Dataset Information

Dynamic sitting: Measurement and associations with metabolic health.

ABSTRACT: Dynamic sitting, such as fidgeting and desk work, might be associated with health, but remains difficult to identify out of accelerometry data. We examined, in a laboratory study, whether dynamic sitting can be identified out of triaxial activity counts. Among 18 participants (56% men, 27.3 ± 6.5 years), up to 236 counts per minute were recorded in the anteroposterior and mediolateral axes during dynamic sitting using a hip-worn accelerometer. Subsequently, we examined in 621 participants (38% men, 80.0 ± 4.7 years) from the AGES-Reykjavik Study whether dynamic sitting was associated with cardio-metabolic health. Compared to participants who recorded the fewest dynamic sitting minutes (Q1), those with more dynamic sitting minutes had a lower BMI (Q2 = -1.39 (95%CI = -2.33;-0.46); Q3 = -1.87 (-2.82;-0.92); Q4 = -3.38 (-4.32;-2.45)), a smaller waist circumference (Q2 = -2.95 (-5.44;-0.46); Q3 = -3.47 (-6.01;-0.93); Q4 = -8.21 (-10.72;-5.71)), and a lower odds for the metabolic syndrome (Q2 = 0.74 [0.45;1.20] Q3 = 0.58 [0.36;0.95]; Q4 = 0.36 [0.22;0.59]). Our findings suggest that dynamic sitting might be identified using accelerometry and that this behaviour was associated with health. This might be important given the large amounts of time people spend sitting. Future studies with a focus on validation, causation and physiological pathways are needed to further examine the possible relevance of dynamic sitting.

SUBMITTER: van der Berg JD

PROVIDER: S-EPMC6579695 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Dynamic sitting: Measurement and associations with metabolic health.

van der Berg Julianne D JD Stehouwer Coen D A CDA Bosma Hans H Caserotti Paolo P Eiriksdottir Gudny G Arnardottir Nanna Y NY Van Domelen Dane R DR Brychta Robert J RJ Chen Kong Y KY Sveinsson Thorarinn T Johannsson Erlingur E Launer Lenore J LJ Gudnason Vilmundur V Jonsson Palmi V PV Harris Tamara B TB Koster Annemarie A

Journal of sports sciences 20190330 15

Dynamic sitting, such as fidgeting and desk work, might be associated with health, but remains difficult to identify out of accelerometry data. We examined, in a laboratory study, whether dynamic sitting can be identified out of triaxial activity counts. Among 18 participants (56% men, 27.3 ± 6.5 years), up to 236 counts per minute were recorded in the anteroposterior and mediolateral axes during dynamic sitting using a hip-worn accelerometer. Subsequently, we examined in 621 participants (38% m ...[more]

PMID: 30929574

Similar Datasets

Project description:BackgroundHigh amounts of time spent sitting can increase cardiovascular disease risk and are deleteriously associated cardio-metabolic risk biomarkers. Though evidence suggests that accruing sitting time in prolonged periods may convey additional risk, verification using high-quality measures is needed. We examined this issue in adults from the Australian Diabetes, Obesity and Lifestyle Study, using accurate measures of sitting accumulation.MethodsIn 2011/12, 739 adults aged 36 to 89 years (mean±SD 58±10 years) wore activPAL3™ monitors (which provide accurate objective measures of sitting); 678 provided ?4 valid days of monitor data and complete cardio-metabolic biomarker and confounder data. Multivariable linear regression models examined associations of sitting time, sitting time accrued in ?30 minute bouts (prolonged sitting time), and three measures of sitting accumulation patterns with cardio-metabolic risk markers: body mass index (BMI), waist circumference, blood pressure, high- and low- density lipoprotein (HDL and LDL) cholesterol, triglycerides, glycated haemoglobin (HbA1c), fasting plasma glucose (FPG) and 2-hour post-load glucose (PLG). Interactions tests examined whether associations of sitting time with biomarkers varied by usual sitting bout duration.ResultsAdjusted for potential confounders, greater amounts of sitting time and prolonged sitting time were significantly (p<0.05) deleteriously associated with BMI, waist circumference, HDL cholesterol, and triglycerides. Total sitting time was also significantly associated with higher PLG. Sitting accumulation patterns of frequently interrupted sitting (compared to patterns with relatively more prolonged sitting) were significantly beneficially associated with BMI, waist circumference, HDL cholesterol, triglycerides, PLG, and with FPG. Effect sizes were typically larger for accumulation patterns than for sitting time. Significant interactions (p<0.05) showed that associations of sitting time with HDL, triglycerides and PLG became more deleterious the longer at a time sitting was usually accumulated.ConclusionsAdding to previous evidence reliant on low-quality measures, our study showed that accumulating sitting in patterns where sitting was most frequently interrupted had significant beneficial associations with several cardio-metabolic biomarkers and that sitting for prolonged periods at a time may exacerbate some of the effects of sitting time. The findings support sedentary behavior guidelines that promote reducing and regularly interrupting sitting.

Project description:AIM:To identify and describe the characteristics of naturally occurring patterns of exercise, sitting in leisure time and at work and cardiorespiratory fitness, and the association of such profiles with metabolic risk factors, perceived health, and perceived symptoms. METHODS:64,970 participants (42% women, 18-75 years) participating in an occupational health service screening in 2014-2018 were included. Exercise and sitting were self-reported. Cardiorespiratory fitness was estimated using a submaximal cycle test. Latent profile analysis was used to identify profiles. BMI and blood pressure were assessed through physical examination. Perceived back/neck pain, overall stress, global health, and sleeping problems were self-reported. RESULTS:Six profiles based on exercise, sitting in leisure time and at work and cardiorespiratory fitness were identified and labelled; Profile 1 "Inactive, low fit and average sitting in leisure, with less sitting at work"; Profile 2 "Inactive, low fit and sedentary"; Profile 3 "Active and average fit, with less sitting at work"; Profile 4 "Active, average fit and sedentary in leisure, with a sedentary work" (the most common profile, 35% of the population); Profile 5 "Active and fit, with a sedentary work"; Profile 6 "Active and fit, with less sitting at work". Some pairwise similarities were found between profiles (1 and 2, 3 and 4, 5 and 6), mainly based on similar levels of exercise, leisure time sitting and fitness, which translated into similar dose-response associations with the outcomes. In general, profile 1 and 2 demonstrated most adverse metabolic and perceived health, profile 4 had a more beneficial health than profile 3, as did profile 6 compared to profile 5. CONCLUSIONS:The present results implies a large variation in exercise, sitting, and fitness when studying naturally occurring patterns, and emphasize the possibility to target exercise, sitting time, and/or fitness in health enhancing promotion intervention and strategies.

Project description:BackgroundClinical practice guidelines recommend that adults with type 2 diabetes (T2D) sit less and move more throughout the day. The 18-month OPTIMISE Your Health Clinical Trial was developed to support desk-based workers with T2D achieve these recommendations. The two-arm protocol consists of an intervention and control arms. The intervention arm receives 6 months health coaching, a sit-stand desktop workstation and an activity tracker, followed by 6 months of text message support, then 6 months maintenance. The control arm receives a delayed modified intervention after 12 months of usual care. This paper describes the methods of a randomised controlled trial (RCT) evaluating the effectiveness and cost-effectiveness of the intervention, compared to a delayed intervention control.MethodsThis is a two-arm RCT being conducted in Melbourne, Australia. Desk-based workers (≥0.8 full-time equivalent) aged 35-65 years, ambulatory, and with T2D and managed glycaemic control (6.5-10.0% HbA1c), are randomised to the multicomponent intervention (target n = 125) or delayed-intervention control (target n = 125) conditions. All intervention participants receive 6 months of tailored health coaching assisting them to "sit less" and "move more" at work and throughout the day, supported by a sit-stand desktop workstation and an activity tracker (Fitbit). Participants receive text message-based extended care for a further 6-months (6-12 months) followed by 6-months of non-contact (12-18 months: maintenance). Delayed intervention occurs at 12-18 months for the control arm. Assessments are undertaken at baseline, 3, 6, 12, 15 and 18-months. Primary outcomes are activPAL-measured sitting time (h/16 h day), glycosylated haemoglobin (HbA1c; %, mmol/mol) and, cognitive function measures (visual learning and new memory; Paired Associates Learning Total Errors [adjusted]). Secondary, exploratory, and process outcomes will also be collected throughout the trial.DiscussionThe OPTIMISE Your Health trial will provide unique insights into the benefits of an intervention aimed at sitting less and moving more in desk-bound office workers with T2D, with outcomes relevant to glycaemic control, and to cardiometabolic and brain health. Findings will contribute new insights to add to the evidence base on initiating and maintaining behaviour change with clinical populations and inform practice in diabetes management.Trial registrationANZCTRN12618001159246 .

Dataset Information

Dynamic sitting: Measurement and associations with metabolic health.

Publications

Dynamic sitting: Measurement and associations with metabolic health.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets