How Accurate and Precise Can We Measure the Posture and the Energy Expenditure Component of Sedentary Behaviour with One Sensor?
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SUBMITTER: Kuster RP
PROVIDER: S-EPMC8198866 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description: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.
| S-EPMC5479887 | biostudies-other
Project description:BackgroundDespite growing scientific interest in the benefits of breaking up sedentary time with intermittent standing or walking, few studies have investigated the energy cost of posture transitions. This study aimed to determine whether posture transitions are associated with increased energy expenditure in preschool children.MethodsForty children (mean age 5.3 ± 1.0y) completed a ~150-min room calorimeter protocol involving sedentary, light, and moderate- to vigorous-intensity activities. This study utilised data from ~65-min of the protocol, during which children were undertaking sedentary behaviours (TV viewing, drawing/colouring in, and playing with toys on the floor). Posture was coded as sit/lie, stand, walk, or other using direct observation; posture transitions were classified as sit/lie to stand/walk, sit/lie to other, stand/walk to other, or vice versa. Energy expenditure was calculated using the Weir equation and used to calculate individualised MET and activity energy expenditure (AEE) values. Spearman's rank correlations were used to compare the number of posture transitions, in the individual activities separately and combined, with corresponding MET and AEE values. Participants were divided into tertiles based on the number of posture transitions; MET and AEE values of children in the lowest and highest tertiles of posture transitions were compared using unpaired t-tests. Effect sizes (Cohen's d) were calculated.ResultsThere was a positive correlation between the total number of posture transitions and average METs (rs = 0.42, p = 0.02) and AEE (rs = 0.43, p = 0.02). MET differences between the lowest and highest tertiles of posture transitions resulted in a small effect size for playing with toys (d = 0.27), and moderate effect sizes for TV viewing, drawing and all three activities combined (d = 0.61, 0.50 and 0.64 respectively). Similar results were found for AEE.ConclusionsResults from this study showed that variation in posture transitions may be associated with variation in energy expenditure in preschool children. The findings suggest that the concept that variation in posture transitions may have meaningful biological or health effects in early childhood is worth investigating further.
| S-EPMC6464188 | biostudies-literature
Project description:BackgroundSedentary Behaviour (SB) gets an increasing attention from ergonomics and public health due to its associated detrimental health effects. A large number of studies record SB with ActiGraph counts-per-minute cut-points, but we still lack valid information about what the cut-points tell us about office work. This study therefore analysed the concurrent and discriminant validity of commonly used cut-points to measure SB, activity level, and posture.MethodsThirty office workers completed four office tasks at three workplaces (conventional chair, activity-promoting chair, and standing desk) while wearing two ActiGraphs (waist and wrist). Indirect calorimetry and prescribed posture served as reference criteria. Generalized Estimation Equations analysed workplace and task effects on the activity level and counts-per-minute, and kappa statistics and ROC curves analysed the cut-point validity.ResultsThe activity-promoting chair (p < 0.001, ES ≥ 0.66) but not the standing desk (p = 1.0) increased the activity level, and both these workplaces increased the waist (p ≤ 0.003, ES ≥ 0.63) but not the wrist counts-per-minute (p = 0.74) compared to the conventional chair. The concurrent and discriminant validity was higher for activity level (kappa: 0.52-0.56 and 0.38-0.45, respectively) than for SB and posture (kappa ≤0.35 and ≤ 0.19, respectively). Furthermore, the discriminant validity for activity level was higher for task effects (kappa: 0.42-0.48) than for workplace effects (0.13-0.24).ConclusionsActiGraph counts-per-minute for waist and wrist placement were - independently of the chosen cut-point - a measure for activity level and not for SB or posture, and the cut-points performed better to detect task effects than workplace effects. Waist cut-points were most valid to measure the activity level in conventional seated office work, but they showed severe limitations for sit-stand desks. None of the placements was valid to detect the increased activity on the activity-promoting chair. Caution should therefore be paid when analysing the effect of workplace interventions on activity level with ActiGraph waist and wrist cut-points.
| S-EPMC7881682 | biostudies-literature
Project description:Malnutrition is associated with significant morbidity and mortality in cirrhosis. An accurate nutrition prescription is an essential component of care, often estimated using time-efficient predictive equations. Our aim was to compare resting energy expenditure (REE) estimated using predictive equations (predicted REE, pREE) versus REE measured using gold-standard, indirect calorimetry (IC) (measured REE, mREE). We included full-text English language studies in adults with cirrhosis comparing pREE versus mREE. The mean differences across studies were pooled with RevMan 5.3 software. A total of 17 studies (1883 patients) were analyzed. The pooled cohort was comprised of 65% men with a mean age of 53 ± 7 years. Only 45% of predictive equations estimated energy requirements to within 90⁻110% of mREE using IC. Eighty-three percent of predictive equations underestimated and 28% overestimated energy needs by ±10%. When pooled, the mean difference between the mREE and pREE was lowest for the Harris⁻Benedict equation, with an underestimation of 54 (95% CI: 30⁻137) kcal/d. The pooled analysis was associated with significant heterogeneity (I2 = 94%). In conclusion, predictive equations calculating REE have limited accuracy in patients with cirrhosis, most commonly underestimating energy requirements and are associated with wide variations in individual comparative data.
| S-EPMC6412603 | biostudies-literature
Project description:BackgroundEvidence for the effects of Parkinson disease on energy expenditure is incomplete and contradictory. A number of studies showed increased resting energy expenditure among patients with Parkinson disease whereas others did not. It was hypothesized that energy expenditure increases during exercise, based on findings in patients with a variable regime of anti-parkinsonian therapies and at different stages of the disease. However, energy expenditure during posture maintenance has been neglected. To better understand these issues, we studied energy expenditure in a homogenous population of Parkinson patients in an early stage of the disease and different states of activity.MethodsOxygen consumption was assessed in a group of 10 males with early Parkinson disease without dopaminergic treatment and controls matched for age and body composition. Oxygen consumption was measured at rest, during trunk unsupported sitting, and during exercise at different intensities (unloaded and loaded cycling).ResultsResting energy expenditure was similar between groups. Higher energy consumption was observed during maintenance of trunk posture at rest and during light intensity aerobic exercise (P < .05 for all conditions). The increment in energy expenditure associated with increased physical demand tended to be steeper in Parkinson disease.ConclusionResting energy expenditure is normal in Parkinson disease. However, energy expenditure increases during physical activity and even during the maintenance of unsupported posture among patients with Parkinson disease.
| S-EPMC6266470 | biostudies-literature
Project description:BackgroundTelevision watching and playing of video games (VGs) are associated with higher energy intakes. Motion-controlled video games (MC) may be a healthier alternative to sedentary screen-based activities because of higher energy expenditures, but little is known about the effects of these games on energy intakes.ObjectiveEnergy intake, expenditure, and surplus (intake - expenditure) were compared during sedentary (television and VG) and active (MC) screen-time use.DesignYoung adults (n = 120; 60 women) were randomly assigned to the following 3 groups: television watching, playing traditional VGs, or playing MCs for 1 h while snacks and beverages were provided. Energy intakes, energy expenditures, and appetites were measured.ResultsIntakes across these 3 groups showed a trend toward a significant difference (P = 0.065). The energy expenditure (P < 0.001) was higher, and the energy surplus (P = 0.038) was lower, in MC than in television or VG groups. All conditions produced a mean (±SD) energy surplus as follows: 638 ± 408 kcal in television, 655 ± 533 kcal in VG, and 376 ± 487 kcal in MC groups. The OR for consuming ≥500 kcal in the television compared with the MC group was 3.2 (95% CI: 1.2, 8.4). Secondary analyses, in which the 2 sedentary conditions were collapsed, showed an intake that was 178 kcal (95% CI: 8, 349 kcal) lower in the MC condition than in the sedentary groups (television and VG).ConclusionMCs may be a healthier alternative to sedentary screen time because of a lower energy surplus, but the playing of these games still resulted in a positive energy balance. This trial was registered at clinicaltrials.gov as NCT01523795.
| S-EPMC3396440 | biostudies-literature
Project description:BackgroundIt has been proposed that compensations in physical activity, energy expenditure and sedentary parameters can occur as a result of overfeeding studies in order to maintain body weight; however, the evidence has not yet been systematically reviewed.MethodsThe current study systematically reviewed the literature on this subject to determine the common tools used in overfeeding studies and to explore whether overfeeding produces changes in physical activity, energy expenditure and sedentary parameters. Eight electronic databases were searched to identify experimental studies using keywords pertaining to overfeeding, exercise, physical activity and sedentariness. Articles included healthy adults (aged 18-64 years) participating in an overfeeding study that examined at least one parameter of sedentary, energy expenditure or physical activity. Of 123 full-text articles reviewed, 15 met the inclusion criteria.ResultsThe common tools used in overfeeding studies were doubly labeled water (n = 6), room calorimeter (n = 4), accelerometer (n = 7), pedometer (n = 3), radar sensor (n = 4) and survey (n = 1). Parameters partaining to energy expenditure increased between 7 to 50% with different overfeeding duration. Physical activity parameters, such as number of steps and spontaneous activity, increased or decreased significantly in three studies, while five studies showed no significant change. Sedentary parameters were examined by only one study and its results were not significant after 3 days of overfeeding. Methodological issues existed concerning the small number of studies, disparities in sedentary and physical activity parameters and various definitions of free-living experimental conditions and physical activity limits.ConclusionsThere is actually a use of many tools and a large variation of parameters for physical activity in overfeeding studies. Contradictory findings showed changes in physical activity parameters following overfeeding and limited findings support the absence of changes in sedentariness. While energy expenditure parameters are more numerous and all show an increase after an overfeeding period, further studies are required to confirm changes in physical activity and sedentary parameters.
| S-EPMC6054727 | biostudies-literature
Project description:BackgroundAchieving energy balance is critical for the interpretation of results obtained in respiratory chambers. However, 24-h energy expenditure (24EE) predictions based on estimated resting metabolic rate and physical activity level are often inaccurate and imprecise.ObjectiveWe aimed to develop and validate equations to better achieve energy balance in a respiratory chamber by adding or subtracting food items.DesignBy using a randomized data set with measures of 24EE (n = 241) performed at the Pennington Biomedical Research Center, we developed equations to predict 24EE from anthropometric, demographic, and body composition variables before and at 3 and 7 h into the chamber measurement. The equations were tested on an independent data set (n = 240) and compared with published predictive equations.ResultsBy using anthropometric and demographic variables, the equation was as follows: 24EE (kcal/d) = 11.6 [weight (kg)] + 8.03 [height (cm)] - 3.45 [age (y)] + 217 (male) - 52 (African American) - 235. The mean prediction error was -9 ± 155 kcal/d (2046 ± 305 compared with 2055 ± 343 kcal/d for measured 24EE; P = 0.36). The prediction achieved a precision of ±10% of measured 24EE in 83% of the participants. Energy prescription was then refined by equations with the use of energy expenditure values after 3 h, 7 h, or both into the chamber study. These later equations improved the precision (±10% of measured 24EE) to 92% (P = 0.003) and 96% (P < 0.0001) of the participants at 3 and 7 h, respectively. Body composition did not improve 24EE predictions.ConclusionsWe showed the use of a set of equations to prescribe and adjust energy intake to achieve energy balance in respiratory chambers over 24 h. These equations may be used in most respiratory chambers and modified to accommodate exercise or specific feeding protocols.
| S-EPMC3953881 | biostudies-literature
Project description:PURPOSE:To assess the validity of a derived algorithm, combining tri-axial accelerometry and heart rate (HR) data, compared to a research-grade multi-sensor physical activity device, for the estimation of ambulatory physical activity energy expenditure (PAEE) in individuals with traumatic lower-limb amputation. METHODS:Twenty-eight participants [unilateral (n = 9), bilateral (n = 10) with lower-limb amputations, and non-injured controls (n = 9)] completed eight activities; rest, ambulating at 5 progressive treadmill velocities (0.48, 0.67, 0.89, 1.12, 1.34m.s-1) and 2 gradients (3 and 5%) at 0.89m.s-1. During each task, expired gases were collected for the determination of [Formula: see text] and subsequent calculation of PAEE. An Actigraph GT3X+ accelerometer was worn on the hip of the shortest residual limb and, a HR monitor and an Actiheart (AHR) device were worn on the chest. Multiple linear regressions were employed to derive population-specific PAEE estimated algorithms using Actigraph GT3X+ outputs and HR signals (GT3X+HR). Mean bias±95% Limits of Agreement (LoA) and error statistics were calculated between criterion PAEE (indirect calorimetry) and PAEE predicted using GT3X+HR and AHR. RESULTS:Both measurement approaches used to predict PAEE were significantly related (P<0.01) with criterion PAEE. GT3X+HR revealed the strongest association, smallest LoA and least error. Predicted PAEE (GT3X+HR; unilateral; r = 0.92, bilateral; r = 0.93, and control; r = 0.91, and AHR; unilateral; r = 0.86, bilateral; r = 0.81, and control; r = 0.67). Mean±SD percent error across all activities were 18±14%, 15±12% and 15±14% for the GT3X+HR and 45±20%, 39±23% and 34±28% in the AHR model, for unilateral, bilateral and control groups, respectively. CONCLUSIONS:Statistically derived algorithms (GT3X+HR) provide a more valid estimate of PAEE in individuals with traumatic lower-limb amputation, compared to a proprietary group calibration algorithm (AHR). Outputs from AHR displayed considerable random error when tested in a laboratory setting in individuals with lower-limb amputation.
| S-EPMC6354995 | biostudies-literature
Project description:This SuperSeries is composed of the SubSeries listed below.
2023-04-20 | GSE230208 | GEO