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Are temporal patterns of sitting associated with obesity among blue-collar workers? A cross sectional study using accelerometers
Background
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.
Methods
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
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.
Conclusions
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.
Journal Article
Hip Positioning and Sitting Posture Recognition Based on Human Sitting Pressure Image
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%.
Journal Article
Make money! Be a pet sitter
\"Through trial and error and a few humourous mistakes, a girl learns how to take care of pets, find clients, and create a successful pet sitting business to earn enough money to buy her own pet\"--Provided by publisher.
Book
Is the time right for quantitative public health guidelines on sitting? A narrative review of sedentary behaviour research paradigms and findings
Sedentary behaviour (SB) has been proposed as an ‘independent’ risk factor for chronic disease risk, attracting much research and media attention. Many countries have included generic, non-quantitative reductions in SB in their public health guidelines and calls for quantitative SB targets are increasing. The aim of this narrative review is to critically evaluate key evidence areas relating to the development of guidance on sitting for adults. We carried out a non-systematic narrative evidence synthesis across seven key areas: (1) definition of SB, (2) independence of sitting from physical activity, (3) use of television viewing as a proxy of sitting, (4) interpretation of SB evidence, (5) evidence on ‘sedentary breaks’, (6) evidence on objectively measured sedentary SB and mortality and (7) dose response of sitting and mortality/cardiovascular disease. Despite research progress, we still know little about the independent detrimental health effects of sitting, and the possibility that sitting is mostly the inverse of physical activity remains. Unresolved issues include an unclear definition, inconsistencies between mechanistic and epidemiological studies, over-reliance on surrogate outcomes, a very weak epidemiological evidence base to support the inclusion of ‘sedentary breaks’ in guidelines, reliance on self-reported sitting measures, and misinterpretation of data whereby methodologically inconsistent associations are claimed to be strong evidence. In conclusion, public health guidance requires a consistent evidence base but this is lacking for SB. The development of quantitative SB guidance, using an underdeveloped evidence base, is premature; any further recommendations for sedentary behaviour require development of the evidence base and refinement of the research paradigms used in the field.
Journal Article
Associations of context-specific sitting time with markers of cardiometabolic risk in Australian adults
Background
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.
Methods
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).
Results
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.
Conclusions
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.
Journal Article
Wheelchair posture correction equipment
This paper presents an equipment for the detection and correction of the vicious posture of the wheelchair users, as well as of people who spend more time in a sitting position and need to correct their posture. Its second action is to prevent / early detect of bedsores in the sitting area. Based on the structure and components of the equipment, its functionality is emphasized and the developed prototype is presented. Some potential applications of the proposed equipment are described, for five different wheelchair vicious postures and our initial results are given.
Journal Article