Little is known about associations of temporal patterns of sitting (i.e., distribution of sitting across time) with obesity. We aimed investigating the association between temporal patterns of ...sitting (long, moderate and brief uninterrupted bouts) and obesity indicators (body mass index (BMI), waist circumference and fat percentage), independently from moderate-vigorous physical activity (MVPA) and total sitting time among blue-collar workers.
Workers (n = 205) wore Actigraph GT3X+ accelerometers on the thigh and trunk for 1-4 working days. Using the validated Acti4 software, the total sitting time and time spent sitting in brief (≤5 mins), moderate (>5 and ≤30 mins), and long (>30mins) bouts on working days were determined for the whole day, and for leisure and work separately. BMI (kg/m(2)), waist circumference (cm) and fat percentage were objectively measured.
Results of linear regression analysis adjusted for multiple confounders indicated that brief bouts of sitting was negatively associated with obesity for the whole day (BMI, P < 0.01; fat percentage, P < 0.01; waist circumference, P < 0.01) and work (BMI, P < 0.01; fat percentage, P < 0.01; waist circumference, P < 0.01), but not for leisure. Sitting time in long bouts was positively associated with obesity indicators for the whole day (waist circumference, P = 0.05) and work (waist circumference, P = 0.01; BMI, P = 0.04), but not leisure.
For the whole day as well as for work, brief bouts and long bouts of sitting showed opposite associations with obesity even after adjusting for MVPA and total sitting time, while sitting during leisure did not show these associations. Thus, the temporal distribution of sitting seems to influence the relationship between sitting and obesity.
Full text
Available for:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The relationships between sedentary lifestyle, sitting behaviour, and low back pain (LBP) remain controversial. In this study, we investigated the relationship between back pain and occupational ...sitting habits in 64 call-centre employees. A textile pressure mat was used to evaluate and parameterise sitting behaviour over a total of 400 h, while pain questionnaires evaluated acute and chronic LBP.
Seventy-five percent of the participants reported some level of either chronic or acute back pain. Individuals with chronic LBP demonstrated a possible trend (t-test not significant) towards more static sitting behaviour compared to their pain-free counterparts. Furthermore, a greater association was found between sitting behaviour and chronic LBP than for acute pain/disability, which is plausibly due to a greater awareness of pain-free sitting positions in individuals with chronic pain compared to those affected by acute pain.
•Sitting behaviour was analysed in 64 office employees using textile pressure mats.•The overall classification accuracy for the different sitting positions was 90%.•Subjects with chronic low back pain tended to show a more static sitting behaviour.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
We investigated the effect of two dynamic seat cushions on postural shift, trunk muscle activation and spinal discomfort. In this repeated-measures study, 30 healthy office workers were randomly ...assigned to a sequence of three conditions: sitting on a dynamic seat cushion-A, cushion-B and control (no seat cushion). The two dynamic seat cushions had different inflation levels. Participants typed a standard text for an hour and were monitored for postural shift by using a seat pressure mat, transversus abdominis/internal oblique and lumbar multifidus muscles activity by using surface EMG, spinal discomfort by using Borg's CR-10 scale. Two-way repeated ANOVAs showed no statistically significant interaction effects between condition and time on postural shift and muscle activation. Post hoc Bonferroni tests showed that postural shifts and lumbar multifidus activation during sitting on cushion-A were significantly higher (p < 0.01) than in the control and cushion-B conditions. Both cushions reduced spinal discomfort, compared to the control condition (p < 0.05).
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
High volumes of sitting time are associated with an elevated risk of type 2 diabetes and cardiovascular disease, and with adverse cardiometabolic risk profiles. However, previous studies have ...predominately evaluated only total sitting or television (TV) viewing time, limiting inferences about the specific cardiometabolic health impacts of sitting accumulated in different contexts. We examined associations of sitting time in four contexts with cardiometabolic risk biomarkers in Australian adults.
Participants (n = 3429; mean ± SD age 58 ± 10 years) were adults without clinically diagnosed diabetes or cardiovascular disease from the 2011-2012 Australian Diabetes, Obesity and Lifestyle (AusDiab) study. Multiple linear regressions examined associations of self-reported context-specific sitting time (occupational, transportation, TV-viewing and leisure-time computer use) with a clustered cardiometabolic risk score (CMR) and with individual cardiometabolic risk biomarkers (waist circumference, BMI, resting blood pressure, triglycerides, HDL- and LDL-cholesterol, and fasting and 2-h post-load plasma glucose).
Higher CMR was significantly associated with greater TV-viewing and computer sitting time (b 95%CI = 0.07 0.04, 0.09 and 0.06 0.03, 0.09), and tended to be associated with higher occupational and transport sitting time (0.01 - 0.01, 0.03 and 0.03 - 0.00, 0.06), after adjustment for potential confounders. Furthermore, keeping total sitting time constant, accruing sitting via TV-viewing and computer use was associated with significantly higher CMR (0.05 0.02, 0.08 and 0.04 0.01, 0.06), accruing sitting in an occupational context was associated with significantly lower CMR (- 0.03 - 0.05, - 0.01), while no significant association was seen for transport sitting (0.00 - 0.03, 0.04). Results varied somewhat between the respective biomarkers; however, higher sitting time in each domain tended to be associated detrimentally with individual biomarkers except for fasting glucose (non-significant associations) and systolic blood pressure (a beneficial association was observed). Overall, associations were stronger for TV-viewing and computer use, and weaker for occupational sitting.
Higher context-specific sitting times tended to be detrimentally associated, albeit modestly, with CMR and several cardiometabolic risk biomarkers. There was some evidence suggesting that the context in which people sit is relevant above and beyond total sitting time. Methodological issues notwithstanding, these findings may assist in identifying priorities for sitting-reduction initiatives, in order to achieve optimal cardiometabolic health benefits.
Full text
Available for:
IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Bad sitting posture is harmful to human health. Intelligent sitting posture recognition algorithm can remind people to correct their sitting posture. In this paper, a sitting pressure image ...acquisition system was designed. With the system, we innovatively proposed a hip positioning algorithm based on hip templates. The average deviation of the algorithm for hip positioning is 1.306 pixels (the equivalent distance is 1.50 cm), and the proportion of the maximum positioning deviation less than three pixels is 94.1%. Statistics show that the algorithm works relatively well for different subjects. At the same time, the algorithm can not only effectively locate the hip position with a small rotation angle (0°-15°), but also has certain adaptability to the sitting posture with a medium rotation angle (15°-30°) or a large rotation angle (30°-45°). Using the hip positioning algorithm, the regional pressure values of the left hip, right hip and caudal vertebrae are effectively extracted as the features, and support vector machine (SVM) with polynomial kernel is used to classify the four types of sitting postures, with a classification accuracy of up to 89.6%.
Full text
Available for:
IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Prolonged sitting time has been associated with adverse health outcomes. Interventions at work may contribute to reduced sitting. The objective was to test if a multicomponent work-based intervention ...can reduce sitting time and the number of prolonged sitting periods (> 30 min), increase the number of sit-to-stand transitions and decrease waist circumference and body fat percentage among office workers. Primary outcomes were: change in sitting time, prolonged sitting periods and sit-to-stand transitions at follow-up 1 month later.
At four workplaces, 19 offices (317 workers in total) were cluster randomized for intervention or control. The intervention included the appointment of local ambassadors, management support, environmental changes, a lecture and a workshop. Sitting time was measured using an ActiGraph GT3X+ fixed on the thigh. Data were processed using Acti4 software providing data on time spent sitting, standing and doing other activities. Control participants were instructed to behave as usual. Follow-up measurements were obtained after 1 and 3 months.
At 1 and 3 months, total sitting time was 71 ( P < 0.001) and 48 min ( P < 0.001) lower per 8-h workday in the intervention group compared with the control group. At 1 month, the number of prolonged sitting periods was lower (-0.79/8-h workday, P < 0.001) and sit-to-stand transitions were higher (+14%/sitting hour, P = 0.001) in the intervention compared with the control group. After 3 months, trends persisted. The body fat percentage was lower by 0.61 percentage points ( P = 0.011) in the intervention group compared with the control group after 3 months.
The multicomponent workplace-based intervention was effective in reducing sitting time, prolonged sitting periods and body fat percentage, and in increasing the number of sit-to-stand transitions.
Objectives. A posture maintained for a long period can be harmful to the health of office workers. This study aimed to estimate the recommended ergonomic duration for maintaining different sitting ...postures. Methods. Forty healthy male and female students participated in this experiment designed to measure perceived discomfort caused by maintaining common static sitting postures of office workers in a simple ergonomic set-up for 4 min. The Borg CR10 scale was given to the participants to assess the discomfort in different body parts, before and after each experiment. Based on the mean group discomfort level of 2, the recommended holding time of each posture was estimated. Results
. The recommended holding time and its discomfort score for each studied posture were tabulated. The shortest holding time of a posture was obtained for the moderate neck flexion (1.61 min), and the longest holding time was obtained for a leg posture with 90° knee flexion (6.45 min). Conclusions
. The recommended holding time in this study may help to assess the risk of musculoskeletal disorders (MSDs) in office workers and train the individuals involved in office tasks in proper sitting behavior.
Full text
Available for:
BFBNIB, GIS, IJS, KISLJ, NUK, PNG, UL, UM, UPUK, VSZLJ
In developed and developing countries, social, economic, and environmental transitions have led to physical inactivity and large amounts of time spent sitting. Research is now unraveling the adverse ...public health consequences of too much sitting. We describe improvements in device-based measurement that are providing new insights into sedentary behavior and health. We consider the implications of research linking evidence from epidemiology and behavioral science with mechanistic insights into the underlying biology of sitting time. Such evidence has led to new sedentary behavior guidelines and initiatives. We highlight ways that this emerging knowledge base can inform public health strategy: First, we consider epidemiologic and experimental evidence on the health consequences of sedentary behavior; second, we describe solutions-focused research from initiatives in workplaces and schools. To inform a broad public health strategy, researchers need to pursue evidence-informed collaborations with occupational health, education, and other sectors.
Objectives
Prolonged sitting has been suggested as a risk factor for neck–shoulder pain (NSP). Using a cross-sectional design, we investigated the extent to which objectively measured time sitting is ...associated with NSP among blue-collar workers.
Methods
Sitting time was measured during multiple working days on male (
n
= 118) and female (
n
= 84) blue-collar workers (
n
= 202) using triaxial accelerometers (Actigraph) placed on the thigh and trunk. Workers were categorized into having, on average, a low, moderate or high sitting time, with mean values (SD between subjects) of 4.9 (1.0), 7.3 (0.5) and 9.6 (1.1) h in total per day. Workers rated their largest NSP intensity during the previous month on a numerical scale (0–9) and were subsequently dichotomized into a low and high NSP intensity group (ratings 0–4 and >4, respectively). Logistic regression analyses adjusted for several individual, and work-related factors were used to investigate the association between average sitting time per day (work, leisure and total) and NSP intensity.
Results
For total sitting time, workers in the high sitting category were more likely (adjusted OR 2.97, CI 1.25–7.03) to report high NSP intensity than those who sat moderately (reference category). Low sitting during work was associated with a reduced NSP intensity, but only for males (adjusted OR 0.26 CI 0.07–0.96). No significant association was found between sitting during leisure and NSP intensity.
Conclusion
These findings suggest an association between sitting time, in total per day and specifically during work, and NSP intensity among blue-collar workers. We encourage studying the structure and explanation of this association further in prospective studies on larger populations.
Full text
Available for:
EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Aims/hypothesis
In our current society sedentary behaviour predominates in most people and is associated with the risk of developing type 2 diabetes. It has been suggested that replacing sitting time ...by standing and walking could be beneficial for individuals with type 2 diabetes but the underlying mechanisms are unknown and direct comparisons with exercise are lacking. Our objective was to directly compare metabolic responses of either sitting less or exercising, relative to being sedentary.
Methods
We performed a randomised, crossover intervention study in 12 overweight women who performed three well-controlled 4 day activity regimens: (1) sitting regimen (sitting 14 h/day); (2) exercise regimen (sitting 13 h/day, exercise 1 h/day); and (3) sitting less regimen (sitting 9 h/day, standing 4 h/day and walking 3 h/day). The primary outcome was insulin sensitivity measured by a two-step hyperinsulinaemic–euglycaemic clamp. We additionally performed metabolomics on muscle biopsies taken before the clamp to identify changes at the molecular level.
Results
Replacing sitting time by standing and walking over 4 days resulted in improved peripheral insulin sensitivity, comparable with the improvement achieved by moderate-to-vigorous exercise. Specifically, we report a significant improvement in peripheral insulin sensitivity in the sitting less (~13%) and the exercise regimen (~20%), compared with the sitting regimen. Furthermore, sitting less shifted the underlying muscle metabolome towards that seen with moderate-to-vigorous exercise, compared with the sitting regimen.
Conclusions/interpretations
Replacing sitting time by standing and walking is an attractive alternative to moderate-to-vigorous exercise for improving metabolic health.
Trial registration
ClinicalTrials.gov
NCT03912922.
Graphical abstract
Full text
Available for:
EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
PDF
