Dataset Information

How Accurate and Precise Can We Measure the Posture and the Energy Expenditure Component of Sedentary Behaviour with One Sensor?

ABSTRACT: Sedentary behaviour is an emergent public health topic, but there is still no method to simultaneously measure both components of sedentary behaviour-posture and energy expenditure-with one sensor. This study investigated the accuracy and precision of measuring sedentary time when combining the proprietary processing of a posture sensor (activPAL) with a new energy expenditure algorithm and the proprietary processing of a movement sensor (ActiGraph) with a published posture algorithm. One hundred office workers wore both sensors for an average of 7 days. The activPAL algorithm development used 38 and the subsequent independent method comparison 62 participants. The single sensor sedentary estimates were compared with Bland-Atman statistics to the Posture and Physical Activity Index, a combined measurement with both sensors. All single-sensor methods overestimated sedentary time. However, adding the algorithms reduced the overestimation from 129 to 21 (activPAL) and from 84 to 7 min a day (ActiGraph), with far narrower 95% limits of agreements. Thus, combining the proprietary data with the algorithms is an easy way to increase the accuracy and precision of the single sensor sedentary estimates and leads to sedentary estimates that are more precise at the individual level than those of the proprietary processing are at the group level.

SUBMITTER: Kuster RP

PROVIDER: S-EPMC8198866 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

How Accurate and Precise Can We Measure the Posture and the Energy Expenditure Component of Sedentary Behaviour with One Sensor?

Kuster Roman P RP Grooten Wilhelmus J A WJA Blom Victoria V Baumgartner Daniel D Hagströmer Maria M Ekblom Örjan Ö

International journal of environmental research and public health 20210527 11

Sedentary behaviour is an emergent public health topic, but there is still no method to simultaneously measure both components of sedentary behaviour-posture and energy expenditure-with one sensor. This study investigated the accuracy and precision of measuring sedentary time when combining the proprietary processing of a posture sensor (activPAL) with a new energy expenditure algorithm and the proprietary processing of a movement sensor (ActiGraph) with a published posture algorithm. One hundre ...[more]

PMID: 34072243

Similar Datasets

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.

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.

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.

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.

Dataset Information

How Accurate and Precise Can We Measure the Posture and the Energy Expenditure Component of Sedentary Behaviour with One Sensor?

Publications

How Accurate and Precise Can We Measure the Posture and the Energy Expenditure Component of Sedentary Behaviour with One Sensor?

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets