PhD student, Karolinska Institutet
We try to measure physical inactivity in desk based office work with a new method
The sitting posture is a substantial part of mankind’s modern lifestyle, accounting for more than half of the waking hours. This sedentary lifestyle with its low energy expenditure is strongly associated with cardio-metabolic diseases like diabetes or adiposities and reduces life expectancy significantly. In particular, people in jobs that require large amount of sitting - as typically seen in the office - have therefore an increased mortality risk. More than 10 hour sitting each day increases the mortality risk by some 30% versus sitting less than 4 hours. Contrary to expectation, this sitting related mortality risk is significantly higher than for tobacco (18%) and alcohol (2%). Even if sedentary person meet the general health recommendation on physical activity, their cardio-metabolic health is significantly impaired as a result of prolonged sitting. Thus, the negative health effect of SB have to be seen independent of the people’s physical activity. Due to the large prevalence of sedentary behavior (SB) in occupational settings, various interventions to increase the energy expenditure (so called active workplaces) were introduced and are currently recommended (e.g. dynamic office chairs, standing desks, active-breaks). However, we so far lack evidence that active workplaces have an effect on the office workers energy expenditure (as we do not have a suitable instrument to measure it). The current way to measure the energy expenditure in field settings is to let a person wear a pelvis or thigh mounted accelerometer. Those accelerometers were calibrated in laboratory studies to the true energy expenditure measured with indirect calorimeters. However, the calibrations were carried out for activities like walking or housekeeping that are known to have much higher energy levels. As a consequence, SB is arbitrary defined by the absence of such activities. This approach makes it even hard to distinguish between a person sitting on an office chair and a bicycle. In consequence, we do not have a sensitive instrument to measure EE and small changes thereof for activities in the range of SB between resting and light physical activity, although it is exactly this inactive range that comes into question to cause several cardio-metabolic diseases. This is why this project aims to develop and validate a specific instrument tailored to the energy expenditure of SB to investigate active workplaces.
Abstract: While physical and mental health benefits of regular physical activity are well known, increasing evidence suggests that limiting sedentary behaviour is also important for health. Evidence shows associations of physical activity and sedentary behaviour with health-related quality of life (HRQoL), however, these findings are based predominantly on duration measures of physical activity and sedentary behaviour (e.g., minutes/week), with less attention on frequency measures (e.g., number of bouts). We examined the association of HRQoL with physical activity and sedentary behaviour, using both continuous duration (average daily minutes) and frequency (average daily bouts≥10 min) measures. Baseline data from the WALK 2.0 trial were analysed. WALK 2.0 is a randomised controlled trial investigating the effects of Web 2.0 applications on engagement, retention, and subsequent physical activity change. Daily physical activity and sedentary behaviour (duration = average minutes, frequency = average number of bouts ≥10 minutes) were measured (ActiGraph GT3X) across one week, and HRQoL was assessed with the 'general health' subscale of the RAND 36-Item Health Survey. Structural equation modelling was used to evaluate associations. Participants (N = 504) were 50.8±13.1 (mean±SD) years old with a BMI of 29.3±6.0. The 465 participants with valid accelerometer data engaged in an average of 24.0±18.3 minutes and 0.64±0.74 bouts of moderate-vigorous physical activity per day, 535.2±83.8 minutes and 17.0±3.4 bouts of sedentary behaviour per day, and reported moderate-high general HRQoL (64.5±20.0). After adjusting for covariates, the duration measures of physical activity (path correlation = 0.294, p<0.05) and sedentary behaviour were related to general HRQoL (path coefficient = -0.217, p<0.05). The frequency measure of physical activity was also significant (path coefficient = -0.226, p<0.05) but the frequency of sedentary behaviour was not significantly associated with general HRQoL. Higher duration levels of physical activity in fewer bouts, and lower duration of sedentary behaviour are associated with better general HRQoL. Further prospective studies are required to investigate these associations in different population groups over time.
Pub.: 01 Jul '17, Pinned: 14 Sep '17
Abstract: This study sought to validate cut-points for use of wrist-worn GENEActiv accelerometer data, to analyse preschool children's (4 to 5 year olds) physical activity (PA) levels via calibration with oxygen consumption values (VO2). This was a laboratory-based calibration study. Twenty-one preschool children, aged 4.7 ± 0.5 years old, completed six activities (ranging from lying supine to running) whilst wearing the GENEActiv accelerometers at two locations (left and right wrist), these being the participants' non-dominant and dominant wrist, and a Cortex face mask for gas analysis. VO2 data was used for the assessment of criterion validity. Location specific activity intensity cut-points were established via receiver operator characteristic curve (ROC) analysis. The GENEActiv accelerometers, irrespective of their location, accurately discriminated between all PA intensities (sedentary, light, and moderate and above), with the dominant wrist monitor providing a slightly more precise discrimination at light PA and the non-dominant at the sedentary behaviour and moderate and above intensity levels (area under the curve (AUC) for non-dominant = 0.749-0.993, compared to AUC dominant = 0.760-0.988).This study establishes wrist-worn physical activity cut-points for the GENEActiv accelerometer in preschoolers. What is Known: • GENEActiv accelerometers have been validated as a PA measurement tool in adolescents and adults. • No study to date has validated the GENEActiv accelerometers in preschoolers. What is New: • Cut-points were determined for the wrist-worn GENEActiv accelerometer in preschoolers. • These cut-points can be used in future research to help classify and increase preschoolers' compliance rates with PA.
Pub.: 05 Jul '17, Pinned: 14 Sep '17
Abstract: A central aspect of physical activity and sedentary behaviour research is accurate exposure assessment in the context of disease outcomes. The primary objectives of this study were to evaluate the convergent validity and test-retest reliability of the ActiGraph GT3X+ and activPAL3 accelerometers.Participants from the Breast Cancer and Exercise Trial in Alberta (n=266) wore both devices concurrently during waking hours for 7 days. Summary measures of time (hours/day) for physical activity and sedentary behaviour were compared between devices using Student's t-tests. Bland-Altman plots were used to assess or evaluate the mean differences and limits of agreement between monitors, and intraclass correlation coefficients (ICCs) were used to assess the test-retest reliability of two 7-day activity monitor administrations separated by 2 weeks (n=29).When comparing the ActiGraph Vector Magnitude (VM), which incorporates all three axes of movement (x, y, z), and the Vertical Axis (VT), which detects movement on the vertical or y-axis only, with the activPAL3, all measures of physical activity were statistically significantly different. The difference in measured time in sedentary behaviour was not statistically significant different when comparing the activPAL3 and ActiGraph (VT) estimates (p=0.47) but was statistically significant different for activPAL3 compared with ActiGraph (VM) (p<0.001). ICCs were high and consistent for each method across all behaviours, ranging from 0.87 to 0.93, with the exception of moderate activity and moderate-to-vigorous activity by the ActiGraph (VT) at 0.66 and 0.67, respectively.Despite small mean differences and comparable recordings by both devices at the group level, the precision of estimates between methods was low with wide limits of agreement, suggesting these devices may not be used interchangeably for measuring physical activity and sedentary behaviour using common data reduction methods.
Pub.: 02 Aug '17, Pinned: 14 Sep '17
Abstract: Objective The aim of this study was to determine and verify the optimal location of the motion axis (MA) for the seat of a dynamic office chair. Background A dynamic seat that supports pelvic motion may improve physical well-being and decrease the risk of sitting-associated disorders. However, office work requires an undisturbed view on the work task, which means a stable position of the upper trunk and head. Current dynamic office chairs do not fulfill this need. Consequently, a dynamic seat was adapted to the physiological kinematics of the human spine. Method Three-dimensional motion tracking in free sitting helped determine the physiological MA of the spine in the frontal plane. Three dynamic seats with physiological, lower, and higher MA were compared in stable upper body posture (thorax inclination) and seat support of pelvic motion (dynamic fitting accuracy). Spinal kinematics during sitting and walking were compared. Results The physiological MA was at the level of the 11th thoracic vertebra, causing minimal thorax inclination and high dynamic fitting accuracy. Spinal motion in active sitting and walking was similar. Conclusion The physiological MA of the seat allows considerable lateral flexion of the spine similar to walking with a stable upper body posture and a high seat support of pelvic motion. Application The physiological MA enables lateral flexion of the spine, similar to walking, without affecting stable upper body posture, thus allowing active sitting while focusing on work.
Pub.: 01 Aug '16, Pinned: 14 Sep '17
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