young adults.

Accuracy of 12 Wearable Devices for Estimating Physical Activity Energy Expenditure Using a Metabolic Chamber and the Doubly Labeled Water Method: Validation Study

Background

Self-monitoring using certain types of pedometers and accelerometers has been reported to be effective for promoting and maintaining physical activity (PA). However, the validity of estimating the level of PA or PA energy expenditure (PAEE) for general consumers using wearable devices has not been sufficiently established.

Objective

We examined the validity of 12 wearable devices for determining PAEE during 1 standardized day in a metabolic chamber and 15 free-living days using the doubly labeled water (DLW) method.

Methods

A total of 19 healthy adults aged 21 to 50 years (9 men and 10 women) participated in this study. They followed a standardized PA protocol in a metabolic chamber for an entire day while simultaneously wearing 12 wearable devices: 5 devices on the waist, 5 on the wrist, and 2 placed in the pocket. In addition, they spent their daily lives wearing 12 wearable devices under free-living conditions while being subjected to the DLW method for 15 days. The PAEE criterion was calculated by subtracting the basal metabolic rate measured by the metabolic chamber and 0.1×total energy expenditure (TEE) from TEE. The TEE was obtained by the metabolic chamber and DLW methods. The PAEE values of wearable devices were also extracted or calculated from each mobile phone app or website. The Dunnett test and Pearson and Spearman correlation coefficients were used to examine the variables estimated by wearable devices.

Results

On the standardized day, the PAEE estimated using the metabolic chamber (PAEEcha) was 528.8±149.4 kcal/day. The PAEEs of all devices except the TANITA AM-160 (513.8±135.0 kcal/day; P>.05), SUZUKEN Lifecorder EX (519.3±89.3 kcal/day; P>.05), and Panasonic Actimarker (545.9±141.7 kcal/day; P>.05) were significantly different from the PAEEcha. None of the devices was correlated with PAEEcha according to both Pearson (r=−.13 to .37) and Spearman (ρ=−.25 to .46) correlation tests. During the 15 free-living days, the PAEE estimated by DLW (PAEEdlw) was 728.0±162.7 kcal/day. PAEE values of all devices except the Omron Active style Pro (716.2±159.0 kcal/day; P>.05) and Omron CaloriScan (707.5±172.7 kcal/day; P>.05) were significantly underestimated. Only 2 devices, the Omron Active style Pro (r=.46; P=.045) and Panasonic Actimarker (r=.48; P=.04), had significant positive correlations with PAEEdlw according to Pearson tests. In addition, 3 devices, the TANITA AM-160 (ρ=.50; P=.03), Omron CaloriScan (ρ=.48; P=.04), and Omron Active style Pro (ρ=.48; P=.04), could be ranked in PAEEdlw.

Conclusions

Most wearable devices do not provide comparable PAEE estimates when using gold standard methods during 1 standardized day or 15 free-living days. Continuous development and evaluations of these wearable devices are needed for better estimations of PAEE.

Sit-Stand Desk Software Can Now Monitor and Prompt Office Workers to Change Health Behaviors

OBJECTIVE

To determine the effectiveness of a computer-based intervention designed to increase sit-stand desk usage and help reverse workplace physical inactivity.

BACKGROUND

Sit-stand desks have been successful in reducing workplace sedentary behavior, but the challenge remains for an effective method to increase the usage in order to experience the health and productivity benefits.

METHOD

Data collection (1-year field study with 194 workers) used a novel method of computer software that continuously recorded objective electric sit-stand desk usage, while taking into account the time a worker spends away from their desk (breaks, meetings). During the baseline period, all workers' desk usage was recorded by the software, and the intervention period consisted of software reminders and real-time feedback to all workers to change desk positions. Pooled means were calculated to determine desk usage patterns, and effect sizes and pairwise mean differences were analyzed to test for intervention significance.

RESULTS

The intervention doubled desk usage by increasing ~1 change to ~2 changes per work day. There was a 76% reduction in workers who never used the sit-stand function of the desk. Medium to large effect sizes from the intervention were observed in all three primary outcome measures (desk in sitting/standing position and desk position changes per work day).

CONCLUSION

These findings demonstrate an effective intervention that increased postural transitioning and interrupted prolonged inactivity while remaining at the workstation.

APPLICATION

The methods and results in this research study show that we can quantify an increase in desk usage and collect aggregate data continuously.

Energy Expenditure of a Single Sit-to-Stand Movement with Slow Versus Normal Speed Using the Different Frequency Accumulation Method

Background and objectives: The purpose of this study was to compare the energy expenditures (EE) of a single sit-to-stand (STS) movements with slow and normal speeds using a multi-stage exercise test. Materials and Methods: Twelve young males, aged 21–27 years (age, 23.0 ± 1.7 years; height, 171.2 ± 6.1 cm; weight, 64.3 ± 5.6 kg), performed repeated 3-s stand-up and 3-s sit-down (slow) or 1-s stand-up and 1-s sit-down (normal) movement on two different days with random order. All the participants completed multi-stage tests at different STS frequencies per minute. The slope and intercept of the linear regression relationship between the EE (kcal/min) and the STS frequency were obtained, and the slope of the regression was quantified as the EE of an STS. Results: The metabolic equivalents (METs) of the STS-slow was 4.5 METs for the frequency of 10 times/min (in total 1 min), and the net EE was 5.00 ± 1.2 kcal/min. The net EE of the STS-slow was 0.37 ± 0.12 kcal, which was significantly greater than that during the STS-normal (0.26 ± 0.06 kcal). The difference between the EEs of the STS-slow and STS-normal was significantly greater in taller and heavier subjects. Conclusions: We concluded that the intensity of STS-slow movement is moderate, and the EE during an STS-slow (0.37 ± 0.12 kcal) is higher than that during an STS-normal (0.26 ± 0.06 kcal). Our study results will help exercise and/or health professionals prescribe physical activity programs using STS movement for healthy young population groups.

Validity of a triaxial accelerometer and simplified physical activity record in older adults aged 64-96 years: a doubly labeled water study

BACKGROUND

The aim was to examine the validity of a triaxial accelerometer (ACCTRI) and a simplified physical activity record (sPAR) in estimating total energy expenditure (TEE) and physical activity level (PAL) in older adults with the doubly labeled water (DLW) method.

METHODS

A total of 44 Japanese elderly individuals (64-96 years), of which 28 were community-dwelling healthy adults with or without sporting habits (S or NS group) and 16 were care home residents with frailty (F group), were included in the study. Basal metabolic rate (BMR) was measured by indirect calorimetry, TEE was obtained by the DLW method, and PAL was calculated as TEE/BMR. Daily step count was monitored by a pedometer (Lifecorder). The 24-h average metabolic equivalent was assessed by ACCTRI and sPAR.

RESULTS

The TEE_DLW in men was 2704 ± 353, 2308 ± 442, and 1795 ± 338 kcal d^-1, and that in women was 2260 ± 208, 1922 ± 285, and 1421 ± 274 kcal d^-1 for the S, NS, and F groups, respectively. ACCTRI and sPAR systematically underestimated actual TEE (- 14.2 ± 11.6 and - 15.3 ± 12.3% for ACCTRI and sPAR, respectively). After diet-induced thermogenesis was taken into account for ACCTRI and sPAR, TEE_DLW was significantly correlated with TEE_ACCTRI (R² = 0.714) and TEE_sPAR (R² = 0.668). PAL_DLW was also significantly correlated with PAL_ACCTRI (R² = 0.438) and PAL_sPAR (R² = 0.402).

CONCLUSIONS

Age, living conditions, frailty, and sporting habits contribute to TEE and PAL in the elderly population. ACCTRI and sPAR underestimated TEE and PAL, and adequate corrections are required. The corrected ACCTRI and sPAR are both useful tools to estimate TEE and PAL.

Posture Allocation Revisited: Breaking the Sedentary Threshold of Energy Expenditure for Obesity Management

There is increasing recognition that low-intensity physical activities of daily life play an important role in achieving energy balance and that their societal erosion through substitution with sedentary (mostly sitting) behaviors, whether occupational or for leisure, impact importantly on the obesity epidemic. This has generated considerable interest for better monitoring, characterizing, and promoting countermeasures to sedentariness through a plethora of low-level physical activities (e.g., active workstations, standing desks, sitting breaks), amid the contention that altering posture allocation (lying, sitting, standing) can modify energy expenditure to impact upon body weight regulation and health. In addressing this contention, this paper first revisits the past and more recent literature on postural energetics, with particular emphasis on potential determinants of the large inter-individual variability in the energy cost of standing and the impact of posture on fat oxidation. It subsequently analyses the available data pertaining to various strategies by which posture allocations, coupled with light physical activity, may increase energy expenditure beyond the sedentary threshold, and their relevance as potential targets for obesity management.

Standing economy: does the heterogeneity in the energy cost of posture maintenance reside in differential patterns of spontaneous weight-shifting?

PURPOSE

Due to sedentarity-associated disease risks, there is much interest in methods to increase low-intensity physical activity. In this context, it is widely assumed that altering posture allocation can modify energy expenditure (EE) to impact body-weight regulation and health. However, we have recently shown the existence of two distinct phenotypes pertaining to the energy cost of standing-with most individuals having no sustained increase in EE during steady-state standing relative to sitting comfortably. Here, we investigated whether these distinct phenotypes are related to the presence/absence of spontaneous "weight-shifting", i.e. the redistribution of body-weight from one foot to the other.

METHODS

Using indirect calorimetry to measure EE in young adults during sitting and 10 min of steady-state standing, we examined: (i) heterogeneity in EE during standing (n = 36); (ii) EE and spontaneous weight-shifting patterns (n = 18); (iii) EE during spontaneous weight-shifting versus experimentally induced weight-shifting (n = 7), and; (iv) EE during spontaneous weight-shifting versus intermittent leg/body displacement (n = 6).

RESULTS

Despite heterogeneity in EE response to steady-state standing, no differences were found in the amount or pattern of spontaneous weight-shifting between the two phenotypes. Whilst experimentally induced weight-shifting resulted in a mean EE increase of only 11% (range: 0-25%), intermittent leg/body displacement increased EE to >1.5 METs in all participants.

CONCLUSIONS

Although the variability in spontaneous weight-shifting signatures between individuals does not appear to underlie heterogeneity in the energy cost of standing posture maintenance, these studies underscore the fact that leg/body displacement, rather than standing posture alone, is needed to increase EE above the currently defined sedentary threshold.