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Brakenridge CJ, Koster A, de Galan BE, Carver A, Dumuid D, Dzakpasu FQS, Eussen SJPM, Savelberg HHCM, Bosma H, Owen N, Schaper NC, Healy GN, Dunstan DW. Associations of 24 h time-use compositions of sitting, standing, physical activity and sleeping with optimal cardiometabolic risk and glycaemic control: The Maastricht Study. Diabetologia 2024:10.1007/s00125-024-06145-0. [PMID: 38656371 DOI: 10.1007/s00125-024-06145-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Accepted: 02/28/2024] [Indexed: 04/26/2024]
Abstract
AIMS/HYPOTHESIS The associations of sitting, standing, physical activity and sleep with cardiometabolic health and glycaemic control markers are interrelated. We aimed to identify 24 h time-use compositions associated with optimal metabolic and glycaemic control and determine whether these varied by diabetes status. METHODS Thigh-worn activPAL data from 2388 participants aged 40-75 years (48.7% female; mean age 60.1 [SD = 8.1] years; n=684 with type 2 diabetes) in The Maastricht Study were examined. Compositional isometric log ratios were generated from mean 24 h time use (sitting, standing, light-intensity physical activity [LPA], moderate-to-vigorous physical activity [MVPA] and sleeping) and regressed with outcomes of waist circumference, fasting plasma glucose (FPG), 2 h plasma glucose, HbA1c, the Matsuda index expressed as z scores, and with a clustered cardiometabolic risk score. Overall analyses were adjusted for demographics, smoking, dietary intake and diabetes status, and interaction by diabetes status was examined separately. The estimated difference when substituting 30 min of one behaviour with another was determined with isotemporal substitution. To identify optimal time use, all combinations of 24 h compositions possible within the study footprint (1st-99th percentile of each behaviour) were investigated to determine those cross-sectionally associated with the most-optimal outcome (top 5%) for each outcome measure. RESULTS Compositions lower in sitting time and with greater standing time, physical activity and sleeping had the most beneficial associations with outcomes. Associations were stronger in participants with type 2 diabetes (p<0.05 for interactions), with larger estimated benefits for waist circumference, FPG and HbA1c when sitting was replaced by LPA or MVPA in those with type 2 diabetes vs the overall sample. The mean (range) optimal compositions of 24 h time use, considering all outcomes, were 6 h (range 5 h 40 min-7 h 10 min) for sitting, 5 h 10 min (4 h 10 min-6 h 10 min) for standing, 2 h 10 min (2 h-2 h 20 min) for LPA, 2 h 10 min (1 h 40 min-2 h 20 min) for MVPA and 8 h 20 min (7 h 30 min-9 h) for sleeping. CONCLUSIONS/INTERPRETATION Shorter sitting time and more time spent standing, undergoing physical activity and sleeping are associated with preferable cardiometabolic health. The substitutions of behavioural time use were significantly stronger in their associations with glycaemic control in those with type 2 diabetes compared with those with normoglycaemic metabolism, especially when sitting time was balanced with greater physical activity.
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Affiliation(s)
- Christian J Brakenridge
- Baker Heart and Diabetes Institute, Melbourne, VIC, Australia.
- Mary Mackillop Institute for Health Research, Australian Catholic University, Melbourne, VIC, Australia.
- Active Life Lab, South-Eastern Finland University of Applied Sciences, Mikkeli, Finland.
- Centre for Urban Transitions, Swinburne University of Technology, Melbourne, VIC, Australia.
| | - Annemarie Koster
- Department of Social Medicine, Maastricht University, Maastricht, the Netherlands
- CAPHRI Care and Public Health Research Institute, Maastricht University, Maastricht, the Netherlands
| | - Bastiaan E de Galan
- Department of Internal Medicine, Maastricht University Medical Center+, Maastricht, the Netherlands
- Department of Internal Medicine, Radboud University Medical Centre, Nijmegen, the Netherlands
- CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, the Netherlands
| | - Alison Carver
- National Centre for Healthy Ageing, The School of Translational Medicine, Monash University, Melbourne, VIC, Australia
| | - Dorothea Dumuid
- Alliance for Research in Exercise, Nutrition and Activity, University of South Australia, Adelaide, SA, Australia
| | - Francis Q S Dzakpasu
- Baker Heart and Diabetes Institute, Melbourne, VIC, Australia
- Mary Mackillop Institute for Health Research, Australian Catholic University, Melbourne, VIC, Australia
| | - Simone J P M Eussen
- CAPHRI Care and Public Health Research Institute, Maastricht University, Maastricht, the Netherlands
- CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, the Netherlands
- Department of Epidemiology, Maastricht University, Maastricht, the Netherlands
| | - Hans H C M Savelberg
- Department of Nutrition and Movement Science, Maastricht University, Maastricht, the Netherlands
- NUTRIM School for Nutrition and Translational Research in Metabolism, Maastricht University, Maastricht, the Netherlands
| | - Hans Bosma
- Department of Social Medicine, Maastricht University, Maastricht, the Netherlands
- CAPHRI Care and Public Health Research Institute, Maastricht University, Maastricht, the Netherlands
| | - Neville Owen
- Baker Heart and Diabetes Institute, Melbourne, VIC, Australia
- Centre for Urban Transitions, Swinburne University of Technology, Melbourne, VIC, Australia
| | - Nicolaas C Schaper
- CAPHRI Care and Public Health Research Institute, Maastricht University, Maastricht, the Netherlands
- CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, the Netherlands
| | - Genevieve N Healy
- School of Human Movement and Nutrition Sciences, The University of Queensland, Brisbane, QLD, Australia
| | - David W Dunstan
- Baker Heart and Diabetes Institute, Melbourne, VIC, Australia
- Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Melbourne, VIC, Australia
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Contardo Ayala AM, Ridgers ND, Timperio A, Arundell L, Dunstan DW, Hesketh KD, Daly RM, Salmon J. The association between device-measured sitting time and cardiometabolic health risk factors in children. BMC Public Health 2024; 24:1015. [PMID: 38609909 PMCID: PMC11010425 DOI: 10.1186/s12889-024-18495-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Accepted: 04/01/2024] [Indexed: 04/14/2024] Open
Abstract
BACKGROUND There is limited evidence of the associations between postural-derived sitting time, waist-worn derived sedentary time and children's health and the moderation effect of physical activity (PA). This study examined associations of children's device-measured sitting time with cardiometabolic health risk factors, including moderation by physical activity. METHODS Cross-sectional baseline data from children (mean-age 8.2 ± 0.5 years) in Melbourne, Australia (2010) participating in the TransformUs program were used. Children simultaneously wore an activPAL to assess sitting time and an ActiGraph GT3X to assess sedentary time and physical activity intensity. Cardiometabolic health risk factors included: adiposity (body mass index [BMI], waist circumference [WC]), systolic and diastolic blood pressure (SBP, DBP), high-density lipoprotein (HDL), low-density lipoprotein (LDL), cholesterol, triglycerides, fasting plasma glucose (FPG), serum insulin, and 25-hydroxyvitaminD (25[OH]D). Linear regression models (n = 71-113) assessed associations between sitting time with each health risk factor, adjusted for different PA intensities (i.e. light [LIPA], moderate-vigorous intensities [MVPA], separately on each model), age, sex, adiposity, and clustering by school. Interaction terms examined moderation. The analyses were repeated using device-measured sedentary time (i.e. ActiGraph GT3X) for comparison. RESULTS Sitting time was positively associated with SBP (b = 0.015; 95%CI: 0.004, 0.026), DBP (b = 0.012; 95%CI:0.004, 0.020), and FPG (b = 0.001; 95%CI: 0.000, 0.000), after adjusting for higher PA intensities. The association between sitting time and insulin (b = 0.003; 95%CI: 0.000, 0.006) was attenuated after adjusting for higher PA intensities. When the models were adjusted for LIPA and MVPA, there was a negative association with LDL (b=-0.001; 95%CI: -0.002, -0.000 and b=-0.001; 95%CI: -0.003, -0.000, respectively). There was a negative association of sedentary time with WCz (b=-0.003; 95%CI: -0.005, 0.000) and BMIz (b=-0.003; 95%CI: -0.006, -0.000) when the models were adjusted by MVPA. Sedentary time was positively associated with triglycerides (b = 0.001; 95%CI: 0.000, 0.001) but attenuated after adjusting for MVPA. No evidence of moderation effects was found. CONCLUSIONS Higher volumes of sitting and sedentary time were associated with some adverse associations on some cardiometabolic health risk factors in children. These associations were more evident when sitting time was the predictor. This suggests that reducing time spent sitting may benefit some cardiometabolic health outcomes, but future experimental research is needed to confirm causal relationships and identify the biological mechanisms that might be involved. TRIAL REGISTRATION Australian New Zealand Clinical Trials Registry: ACTRN12609000715279.
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Affiliation(s)
- Ana María Contardo Ayala
- Institute for Physical Activity and Nutrition (IPAN), School of Exercise and Nutrition Sciences, Deakin University, 221 Burwood Highway, Geelong, Victoria, Australia.
| | - Nicola D Ridgers
- Institute for Physical Activity and Nutrition (IPAN), School of Exercise and Nutrition Sciences, Deakin University, 221 Burwood Highway, Geelong, Victoria, Australia
- Alliance for Research in Exercise, Nutrition and Activity (ARENA), Allied Health and Human Performance, University of South Australia, Adelaide, South Australia, Australia
| | - Anna Timperio
- Institute for Physical Activity and Nutrition (IPAN), School of Exercise and Nutrition Sciences, Deakin University, 221 Burwood Highway, Geelong, Victoria, Australia
| | - Lauren Arundell
- Institute for Physical Activity and Nutrition (IPAN), School of Exercise and Nutrition Sciences, Deakin University, 221 Burwood Highway, Geelong, Victoria, Australia
| | - David W Dunstan
- Institute for Physical Activity and Nutrition (IPAN), School of Exercise and Nutrition Sciences, Deakin University, 221 Burwood Highway, Geelong, Victoria, Australia
| | - Kylie D Hesketh
- Institute for Physical Activity and Nutrition (IPAN), School of Exercise and Nutrition Sciences, Deakin University, 221 Burwood Highway, Geelong, Victoria, Australia
| | - Robin M Daly
- Institute for Physical Activity and Nutrition (IPAN), School of Exercise and Nutrition Sciences, Deakin University, 221 Burwood Highway, Geelong, Victoria, Australia
| | - Jo Salmon
- Institute for Physical Activity and Nutrition (IPAN), School of Exercise and Nutrition Sciences, Deakin University, 221 Burwood Highway, Geelong, Victoria, Australia
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Ringin E, Dunstan DW, Meyer D, McIntyre RS, Owen N, Berk M, Hallgren M, Rossell SL, Van Rheenen TE. Relative associations of behavioral and physiological risks for cardiometabolic disease with cognition in bipolar disorder during mid and later-life: findings from the UK biobank. Psychol Med 2024:1-11. [PMID: 38563285 DOI: 10.1017/s0033291724000722] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
BACKGROUND Cardiometabolic disease risk factors are disproportionately prevalent in bipolar disorder (BD) and are associated with cognitive impairment. It is, however, unknown which health risk factors for cardiometabolic disease are relevant to cognition in BD. This study aimed to identify the cardiometabolic disease risk factors that are the most important correlates of cognitive impairment in BD; and to examine whether the nature of the relationships vary between mid and later life. METHODS Data from the UK Biobank were available for 966 participants with BD, aged between 40 and 69 years. Individual cardiometabolic disease risk factors were initially regressed onto a global cognition score in separate models for the following risk factor domains; (1) health risk behaviors (physical activity, sedentary behavior, smoking, and sleep) and (2) physiological risk factors, stratified into (2a) anthropometric and clinical risk (handgrip strength, body composition, and blood pressure), and (2b) cardiometabolic disease risk biomarkers (CRP, lipid profile, and HbA1c). A final combined multivariate regression model for global cognition was then fitted, including only the predictor variables that were significantly associated with cognition in the previous models. RESULTS In the final combined model, lower mentally active and higher passive sedentary behavior, higher levels of physical activity, inadequate sleep duration, higher systolic and lower diastolic blood pressure, and lower handgrip strength were associated with worse global cognition. CONCLUSIONS Health risk behaviors, as well as blood pressure and muscular strength, are associated with cognitive function in BD, whereas other traditional physiological cardiometabolic disease risk factors are not.
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Affiliation(s)
- Elysha Ringin
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Melbourne, Australia
| | - David W Dunstan
- Physical Activity Laboratory, Baker Heart & Diabetes Institute, Melbourne, VIC, Australia
- Deakin University, Institute for Physical Activity and Nutrition (IPAN), School of Exercise and Nutrition Sciences, Geelong, Australia
| | - Denny Meyer
- Centre for Mental Health, School of Health Sciences, Swinburne University, Melbourne, Australia
| | - Roger S McIntyre
- Department of Psychiatry and Pharmacology, University of Toronto, Toronto, Canada
| | - Neville Owen
- Physical Activity Laboratory, Baker Heart & Diabetes Institute, Melbourne, VIC, Australia
- Centre for Urban Transitions, Swinburne University of Technology, Melbourne, VIC, Australia
| | - Michael Berk
- Deakin University, The Institute for Mental and Physical Health and Clinical Translation, Barwon Health, Geelong, VIC, Australia
- Department of Psychiatry, University of Melbourne, Melbourne, Australia
- Orygen Youth Health, Melbourne, Australia
| | - Mats Hallgren
- Epidemiology of Psychiatric Conditions, Substance Use and Social Environment (EPiCSS), Department of Public Health Sciences, Karolinska Institutet, Stockholm, Sweden
| | - Susan L Rossell
- Centre for Mental Health, School of Health Sciences, Swinburne University, Melbourne, Australia
- St Vincent's Mental Health, St Vincent's Hospital, Melbourne, VIC, Australia
| | - Tamsyn E Van Rheenen
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Melbourne, Australia
- Centre for Mental Health, School of Health Sciences, Swinburne University, Melbourne, Australia
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Zou L, Herold F, Cheval B, Wheeler MJ, Pindus DM, Erickson KI, Raichlen DA, Alexander GE, Müller NG, Dunstan DW, Kramer AF, Hillman CH, Hallgren M, Ekelund U, Maltagliati S, Owen N. Sedentary behavior and lifespan brain health. Trends Cogn Sci 2024; 28:369-382. [PMID: 38431428 DOI: 10.1016/j.tics.2024.02.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Revised: 02/02/2024] [Accepted: 02/06/2024] [Indexed: 03/05/2024]
Abstract
Higher levels of physical activity are known to benefit aspects of brain health across the lifespan. However, the role of sedentary behavior (SB) is less well understood. In this review we summarize and discuss evidence on the role of SB on brain health (including cognitive performance, structural or functional brain measures, and dementia risk) for different age groups, critically compare assessment approaches to capture SB, and offer insights into emerging opportunities to assess SB via digital technologies. Across the lifespan, specific characteristics of SB (particularly whether they are cognitively active or cognitively passive) potentially act as moderators influencing the associations between SB and specific brain health outcomes. We outline challenges and opportunities for future research aiming to provide more robust empirical evidence on these observations.
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Affiliation(s)
- Liye Zou
- Body-Brain-Mind Laboratory, School of Psychology, Shenzhen University, Shenzhen, China.
| | - Fabian Herold
- Body-Brain-Mind Laboratory, School of Psychology, Shenzhen University, Shenzhen, China; Research Group Degenerative and Chronic Diseases, Movement, Faculty of Health Sciences Brandenburg, University of Potsdam, 14476 Potsdam, Germany
| | - Boris Cheval
- Department of Sport Sciences and Physical Education, Ecole Normale Supérieure Rennes, Bruz, France; Laboratory VIPS2, University of Rennes, Rennes, France
| | - Michael J Wheeler
- Physical Activity Laboratory, Baker Heart & Diabetes Institute, Melbourne, Victoria, Australia; Institute for Physical Activity and Nutrition (IPAN), School of Exercise and Nutrition Sciences, Deakin University, Geelong, Australia
| | - Dominika M Pindus
- Kinesiology and Community Health, University of Illinois at Chicago, Chicago, IL, USA; Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, USA; Neuroscience Program, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Kirk I Erickson
- AdventHealth Research Institute, Department of Neuroscience, AdventHealth, Orlando, FL, USA; Department of Psychology, University of Pittsburgh, Pittsburgh, PA, USA; Center for the Neural Basis of Cognition, University of Pittsburgh, Pittsburgh, PA, USA
| | - David A Raichlen
- Human and Evolutionary Biology Section, Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089, USA; Department of Anthropology, University of Southern California, Los Angeles, CA 90089, USA
| | - Gene E Alexander
- BIO5 Institute, University of Arizona, Tucson, AZ 85721, USA; Department of Psychology, University of Arizona, Tucson, AZ 85721, USA; Evelyn F. McKnight Brain Institute, University of Arizona, Tucson, AZ 85721, USA; Department of Psychiatry, University of Arizona, Tucson, AZ 85721, USA; Neuroscience Graduate Interdisciplinary Program, University of Arizona, Tucson, AZ 85721, USA; Physiological Sciences Graduate Interdisciplinary Program, University of Arizona, Tucson, AZ85721, USA
| | - Notger G Müller
- Research Group Degenerative and Chronic Diseases, Movement, Faculty of Health Sciences Brandenburg, University of Potsdam, 14476 Potsdam, Germany
| | - David W Dunstan
- Physical Activity Laboratory, Baker Heart & Diabetes Institute, Melbourne, Victoria, Australia; Institute for Physical Activity and Nutrition (IPAN), School of Exercise and Nutrition Sciences, Deakin University, Geelong, Australia
| | - Arthur F Kramer
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, USA; Center for Cognitive and Brain Health, Northeastern University, Boston, MA, USA; Department of Psychology, Northeastern University, Boston, MA, 02115, USA
| | - Charles H Hillman
- Center for Cognitive and Brain Health, Northeastern University, Boston, MA, USA; Department of Psychology, Northeastern University, Boston, MA, 02115, USA; Department of Physical Therapy, Movement, & Rehabilitation Sciences, Northeastern University, Boston, MA, 02115, USA
| | - Mats Hallgren
- Epidemiology of Psychiatric Conditions, Substance Use and Social Environment (EPiCSS), Department of Public Health Sciences, Karolinska Institutet, Solna, Sweden
| | - Ulf Ekelund
- Department of Sports Medicine, Norwegian School of Sport Sciences, Oslo, Norway; Department of Chronic Diseases and Ageing, The Norwegian Institute for Public Health, Oslo, Norway
| | - Silvio Maltagliati
- Human and Evolutionary Biology Section, Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089, USA
| | - Neville Owen
- Physical Activity Laboratory, Baker Heart & Diabetes Institute, Melbourne, Victoria, Australia; Centre for Urban Transitions, Swinburne University of Technology, Melbourne, Victoria, Australia
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Brown V, Sheppard L, Salmon J, Arundell L, Cerin E, Ridgers ND, Hesketh KD, Daly RM, Dunstan DW, Brown H, Gatta JD, Chinapaw JMM, Moodie M. Cost-effectiveness of reducing children's sedentary time and increasing physical activity at school: the Transform-Us! intervention. Int J Behav Nutr Phys Act 2024; 21:15. [PMID: 38347579 PMCID: PMC10860323 DOI: 10.1186/s12966-024-01560-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2023] [Accepted: 01/08/2024] [Indexed: 02/15/2024] Open
Abstract
BACKGROUND Improving physical activity and reducing sedentary behavior represent important areas for intervention in childhood in order to reduce the burden of chronic disease related to obesity and physical inactivity in later life. This paper aims to determine the cost-effectiveness of a multi-arm primary school-based intervention to increase physical activity and/or reduce sedentary time in 8-9 year old children (Transform-Us!). METHODS Modelled cost-utility analysis, using costs and effects from a cluster randomized controlled trial of a 30-month intervention that used pedagogical and environmental strategies to reduce and break up sedentary behaviour (SB-I), promote physical activity (PA-I), or a combined approach (PA + SB-I), compared to current practice. A validated multiple-cohort lifetable model (ACE-Obesity Policy model) estimated the obesity and physical activity-related health outcomes (measured as change in body mass index and change in metabolic equivalent task minutes respectively) and healthcare cost-savings over the cohort's lifetime from the public-payer perspective, assuming the intervention was delivered to all 8-9 year old children attending Australian Government primary schools. Sensitivity analyses tested the impact on cost-effectiveness of varying key input parameters, including maintenance of intervention effect assumptions. RESULTS Cost-effectiveness results demonstrated that, when compared to control schools, the PA-I and SB-I intervention arms were "dominant", meaning that they resulted in net health benefits and healthcare cost-savings if the intervention effects were maintained. When the costs and effects of these intervention arms were extrapolated to the Australian population, results suggested significant potential as obesity prevention measures (PA-I: 60,780 HALYs saved (95% UI 15,007-109,413), healthcare cost-savings AUD641M (95% UI AUD165M-$1.1B); SB-I: 61,126 HALYs saved (95% UI 11,770 - 111,249), healthcare cost-savings AUD654M (95% UI AUD126M-1.2B)). The PA-I and SB-I interventions remained cost-effective in sensitivity analysis, assuming the full decay of intervention effect after 10 years. CONCLUSIONS The PA-I and SB-I Transform-Us! intervention arms represent good value for money and could lead to health benefits and healthcare cost-savings arising from the prevention of chronic disease in later life if intervention effects are sustained. TRIAL REGISTRATION International Standard Randomized Controlled Trial Number (ISRCTN83725066). Australia and New Zealand Clinical Trials Registry Number (ACTRN12609000715279).
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Affiliation(s)
- Vicki Brown
- Deakin University, Deakin Health Economics, Global Centre for Preventive Health and Nutrition (GLOBE), Institute for Health Transformation (IHT), Geelong, Australia.
| | - Lauren Sheppard
- Deakin University, Deakin Health Economics, Institute for Health Transformation, Geelong, Australia
| | - Jo Salmon
- Deakin University, Institute for Physical Activity and Nutrition (IPAN), Geelong, Australia
| | - Lauren Arundell
- Deakin University, Institute for Physical Activity and Nutrition (IPAN), Geelong, Australia
| | - Ester Cerin
- Mary McKillop Institute for Health Research, Australian Catholic University, Melbourne, Australia
| | - Nicola D Ridgers
- Allied Health and Human Performance, Alliance for Research in Exercise, Nutrition and Activity (ARENA), University of South Australia; Deakin University, Institute for Physical Activity and Nutrition, Geelong, Australia
| | - Kylie D Hesketh
- Deakin University, Institute for Physical Activity and Nutrition (IPAN), Geelong, Australia
| | - Robin M Daly
- Deakin University, Institute for Physical Activity and Nutrition (IPAN), Geelong, Australia
| | | | - Helen Brown
- Deakin University, Institute for Physical Activity and Nutrition (IPAN), Geelong, Australia
| | - Jacqueline Della Gatta
- Deakin University, Institute for Physical Activity and Nutrition (IPAN), Geelong, Australia
| | - J M M Chinapaw
- Department of Public and Occupational Health, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Public Health research institute, Amsterdam, Netherlands
| | - Marj Moodie
- Deakin University, Deakin Health Economics, Institute for Health Transformation, Geelong, Australia
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Daryabeygi-Khotbehsara R, Rawstorn JC, Dunstan DW, Shariful Islam SM, Abdelrazek M, Kouzani AZ, Thummala P, McVicar J, Maddison R. A Bluetooth-Enabled Device for Real-Time Detection of Sitting, Standing, and Walking: Cross-Sectional Validation Study. JMIR Form Res 2024; 8:e47157. [PMID: 38265864 PMCID: PMC10851128 DOI: 10.2196/47157] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2023] [Revised: 10/20/2023] [Accepted: 10/29/2023] [Indexed: 01/25/2024] Open
Abstract
BACKGROUND This study assesses the accuracy of a Bluetooth-enabled prototype activity tracker called the Sedentary behaviOR Detector (SORD) device in identifying sedentary, standing, and walking behaviors in a group of adult participants. OBJECTIVE The primary objective of this study was to determine the criterion and convergent validity of SORD against direct observation and activPAL. METHODS A total of 15 healthy adults wore SORD and activPAL devices on their thighs while engaging in activities (lying, reclining, sitting, standing, and walking). Direct observation was facilitated with cameras. Algorithms were developed using the Python programming language. The Bland-Altman method was used to assess the level of agreement. RESULTS Overall, 1 model generated a low level of bias and high precision for SORD. In this model, accuracy, sensitivity, and specificity were all above 0.95 for detecting sitting, reclining, standing, and walking. Bland-Altman results showed that mean biases between SORD and direct observation were 0.3% for sitting and reclining (limits of agreement [LoA]=-0.3% to 0.9%), 1.19% for standing (LoA=-1.5% to 3.42%), and -4.71% for walking (LoA=-9.26% to -0.16%). The mean biases between SORD and activPAL were -3.45% for sitting and reclining (LoA=-11.59% to 4.68%), 7.45% for standing (LoA=-5.04% to 19.95%), and -5.40% for walking (LoA=-11.44% to 0.64%). CONCLUSIONS Results suggest that SORD is a valid device for detecting sitting, standing, and walking, which was demonstrated by excellent accuracy compared to direct observation. SORD offers promise for future inclusion in theory-based, real-time, and adaptive interventions to encourage physical activity and reduce sedentary behavior.
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Affiliation(s)
- Reza Daryabeygi-Khotbehsara
- Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Melbourne Burwood, Australia
| | - Jonathan C Rawstorn
- Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Melbourne Burwood, Australia
| | - David W Dunstan
- Baker-Deakin Department of Lifestyle and Diabetes, Melbourne Burwood, Australia
| | - Sheikh Mohammed Shariful Islam
- Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Melbourne Burwood, Australia
| | - Mohamed Abdelrazek
- School of Information Technology, Deakin University, Melbourne Burwood, Australia
| | - Abbas Z Kouzani
- School of Engineering, Deakin University, Geelong, Australia
| | - Poojith Thummala
- School of Information Technology, Deakin University, Melbourne Burwood, Australia
| | - Jenna McVicar
- Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Melbourne Burwood, Australia
| | - Ralph Maddison
- Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Melbourne Burwood, Australia
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Lin CY, Shibata A, Ishii K, Koohsari MJ, Hadgraft N, Dunstan DW, Owen N, Oka K. Reallocating desk workers' sitting time to standing or stepping: associations with work performance. Occup Med (Lond) 2023; 73:575-580. [PMID: 38104251 PMCID: PMC10824261 DOI: 10.1093/occmed/kqad142] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2023] Open
Abstract
BACKGROUND Studies have suggested that sitting time at work may lead to underperformance but they may underestimate the benefits to desk workers' performance of reducing occupational sitting time without considering the relative effects of the specific activities replaced. AIMS To estimate differences in work performance (presenteeism, absenteeism and engagement) when occupational sitting time is reallocated to standing/stepping in desk workers. METHODS Data for middle-aged desk workers were from a Japan-wide online survey (n = 2228). Self-report proportion of occupational sitting and standing/stepping, work hours and work performance indicators, including absolute (ratings relating only to self) and relative (ratings of self, compared to others) presenteeism and absenteeism, and dimensions of work engagement, were collected. Partition and isotemporal substitution models were used to investigate the associations of occupational sitting and standing/stepping time with work performance, including their reallocation effects. RESULTS In partition models, longer occupational sitting time was associated with a lower absolute presenteeism score (i.e. less productivity), lower absolute absenteeism (i.e. longer-than-expected work hours), and lower engagement. Longer occupational standing/stepping time was associated with lower absolute absenteeism and more engagement. Isotemporal substitution models showed that each hour of occupational sitting reallocated to standing/stepping was favourably associated with overall work engagement (B = 0.087; 95% confidence interval 0.051, 0.122) and its dimensions (B ranged from 0.078 to 0.092), but was not associated with presenteeism or absenteeism. CONCLUSIONS These findings suggest that management support and practical initiatives to encourage desk workers to replace portions of their sitting time with standing/stepping may contribute to enhanced work engagement.
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Affiliation(s)
- C-Y Lin
- Department of Public Health, College of Public Health, China Medical University, Taichung, 406040Taiwan
- Faculty of Sport Sciences, Waseda University, Tokorozawa, 359-1192Japan
- Centre for Urban Transitions, Swinburne University of Technology, Melbourne, Victoria, 3122Australia
| | - A Shibata
- Institute of Health and Sport Sciences, University of Tsukuba, Tsukuba, 305-8577Japan
| | - K Ishii
- Faculty of Sport Sciences, Waseda University, Tokorozawa, 359-1192Japan
| | - M J Koohsari
- Faculty of Sport Sciences, Waseda University, Tokorozawa, 359-1192Japan
- School of Knowledge Science, Japan Advanced Institute of Science and Technology, Nomi, 923-1292Japan
- Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong, Victoria, 3216Australia
| | - N Hadgraft
- Centre for Urban Transitions, Swinburne University of Technology, Melbourne, Victoria, 3122Australia
- Physical Activity Laboratory, Baker Heart & Diabetes Institute, Melbourne, Victoria, 3004Australia
| | - D W Dunstan
- Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong, Victoria, 3216Australia
- Physical Activity Laboratory, Baker Heart & Diabetes Institute, Melbourne, Victoria, 3004Australia
| | - N Owen
- Centre for Urban Transitions, Swinburne University of Technology, Melbourne, Victoria, 3122Australia
- Physical Activity Laboratory, Baker Heart & Diabetes Institute, Melbourne, Victoria, 3004Australia
| | - K Oka
- Faculty of Sport Sciences, Waseda University, Tokorozawa, 359-1192Japan
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8
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Edwardson CL, Abell L, Clarke-Cornwell A, Dunstan DW, Gray LJ, Healy GN, Hadjiconstantinou M, Wilson P, Maylor B, Munir F, Biddle SJ. Implementation and engagement of the SMART Work & Life sitting reduction intervention: an exploratory analysis on intervention effectiveness. Int J Behav Nutr Phys Act 2023; 20:148. [PMID: 38115044 PMCID: PMC10729557 DOI: 10.1186/s12966-023-01548-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Accepted: 12/09/2023] [Indexed: 12/21/2023] Open
Abstract
BACKGROUND To enhance the impact of interventions, it is important to understand how intervention engagement relates to study outcomes. We report on the level of implementation and engagement with the SMART Work & Life (SWAL) programme (delivered with (SWAL plus desk) and without a height-adjustable desk (SWAL)) and explore the effects of different levels of this on change in daily sitting time in comparison to the control group. METHODS The extent of intervention delivery by workplace champions and the extent of engagement by champions and participants (staff) with each intervention activity was assessed by training attendance logs, workplace champion withdrawal dates, intervention activities logs and questionnaires. These data were used to assess whether a cluster met defined criteria for low, medium, or high implementation and engagement or none of these. Mixed effects linear regression analyses tested whether change in sitting time varied by: (i) the number of intervention activities implemented and engaged with, and (ii) the percentage of implementation and engagement with all intervention strategies. RESULTS Workplace champions were recruited for all clusters, with 51/52 (98%) attending training. Overall, 12/27 (44.4%) SWAL and 9/25 (36.0%) SWAL plus desk clusters implemented all main intervention strategies. Across remaining clusters, the level of intervention implementation varied. Those in the SWAL (n = 8 (29.6%) clusters, 80 (32.1%) participants) and SWAL plus desk (n = 5 (20.0%) clusters, 41 (17.1%) participants) intervention groups who implemented and engaged with the most intervention strategies and had the highest percentage of cluster implementation and engagement with all intervention strategies sat for 30.9 (95% CI -53.9 to -7.9, p = 0.01) and 75.6 (95% CI -103.6 to -47.7, p < 0.001) fewer minutes/day respectively compared to the control group at 12 month follow up. These differences were larger than the complete case analysis. The differences in sitting time observed for the medium and low levels were similar to the complete case analysis. CONCLUSIONS Most intervention strategies were delivered to some extent across the clusters although there was large variation. Superior effects for sitting reduction were seen for those intervention groups who implemented and engaged with the most intervention components and had the highest level of cluster implementation and engagement. TRIAL REGISTRATION ISRCTN11618007. Registered on 24 January 2018. https://www.isrctn.com/ISRCTNISRCTN11618007 .
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Affiliation(s)
- Charlotte L Edwardson
- Diabetes Research Centre, University of Leicester, Leicester, LE5 4PW, UK.
- NIHR Leicester Biomedical Research Centre, Leicester, LE5 4PW, UK.
| | - Lucy Abell
- Department of Population Health Sciences, University of Leicester, Leicester, LE1 7RH, UK
| | - Alex Clarke-Cornwell
- School of Health & Society, University of Salford, Salford, Greater Manchester, M6 6PU, UK
| | - David W Dunstan
- Baker Heart and Diabetes Institute, Melbourne, VIC, 3004, Australia
- Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Melbourne, VIC, 3125, Australia
| | - Laura J Gray
- NIHR Leicester Biomedical Research Centre, Leicester, LE5 4PW, UK
- Department of Population Health Sciences, University of Leicester, Leicester, LE1 7RH, UK
| | - Genevieve N Healy
- School of Human Movement and Nutrition Sciences, The University of Queensland, Brisbane, QLD, 4072, Australia
| | | | - Panna Wilson
- Leicester Diabetes Centre, University Hospitals of Leicester, Leicester, LE5 4PW, UK
| | - Benjamin Maylor
- Diabetes Research Centre, University of Leicester, Leicester, LE5 4PW, UK
- NIHR Leicester Biomedical Research Centre, Leicester, LE5 4PW, UK
| | - Fehmidah Munir
- School of Sport, Exercise and Health Sciences, Loughborough University, Leicestershire, LE11 3TU, UK
| | - Stuart Jh Biddle
- Centre for Health Research, University of Southern Queensland, Springfield Central, QLD, 4300, Australia
- Faculty of Sport & Health Sciences, University of Jyväskylä, Jyväskylä, FI-40014, Finland
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9
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Dzakpasu FQS, Owen N, Carver A, Brakenridge CJ, Eakin EG, Healy GN, Lamontagne AD, Moodie M, Coenen P, Straker L, Dunstan DW. Changes in Desk-Based Workers' Sitting, Standing, and Stepping Time: Short- and Longer-Term Effects on Musculoskeletal Pain. Med Sci Sports Exerc 2023; 55:2241-2252. [PMID: 37729188 DOI: 10.1249/mss.0000000000003248] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/22/2023]
Abstract
PURPOSE Sitting at work can be associated with musculoskeletal pain, but the effect of reductions in sitting is not well understood. We examined relationships with musculoskeletal pain of changes in sitting, standing, stepping, and short and long bouts of these behaviors. METHODS Analyses pooled data from 224 desk workers (68.4% women; mean ± SD age = 45.5 ± 9.4 yr; body mass index = 28.1 ± 6.1 kg⋅m -2 ) in intervention trial. Device-assessed (activPAL3) sitting, standing, and stepping time and multisite musculoskeletal pain (Nordic Questionnaire; 12 body areas) were assessed at baseline, 3 months, and 12 months. Compositional data analyses in linear mixed-effects regressions examined relationships within 16 waking hours of the behaviors and their short and long bouts, with changes from baseline in acute and chronic multisite musculoskeletal pain at 3 and 12 months. Analyses were adjusted for initial group randomization and relevant covariates. RESULTS At 3 months, increased standing relative to changes in other compositions was significantly associated with increased multisite musculoskeletal pain (acute: β = 1.54, 95% confidence interval [CI] = 0.10 to 2.98; chronic: β = 1.49, 95% CI = 0.12 to 2.83). By contrast, increased stepping relative to changes in other compositions was significantly associated with reduced multisite musculoskeletal pain (acute: β = -1.49, 95% CI = -2.97 to -0.02; chronic: β = -1.87, 95% CI = -3.75 to -0.01). Neither sitting reduction relative to changes in other compositions nor changes in short bouts relative to long bouts of the behaviors were significantly associated with multisite musculoskeletal pain changes. At 12 months, there were no significant associations for any of the compositional changes. CONCLUSIONS In the short term, while increasing standing with reduced sitting time can be unfavorable, concurrently increasing stepping could potentially reduce musculoskeletal pain. In the longer term, musculoskeletal pain may not be increased by moderate reductions in sitting time through spending more time standing or stepping.
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Affiliation(s)
- Francis Q S Dzakpasu
- Mary MacKillop Institute for Health Research, Australian Catholic University, Melbourne, VIC, AUSTRALIA
- Physical Activity Laboratory, Baker Heart and Diabetes Institute, Melbourne, VIC, AUSTRALIA
| | - Neville Owen
- Physical Activity Laboratory, Baker Heart and Diabetes Institute, Melbourne, VIC, AUSTRALIA
- Centre for Urban Transitions, Swinburne University of Technology, Melbourne, VIC, AUSTRALIA
| | - Alison Carver
- National Centre for Healthy Ageing, Peninsula Clinical School, Monash University, Frankston, VIC, AUSTRALIA
| | - Christian J Brakenridge
- Physical Activity Laboratory, Baker Heart and Diabetes Institute, Melbourne, VIC, AUSTRALIA
- Active Life Lab, South-Eastern Finland University of Applied Sciences, Mikkeli, FINLAND
| | - Elizabeth G Eakin
- School of Public Health, The University of Queensland, Brisbane, QLD, AUSTRALIA
| | - Genevieve N Healy
- School of Human Movement and Nutrition Sciences, The University of Queensland, Brisbane, QLD, AUSTRALIA
| | - Anthony D Lamontagne
- Institute for Health Transformation and School of Health and Social Development, Deakin University, Geelong, VIC, AUSTRALIA
| | - Marj Moodie
- Deakin Health Economics, Institute for Health Transformation, Deakin University, Geelong, VIC, AUSTRALIA
| | - Pieter Coenen
- Public and Occupational Health, Amsterdam UMC Location Vrije Universiteit, Amsterdam, THE NETHERLANDS
- Amsterdam Public Health, Societal Participation and Health, Amsterdam, THE NETHERLANDS
| | - Leon Straker
- Curtin School of Allied Health, Curtin University, Perth, WA, AUSTRALIA
| | - David W Dunstan
- Physical Activity Laboratory, Baker Heart and Diabetes Institute, Melbourne, VIC, AUSTRALIA
- Institute for Physical Activity and Nutrition (IPAN), School of Exercise and Nutrition Sciences, Deakin University, Geelong, VIC, AUSTRALIA
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10
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Edwardson CL, Maylor BD, Biddle SJH, Clarke-Cornwell AM, Clemes SA, Davies MJ, Dunstan DW, Granat MH, Gray LJ, Hadjiconstantinou M, Healy GN, Wilson P, Munir F, Yates T, Eborall H. Participant and workplace champion experiences of an intervention designed to reduce sitting time in desk-based workers: SMART work & life. Int J Behav Nutr Phys Act 2023; 20:142. [PMID: 38037043 PMCID: PMC10691052 DOI: 10.1186/s12966-023-01539-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Accepted: 11/14/2023] [Indexed: 12/02/2023] Open
Abstract
BACKGROUND A cluster randomised controlled trial demonstrated the effectiveness of the SMART Work & Life (SWAL) behaviour change intervention, with and without a height-adjustable desk, for reducing sitting time in desk-based workers. Staff within organisations volunteered to be trained to facilitate delivery of the SWAL intervention and act as workplace champions. This paper presents the experiences of these champions on the training and intervention delivery, and from participants on their intervention participation. METHODS Quantitative and qualitative feedback from workplace champions on their training session was collected. Participants provided quantitative feedback via questionnaires at 3 and 12 month follow-up on the intervention strategies (education, group catch ups, sitting less challenges, self-monitoring and prompts, and the height-adjustable desk [SWAL plus desk group only]). Interviews and focus groups were also conducted at 12 month follow-up with workplace champions and participants respectively to gather more detailed feedback. Transcripts were uploaded to NVivo and the constant comparative approach informed the analysis of the interviews and focus groups. RESULTS Workplace champions rated the training highly with mean scores ranging from 5.3/6 to 5.7/6 for the eight parts. Most participants felt the education increased their awareness of the health consequences of high levels of sitting (SWAL: 90.7%; SWAL plus desk: 88.2%) and motivated them to change their sitting time (SWAL: 77.5%; SWAL plus desk: 85.77%). A high percentage of participants (70%) reported finding the group catch up session helpful and worthwhile. However, focus groups highlighted mixed responses to the group catch-up sessions, sitting less challenges and self-monitoring intervention components. Participants in the SWAL plus desk group felt that having a height-adjustable desk was key in changing their behaviour, with intrinsic as well as time based factors reported as key influences on the height-adjustable desk usage. In both intervention groups, participants reported a range of benefits from the intervention including more energy, less fatigue, an increase in focus, alertness, productivity and concentration as well as less musculoskeletal problems (SWAL plus desk group only). Work-related, interpersonal, personal attributes, physical office environment and physical barriers were identified as barriers when trying to sit less and move more. CONCLUSIONS Workplace champion and participant feedback on the intervention was largely positive but it is clear that different behaviour change strategies worked for different people indicating that a 'one size fits all' approach may not be appropriate for this type of intervention. The SWAL intervention could be tested in a broader range of organisations following a few minor adaptations based on the champion and participant feedback. TRIAL REGISTRATION ISCRCTN registry (ISRCTN11618007).
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Affiliation(s)
- Charlotte L Edwardson
- Diabetes Research Centre, University of Leicester, Leicester General Hospital, Leicester, LE5 4PW, UK.
- NIHR Leicester Biomedical Research Centre, Leicester, LE5 4PW, UK.
| | - Benjamin D Maylor
- Diabetes Research Centre, University of Leicester, Leicester General Hospital, Leicester, LE5 4PW, UK
| | - Stuart J H Biddle
- Centre for Health Research, University of Southern Queensland, Springfield Central, QLD, 4350, Australia
- Faculty of Sport & Health Sciences, University of Jyväskylä, Jyväskylä, FI-40014, Finland
| | | | - Stacy A Clemes
- NIHR Leicester Biomedical Research Centre, Leicester, LE5 4PW, UK
- School of Sport, Exercise and Health Sciences, Loughborough University, Leicestershire, LE11 3TU, UK
| | - Melanie J Davies
- Diabetes Research Centre, University of Leicester, Leicester General Hospital, Leicester, LE5 4PW, UK
- NIHR Leicester Biomedical Research Centre, Leicester, LE5 4PW, UK
- Leicester Diabetes Centre, University Hospitals of Leicester, Leicester, LE5 4PW, UK
| | - David W Dunstan
- Baker Heart and Diabetes Institute, Melbourne, VIC, 3004, Australia
- Mary MacKillop Institute for Health Research, The Australian Catholic University, Melbourne, VIC, 3000, Australia
| | - Malcolm H Granat
- School of Health & Society, University of Salford, Salford, Greater Manchester, M6 6PU, UK
| | - Laura J Gray
- NIHR Leicester Biomedical Research Centre, Leicester, LE5 4PW, UK
- Department of Population Health Sciences, University of Leicester, Leicester, LE1 7RH, UK
| | | | - Genevieve N Healy
- School of Human Movement and Nutrition Sciences, The University of Queensland, Brisbane, QLD, 4072, Australia
| | - Panna Wilson
- Leicester Diabetes Centre, University Hospitals of Leicester, Leicester, LE5 4PW, UK
| | - Fehmidah Munir
- School of Sport, Exercise and Health Sciences, Loughborough University, Leicestershire, LE11 3TU, UK
| | - Thomas Yates
- Diabetes Research Centre, University of Leicester, Leicester General Hospital, Leicester, LE5 4PW, UK
- NIHR Leicester Biomedical Research Centre, Leicester, LE5 4PW, UK
| | - Helen Eborall
- Department of Population Health Sciences, University of Leicester, Leicester, LE1 7RH, UK
- Deanery of Molecular, Genetic and Population Health Sciences, The University of Edinburgh, Scotland, EH8 9AG, UK
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11
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Inam F, Bergin RJ, Mizrahi D, Dunstan DW, Moore M, Maxwell-Davis N, Denehy L, Lynch BM, Swain CTV. Diverse strategies are needed to support physical activity engagement in women who have had breast cancer. Support Care Cancer 2023; 31:648. [PMID: 37864656 PMCID: PMC10590305 DOI: 10.1007/s00520-023-08113-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2023] [Accepted: 10/09/2023] [Indexed: 10/23/2023]
Abstract
PURPOSE Physical activity can improve health in people living with and beyond breast cancer; however, how to best support physical activity participation in this population is unclear. This qualitative study sought to identify important physical activity program components for breast cancer. METHODS Women with previous breast cancer (n = 11) and allied health professionals (n = 7) participated in one-on-one semi-structured interviews (n = 15) or focus groups (n = 1). Qualitative data were analyzed using reflexive thematic analysis methods. RESULTS Four main themes were generated including (1) the need for physical activity programs; (2) person-centered programs; (3) flexible physical activity programs; and (4) systems factors. These reflected the health and non-health benefits of physical activity, the need to facilitate agency, the diversity in individual characteristics, preferences, abilities, and commitments of people with lived experience of cancer, as well as the need for physical activity programs to be integrated within the broader health system. CONCLUSION Strategies to support physical activity engagement for breast cancer should embrace the diversity of those who are diagnosed with cancer as well as the diversity in which physical activity can be achieved.
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Affiliation(s)
- Farha Inam
- Cancer Science Unit, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Parkville, Australia
| | - Rebecca J Bergin
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Australia
| | - David Mizrahi
- The Daffodil Centre, The University of Sydney, a joint venture with Cancer Council NSW, Sydney, NSW, Australia
| | - David W Dunstan
- School of Exercise and Nutrition Sciences, Institute for Physical Activity and Nutrition (IPAN), Deakin University, Melbourne, Australia
- Physical Activity Laboratory, Baker Heart and Diabetes Institute, Melbourne, Australia
| | - Melissa Moore
- Medical Oncology, St Vincent's Hospital, Melbourne, Australia
| | | | - Linda Denehy
- Department of Physiotherapy, Faculty of Medicine Dentistry and Health Sciences, Melbourne School of Health Sciences, University of Melbourne, Melbourne, Australia
- Health Services Research and Implementation Science, Peter MacCallum Cancer Centre, Melbourne, Australia
- Sir Peter MacCallum Department of Oncology, The University of Melbourne, Melbourne, Australia
| | - Brigid M Lynch
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Australia
- Physical Activity Laboratory, Baker Heart and Diabetes Institute, Melbourne, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Australia
| | - Christopher T V Swain
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Australia.
- Department of Physiotherapy, Faculty of Medicine Dentistry and Health Sciences, Melbourne School of Health Sciences, University of Melbourne, Melbourne, Australia.
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12
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Pinto AJ, Bergouignan A, Dempsey PC, Roschel H, Owen N, Gualano B, Dunstan DW. Physiology of sedentary behavior. Physiol Rev 2023; 103:2561-2622. [PMID: 37326297 PMCID: PMC10625842 DOI: 10.1152/physrev.00022.2022] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Revised: 05/10/2023] [Accepted: 06/14/2023] [Indexed: 06/17/2023] Open
Abstract
Sedentary behaviors (SB) are characterized by low energy expenditure while in a sitting or reclining posture. Evidence relevant to understanding the physiology of SB can be derived from studies employing several experimental models: bed rest, immobilization, reduced step count, and reducing/interrupting prolonged SB. We examine the relevant physiological evidence relating to body weight and energy balance, intermediary metabolism, cardiovascular and respiratory systems, the musculoskeletal system, the central nervous system, and immunity and inflammatory responses. Excessive and prolonged SB can lead to insulin resistance, vascular dysfunction, shift in substrate use toward carbohydrate oxidation, shift in muscle fiber from oxidative to glycolytic type, reduced cardiorespiratory fitness, loss of muscle mass and strength and bone mass, and increased total body fat mass and visceral fat depot, blood lipid concentrations, and inflammation. Despite marked differences across individual studies, longer term interventions aimed at reducing/interrupting SB have resulted in small, albeit marginally clinically meaningful, benefits on body weight, waist circumference, percent body fat, fasting glucose, insulin, HbA1c and HDL concentrations, systolic blood pressure, and vascular function in adults and older adults. There is more limited evidence for other health-related outcomes and physiological systems and for children and adolescents. Future research should focus on the investigation of molecular and cellular mechanisms underpinning adaptations to increasing and reducing/interrupting SB and the necessary changes in SB and physical activity to impact physiological systems and overall health in diverse population groups.
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Affiliation(s)
- Ana J Pinto
- Division of Endocrinology, Metabolism, and Diabetes, Anschutz Health and Wellness Center, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
- Applied Physiology & Nutrition Research Group, Center of Lifestyle Medicine, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, Brazil
| | - Audrey Bergouignan
- Division of Endocrinology, Metabolism, and Diabetes, Anschutz Health and Wellness Center, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
- Institut Pluridisciplinaire Hubert Curien, Centre National de la Recherche Scientifique, Université de Strasbourg, Strasbourg, France
| | - Paddy C Dempsey
- Baker Heart & Diabetes Institute, Melbourne, Victoria, Australia
- Institute for Physical Activity and Nutrition (IPAN), School of Exercise and Nutrition Sciences, Deakin University, Geelong, Victoria, Australia
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge Biomedical Campus, Cambridge, United Kingdom
- Diabetes Research Centre, College of Life Sciences, University of Leicester, Leicester, United Kingdom
| | - Hamilton Roschel
- Applied Physiology & Nutrition Research Group, Center of Lifestyle Medicine, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, Brazil
| | - Neville Owen
- Baker Heart & Diabetes Institute, Melbourne, Victoria, Australia
- Centre for Urban Transitions, Swinburne University of Technology, Melbourne, Victoria, Australia
| | - Bruno Gualano
- Applied Physiology & Nutrition Research Group, Center of Lifestyle Medicine, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, Brazil
- Food Research Center, University of Sao Paulo, Sao Paulo, Brazil
| | - David W Dunstan
- Baker Heart & Diabetes Institute, Melbourne, Victoria, Australia
- Institute for Physical Activity and Nutrition (IPAN), School of Exercise and Nutrition Sciences, Deakin University, Geelong, Victoria, Australia
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13
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Daryabeygi-Khotbehsara R, Dunstan DW, Islam SMS, Zhang Y, Abdelrazek M, Maddison R. Just-In-Time Adaptive Intervention to Sit Less and Move More in People With Type 2 Diabetes: Protocol for a Microrandomized Trial. JMIR Res Protoc 2023; 12:e41502. [PMID: 37672323 PMCID: PMC10512121 DOI: 10.2196/41502] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Revised: 04/07/2023] [Accepted: 04/14/2023] [Indexed: 09/07/2023] Open
Abstract
BACKGROUND Reducing sedentary behavior and increasing physical activity in people with type 2 diabetes (T2D) are associated with various positive health benefits. Just-in-time adaptive interventions offer the potential to target both of these behaviors through more contextually aware, tailored, and personalized support. We have developed a just-in-time adaptive intervention to promote sitting less and moving more in people with T2D. OBJECTIVE This paper presents the study protocol for a microrandomized trial to investigate whether motivational messages are effective in reducing time spent sitting in people with T2D and to determine what behavior change techniques are effective and in which context (eg, location, etc). METHODS We will use a 6-week microrandomized trial design. A total of 22 adults with T2D will be recruited. The intervention aims to reduce sitting time and increase time spent standing and walking and comprises a mobile app (iMove), a bespoke activity sensor called Sedentary Behavior Detector (SORD), a messaging system, and a secured database. Depending on the randomization sequence, participants will potentially receive motivational messages 5 times a day. RESULTS Recruitment was initiated in October 2022. As of now, 6 participants (2 female and 4 male) have consented and enrolled in the study. Their baseline measurements have been completed, and they have started using iMove. The mean age of 6 participants is 56.8 years, and they were diagnosed with T2D for 9.4 years on average. CONCLUSIONS This study will inform the optimization of digital behavior change interventions to support people with T2D Sit Less and Move More to increase daily physical activity. This study will generate new evidence about the immediate effectiveness of sedentary behavior interventions, their active ingredients, and associated factors. TRIAL REGISTRATION Australian New Zealand Clinical Trial Registry ACTRN12622000426785; https://anzctr.org.au/Trial/Registration/TrialReview.aspx?id=383664. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID) DERR1-10.2196/41502.
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Affiliation(s)
| | - David W Dunstan
- Baker-Deakin Department of Lifestyle and Diabetes, Deakin University, Melbourne, Australia
| | | | - Yuxin Zhang
- Institute for Physical Activity and Nutrition (IPAN), Deakin University, Geelong, Australia
| | | | - Ralph Maddison
- Institute for Physical Activity and Nutrition (IPAN), Deakin University, Geelong, Australia
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14
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Edwardson CL, Maylor BD, Biddle SJ, Clemes SA, Cox E, Davies MJ, Dunstan DW, Eborall H, Granat MH, Gray LJ, Hadjiconstantinou M, Healy GN, Jaicim NB, Lawton S, Mandalia P, Munir F, Richardson G, Walker S, Yates T, Clarke-Cornwell AM. A multicomponent intervention to reduce daily sitting time in office workers: the SMART Work & Life three-arm cluster RCT. Public Health Res (Southampt) 2023; 11:1-229. [PMID: 37786938 DOI: 10.3310/dnyc2141] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023] Open
Abstract
Background Office workers spend 70-85% of their time at work sitting. High levels of sitting have been linked to poor physiological and psychological health. Evidence shows the need for fully powered randomised controlled trials, with long-term follow-up, to test the effectiveness of interventions to reduce sitting time. Objective Our objective was to test the clinical effectiveness and cost-effectiveness of the SMART Work & Life intervention, delivered with and without a height-adjustable workstation, compared with usual practice at 12-month follow-up. Design A three-arm cluster randomised controlled trial. Setting Councils in England. Participants Office workers. Intervention SMART Work & Life is a multicomponent intervention that includes behaviour change strategies, delivered by workplace champions. Clusters were randomised to (1) the SMART Work & Life intervention, (2) the SMART Work & Life intervention with a height-adjustable workstation (i.e. SMART Work & Life plus desk) or (3) a control group (i.e. usual practice). Outcome measures were assessed at baseline and at 3 and 12 months. Main outcome measures The primary outcome was device-assessed daily sitting time compared with usual practice at 12 months. Secondary outcomes included sitting, standing, stepping time, physical activity, adiposity, blood pressure, biochemical measures, musculoskeletal issues, psychosocial variables, work-related health, diet and sleep. Cost-effectiveness and process evaluation data were collected. Results A total of 78 clusters (756 participants) were randomised [control, 26 clusters (n = 267); SMART Work & Life only, 27 clusters (n = 249); SMART Work & Life plus desk, 25 clusters (n = 240)]. At 12 months, significant differences between groups were found in daily sitting time, with participants in the SMART Work & Life-only and SMART Work & Life plus desk arms sitting 22.2 minutes per day (97.5% confidence interval -38.8 to -5.7 minutes/day; p = 0.003) and 63.7 minutes per day (97.5% confidence interval -80.0 to -47.4 minutes/day; p < 0.001), respectively, less than the control group. Participants in the SMART Work & Life plus desk arm sat 41.7 minutes per day (95% confidence interval -56.3 to -27.0 minutes/day; p < 0.001) less than participants in the SMART Work & Life-only arm. Sitting time was largely replaced by standing time, and changes in daily behaviour were driven by changes during work hours on workdays. Behaviour changes observed at 12 months were similar to 3 months. At 12 months, small improvements were seen for stress, well-being and vigour in both intervention groups, and for pain in the lower extremity and social norms in the SMART Work & Life plus desk group. Results from the process evaluation supported these findings, with participants reporting feeling more energised, alert, focused and productive. The process evaluation also showed that participants viewed the intervention positively; however, the extent of engagement varied across clusters. The average cost of SMART Work & Life only and SMART Work & Life plus desk was £80.59 and £228.31 per participant, respectively. Within trial, SMART Work & Life only had an incremental cost-effectiveness ratio of £12,091 per quality-adjusted life-year, with SMART Work & Life plus desk being dominated. Over a lifetime, SMART Work & Life only and SMART Work & Life plus desk had incremental cost-effectiveness ratios of £4985 and £13,378 per quality-adjusted life-year, respectively. Limitations The study was carried out in one sector, limiting generalisability. Conclusions The SMART Work & Life intervention, provided with and without a height-adjustable workstation, was successful in changing sitting time. Future work There is a need for longer-term follow-up, as well as follow-up within different organisations. Trial registration Current Controlled Trials ISRCTN11618007.
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Affiliation(s)
| | | | - Stuart Jh Biddle
- Centre for Health Research, University of Southern Queensland, Springfield Central, QLD, Australia
| | - Stacy A Clemes
- NIHR Leicester Biomedical Research Centre, Leicester, UK
| | - Edward Cox
- Centre for Health Economics, University of York, York, UK
| | - Melanie J Davies
- Diabetes Research Centre, University of Leicester, Leicester, UK
| | - David W Dunstan
- Baker Heart and Diabetes Institute, Melbourne, VIC, Australia
| | - Helen Eborall
- Department of Health Sciences, University of Leicester, Leicester, UK
| | | | - Laura J Gray
- Department of Health Sciences, University of Leicester, Leicester, UK
| | | | | | | | - Sarah Lawton
- School of Health & Society, University of Salford, Salford, UK
| | - Panna Mandalia
- Leicester Diabetes Centre, University Hospitals of Leicester, Leicester, UK
| | - Fehmidah Munir
- School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, UK
| | | | - Simon Walker
- Centre for Health Economics, University of York, York, UK
| | - Thomas Yates
- Diabetes Research Centre, University of Leicester, Leicester, UK
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Maylor BD, Edwardson CL, Clarke-Cornwell AM, Davies MJ, Dawkins NP, Dunstan DW, Khunti K, Yates T, Rowlands AV. Physical Activity Assessed by Wrist and Thigh Worn Accelerometry and Associations with Cardiometabolic Health. Sensors (Basel) 2023; 23:7353. [PMID: 37687813 PMCID: PMC10489920 DOI: 10.3390/s23177353] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Revised: 07/20/2023] [Accepted: 08/08/2023] [Indexed: 09/10/2023]
Abstract
Physical activity is increasingly being captured by accelerometers worn on different body locations. The aim of this study was to examine the associations between physical activity volume (average acceleration), intensity (intensity gradient) and cardiometabolic health when assessed by a thigh-worn and wrist-worn accelerometer. A sample of 659 office workers wore an Axivity AX3 on the non-dominant wrist and an activPAL3 micro on the right thigh concurrently for 24 h a day for 8 days. An average acceleration (proxy for physical activity volume) and intensity gradient (intensity distribution) were calculated from both devices using the open-source raw accelerometer processing software GGIR. Clustered cardiometabolic risk (CMR) was calculated using markers of cardiometabolic health, including waist circumference, triglycerides, HDL-cholesterol, mean arterial pressure and fasting glucose. Linear regression analysis assessed the associations between physical activity volume and intensity gradient with cardiometabolic health. Physical activity volume derived from the thigh-worn activPAL and the wrist-worn Axivity were beneficially associated with CMR and the majority of individual health markers, but associations only remained significant after adjusting for physical activity intensity in the thigh-worn activPAL. Physical activity intensity was associated with CMR score and individual health markers when derived from the wrist-worn Axivity, and these associations were independent of volume. Associations between cardiometabolic health and physical activity volume were similarly captured by the thigh-worn activPAL and the wrist-worn Axivity. However, only the wrist-worn Axivity captured aspects of the intensity distribution associated with cardiometabolic health. This may relate to the reduced range of accelerations detected by the thigh-worn activPAL.
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Affiliation(s)
- Benjamin D. Maylor
- Diabetes Research Centre, Population Health Sciences, College of Life Sciences, University of Leicester, Leicester LE1 7RH, UK; (B.D.M.); (M.J.D.); (N.P.D.); (K.K.); (T.Y.); (A.V.R.)
- Assessment of Movement Behaviours Group (AMBer), Leicester Lifestyle and Health Research Group, Diabetes Research Centre, University of Leicester, Leicester LE1 7RH, UK
- Leicester Diabetes Centre, University Hospitals of Leicester NHS Trust, Leicester LE5 4PW, UK
| | - Charlotte L. Edwardson
- Diabetes Research Centre, Population Health Sciences, College of Life Sciences, University of Leicester, Leicester LE1 7RH, UK; (B.D.M.); (M.J.D.); (N.P.D.); (K.K.); (T.Y.); (A.V.R.)
- Assessment of Movement Behaviours Group (AMBer), Leicester Lifestyle and Health Research Group, Diabetes Research Centre, University of Leicester, Leicester LE1 7RH, UK
- Leicester Diabetes Centre, University Hospitals of Leicester NHS Trust, Leicester LE5 4PW, UK
| | | | - Melanie J. Davies
- Diabetes Research Centre, Population Health Sciences, College of Life Sciences, University of Leicester, Leicester LE1 7RH, UK; (B.D.M.); (M.J.D.); (N.P.D.); (K.K.); (T.Y.); (A.V.R.)
- Leicester Diabetes Centre, University Hospitals of Leicester NHS Trust, Leicester LE5 4PW, UK
| | - Nathan P. Dawkins
- Diabetes Research Centre, Population Health Sciences, College of Life Sciences, University of Leicester, Leicester LE1 7RH, UK; (B.D.M.); (M.J.D.); (N.P.D.); (K.K.); (T.Y.); (A.V.R.)
- Leicester Diabetes Centre, University Hospitals of Leicester NHS Trust, Leicester LE5 4PW, UK
- School of Sport and Wellbeing, Leeds Trinity University, Leeds LS18 5HD, UK
| | - David W. Dunstan
- Physical Activity Laboratory, Baker Heart and Diabetes Institute, Melbourne, VIC 3004, Australia;
- Institute for Physical Activity and Nutrition, Faculty of Health, Deakin University, Geelong, VIC 3220, Australia
| | - Kamlesh Khunti
- Diabetes Research Centre, Population Health Sciences, College of Life Sciences, University of Leicester, Leicester LE1 7RH, UK; (B.D.M.); (M.J.D.); (N.P.D.); (K.K.); (T.Y.); (A.V.R.)
- Leicester Diabetes Centre, University Hospitals of Leicester NHS Trust, Leicester LE5 4PW, UK
- NIHR Applied Research Collaboration East Midlands, Diabetes Research Centre, University of Leicester, Leicester LE1 7RH, UK
| | - Tom Yates
- Diabetes Research Centre, Population Health Sciences, College of Life Sciences, University of Leicester, Leicester LE1 7RH, UK; (B.D.M.); (M.J.D.); (N.P.D.); (K.K.); (T.Y.); (A.V.R.)
- Leicester Diabetes Centre, University Hospitals of Leicester NHS Trust, Leicester LE5 4PW, UK
| | - Alex V. Rowlands
- Diabetes Research Centre, Population Health Sciences, College of Life Sciences, University of Leicester, Leicester LE1 7RH, UK; (B.D.M.); (M.J.D.); (N.P.D.); (K.K.); (T.Y.); (A.V.R.)
- Assessment of Movement Behaviours Group (AMBer), Leicester Lifestyle and Health Research Group, Diabetes Research Centre, University of Leicester, Leicester LE1 7RH, UK
- Leicester Diabetes Centre, University Hospitals of Leicester NHS Trust, Leicester LE5 4PW, UK
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16
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Nguyen P, Ananthapavan J, Gao L, Dunstan DW, Moodie M. Cost-effectiveness analysis of sedentary behaviour interventions in offices to reduce sitting time in Australian desk-based workers: A modelling study. PLoS One 2023; 18:e0287710. [PMID: 37384626 PMCID: PMC10309613 DOI: 10.1371/journal.pone.0287710] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Accepted: 06/09/2023] [Indexed: 07/01/2023] Open
Abstract
OBJECTIVES Sedentary behaviour (SB) is associated with increased incidence of chronic diseases such as type 2 diabetes (T2D), cardiovascular disease, cancers, and premature mortality. SB interventions in workplaces are effective in reducing sitting time. Previous economic evaluations have not specifically used changes in sitting time to estimate the long-term impact of SB on chronic disease-related health and cost outcomes. This research evaluated the cost-effectiveness of three hypothetical SB interventions: behavioural (BI), environmental (EI) and multi-component intervention (MI), implemented in the Australian context, using a newly developed epidemiological model that estimates the impact of SB as a risk factor on long-term population health and associated cost outcomes. METHOD Pathway analysis was used to identify the resource items associated with implementing each of the three interventions using a limited societal perspective (included costs: health sector, individuals and industry; excluded costs: productivity). The effectiveness of the modelled interventions in reducing daily sitting time (informed by published meta-analyses) was modelled for the Australian working population aged 20-65 years. A multi-cohort Markov model was developed to simulate the 2019 Australian population and estimate the incidence, prevalence and mortality of five diseases causally related to excessive sitting time, over the life course. Monte-Carlo simulations were used to calculate each intervention's mean incremental costs and benefits (quantified as health adjusted life years HALYs) compared to a do-nothing comparator. RESULTS When implemented at the national level, the interventions were estimated to reach 1,018 organisations with 1,619,239 employees. The estimated incremental cost of SB interventions was A$159M (BI), A$688M (EI) and A$438M (MI) over a year. Incremental health-adjusted life years (HALYs) gained by BI, EI and MI were 604, 919 and 349, respectively. The mean ICER for BI was A$251,863 per HALY gained, A$737,307 for EI and A$1,250,426 for MI. Only BI had any probability (2%) of being cost-effective at a willingness-to-pay threshold of A$50,000 per HALY gained from a societal perspective. CONCLUSION SB interventions are not cost-effective when a reduction in sitting time is the outcome measure of interest. The cost-effectiveness results are heavily driven by the cost of the sit-stand desks and the small HALYs gained from reducing sitting time. Future research should focus on capturing non-health-benefits of these interventions, such as productivity, work satisfaction, and other health benefits: metabolic, physical, and musculoskeletal outcomes. Importantly, the health benefits of simultaneously reducing sitting time and increasing standing time for such interventions should be captured with the joint effects of these risk factors appropriately considered.
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Affiliation(s)
- Phuong Nguyen
- Deakin Health Economics, School of Health and Social Development, Institute for Health Transformation, Deakin University, Geelong, Australia
- Global Obesity Centre, School of Health and Social Development, Institute for Health Transformation, Deakin University, Geelong, Australia
| | - Jaithri Ananthapavan
- Deakin Health Economics, School of Health and Social Development, Institute for Health Transformation, Deakin University, Geelong, Australia
- Global Obesity Centre, School of Health and Social Development, Institute for Health Transformation, Deakin University, Geelong, Australia
| | - Lan Gao
- Deakin Health Economics, School of Health and Social Development, Institute for Health Transformation, Deakin University, Geelong, Australia
- School of Biomedical Sciences and Pharmacy, The University of Newcastle, Callaghan, NSW, Australia
| | - David W. Dunstan
- Baker Heart and Diabetes Institute, Melbourne, Australia
- Mary MacKillop Institute for Health Research, Australian Catholic University, Melbourne, Victoria, Australia
- Institute for Physical Activity and Nutrition, Faculty of Health, Deakin University, Geelong, Vitoria, Australia
| | - Marj Moodie
- Deakin Health Economics, School of Health and Social Development, Institute for Health Transformation, Deakin University, Geelong, Australia
- Global Obesity Centre, School of Health and Social Development, Institute for Health Transformation, Deakin University, Geelong, Australia
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Islam SMS, Siopis G, Sood S, Uddin R, Tegegne T, Porter J, Dunstan DW, Colagiuri S, Zimmet P, George ES, Maddison R. The burden of type 2 diabetes in Australia during the period 1990-2019: Findings from the global burden of disease study. Diabetes Res Clin Pract 2023; 199:110631. [PMID: 36965709 DOI: 10.1016/j.diabres.2023.110631] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/26/2022] [Revised: 02/24/2023] [Accepted: 03/14/2023] [Indexed: 03/27/2023]
Abstract
AIMS To describe morbidity and mortality trends of type 2 diabetes in Australia, from 1990 to 2019, compared with similar sociodemographic index (SDI) countries. METHODS Australia-specific Global Burden of Diseases data were used to estimate age-standardised, age-specific, and sex-specific rates for prevalence, years lived with disability (YLDs), years of life lost (YLLs), disability-adjusted life years (DALYs), and deaths due to type 2 diabetes between 1990 and 2019. Australian data were compared with 14 similar SDI countries. RESULTS Type 2 diabetes increased in Australia between 1990 and 2019. The age-standardised prevalence increased from 1,985 [95% Confidence Interval (CI): 1,786.7-2195.3] per 100,000 population, to 3,429 [95% CI 3,053.3-3,853.7]. Cases tripled, from 379,532 [342,465-419,475] to 1,307,261 [1,165,522-1,461,180]. The age-standardised death rates doubled, from 2,098 [1,953-2,203] per 100,000, to 4,122 [3,617-4,512]. DALYs doubled, from 70,348 [59,187-83,500] to 169,763 [129,792-216,150], with increases seen in YLDs and YLLs. Men displayed higher rates. Compared to similar SDI countries, Australia ranked 4th in terms of burden for type 2 diabetes. CONCLUSIONS The burden of type 2 diabetes in Australia has increased considerably over three decades. There is an urgent need to prioritise resource allocation for prevention programs, screening initiatives to facilitate early detection, and effective and accessible management strategies for the large proportion of the population impacted by type 2 diabetes.
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Affiliation(s)
- Sheikh Mohammed Shariful Islam
- Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong, VIC, Australia.
| | - George Siopis
- Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong, VIC, Australia.
| | - Surbhi Sood
- Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong, VIC, Australia.
| | - Riaz Uddin
- Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong, VIC, Australia.
| | - Teketo Tegegne
- Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong, VIC, Australia.
| | - Judi Porter
- Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong, VIC, Australia.
| | - David W Dunstan
- Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong, VIC, Australia; Baker-Deakin Department Lifestyle and Diabetes, Baker Heart and Diabetes Institute, Melbourne, VIC, Australia.
| | | | - Paul Zimmet
- Department of Medicine, Monash University, Melbourne, VIC, Australia.
| | - Elena S George
- Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong, VIC, Australia.
| | - Ralph Maddison
- Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong, VIC, Australia.
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18
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Pinto AJ, Rezende D, Sieczkowska SM, Meireles K, Bonfiglioli K, Ribeiro ACDM, Bonfá E, Owen N, Dunstan DW, Roschel H, Gualano B. Increased Prolonged Sitting in Patients with Rheumatoid Arthritis during the COVID-19 Pandemic: A Within-Subjects, Accelerometer-Based Study. Int J Environ Res Public Health 2023; 20:3944. [PMID: 36900955 PMCID: PMC10001724 DOI: 10.3390/ijerph20053944] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Revised: 02/17/2023] [Accepted: 02/20/2023] [Indexed: 06/18/2023]
Abstract
BACKGROUND Social distancing measures designed to contain the COVID-19 pandemic can restrict physical activity, a particular concern for high-risk patient groups. We assessed rheumatoid arthritis patients' physical activity and sedentary behavior level, pain, fatigue, and health-related quality of life prior to and during the social distancing measures implemented in Sao Paulo, Brazil. METHODS Post-menopausal females diagnosed with rheumatoid arthritis were assessed before (from March 2018 to March 2020) and during (from 24 May to 7 July 2020) social distancing measures to contain COVID-19 pandemic, using a within-subjects, repeated-measure design. Physical activity and sedentary behavior were assessed using accelerometry (ActivPAL micro). Pain, fatigue, and health-related quality of life were assessed by questionnaires. RESULTS Mean age was 60.9 years and BMI was 29.5 Kg/m2. Disease activity ranged from remission to moderate activity. During social distancing, there were reductions in light-intensity activity (13.0% [-0.2 h/day, 95% CI: -0.4 to -0.04; p = 0.016]) and moderate-to-vigorous physical activity (38.8% [-4.5 min/day, 95% CI: -8.1 to -0.9; p = 0.015]), but not in standing time and sedentary time. However, time spent in prolonged bouts of sitting ≥30 min increased by 34% (1.0 h/day, 95% CI: 0.3 to 1.7; p = 0.006) and ≥60 min increased by 85% (1.0 h/day, 95% CI: 0.5 to 1.6). There were no changes in pain, fatigue, and health-related quality of life (all p > 0.050). CONCLUSIONS Imposed social distancing measures to contain the COVID-19 outbreak were associated with decreased physical activity and increased prolonged sedentary behavior, but did not change clinical symptoms sitting among patients with rheumatoid arthritis.
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Affiliation(s)
- Ana Jessica Pinto
- Applied Physiology and Nutrition Research Group, Laboratory of Assessment and Conditioning in Rheumatology, Hospital das Clínicas HCFMUSP, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Av. Dr. Arnaldo, 455, Sao Paulo 01246-903, Brazil
| | - Diego Rezende
- Applied Physiology and Nutrition Research Group, Laboratory of Assessment and Conditioning in Rheumatology, Hospital das Clínicas HCFMUSP, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Av. Dr. Arnaldo, 455, Sao Paulo 01246-903, Brazil
| | - Sofia Mendes Sieczkowska
- Applied Physiology and Nutrition Research Group, Laboratory of Assessment and Conditioning in Rheumatology, Hospital das Clínicas HCFMUSP, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Av. Dr. Arnaldo, 455, Sao Paulo 01246-903, Brazil
| | - Kamila Meireles
- Applied Physiology and Nutrition Research Group, Laboratory of Assessment and Conditioning in Rheumatology, Hospital das Clínicas HCFMUSP, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Av. Dr. Arnaldo, 455, Sao Paulo 01246-903, Brazil
| | - Karina Bonfiglioli
- Rheumatology Division, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Av. Dr. Arnaldo, 455, Sao Paulo 01246-903, Brazil
| | - Ana Cristina de Medeiros Ribeiro
- Rheumatology Division, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Av. Dr. Arnaldo, 455, Sao Paulo 01246-903, Brazil
| | - Eloisa Bonfá
- Rheumatology Division, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Av. Dr. Arnaldo, 455, Sao Paulo 01246-903, Brazil
| | - Neville Owen
- Baker Heart and Diabetes Institute, 99 Commercial Road, Melbourne, Victoria 3004, Australia
- Centre for Urban Transitions, Swinburne University of Technology, John St, Melbourne, Victoria 3122, Australia
| | - David W. Dunstan
- Baker Heart and Diabetes Institute, 99 Commercial Road, Melbourne, Victoria 3004, Australia
- Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, 1 Gheringhap Street, Geelong, Victoria 3220, Australia
| | - Hamilton Roschel
- Applied Physiology and Nutrition Research Group, Laboratory of Assessment and Conditioning in Rheumatology, Hospital das Clínicas HCFMUSP, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Av. Dr. Arnaldo, 455, Sao Paulo 01246-903, Brazil
| | - Bruno Gualano
- Applied Physiology and Nutrition Research Group, Laboratory of Assessment and Conditioning in Rheumatology, Hospital das Clínicas HCFMUSP, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Av. Dr. Arnaldo, 455, Sao Paulo 01246-903, Brazil
- Rheumatology Division, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Av. Dr. Arnaldo, 455, Sao Paulo 01246-903, Brazil
- Food Research Center, University of Sao Paulo, R. do Lago, 250, Sao Paulo 05508-080, Brazil
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Dillon HT, Foulkes S, Horne-Okano YA, Kliman D, Dunstan DW, Daly RM, Fraser SF, Avery S, Kingwell BA, La Gerche A, Howden EJ. Reduced cardiovascular reserve capacity in long-term allogeneic stem cell transplant survivors. Sci Rep 2023; 13:2112. [PMID: 36747066 PMCID: PMC9902607 DOI: 10.1038/s41598-023-28320-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Accepted: 01/17/2023] [Indexed: 02/08/2023] Open
Abstract
Premature cardiovascular mortality is increased in long-term allogeneic stem cell transplant (allo-SCT) survivors, but little information exists regarding subclinical cardiovascular dysfunction in this population. We compared peak oxygen uptake ([Formula: see text]O2peak), a prognostic cardiovascular marker, and its determinants between long-term allo-SCT survivors and non-cancer controls. Fourteen allo-SCT survivors (mean ± SD, 44 ± 15 years, 50% male, median time since allo-SCT: 6.5 years [range 2-20]) and 14 age- and sex-matched controls (46 ± 13 years, 50% male) underwent cardiopulmonary exercise testing to quantify [Formula: see text]O2peak. Resting echocardiography (left-ventricular ejection fraction and strain), exercise cardiac MRI (peak cardiac and stroke volume index [CIpeak, SVIpeak]), biochemistry (hemoglobin, troponin-I, B-natriuretic peptide), dual-energy x-ray absorptiometry (lean [LM] and fat [FM] mass, percent body fat [%BF]) and Fick-principal calculation (arteriovenous oxygen difference) were also performed. Survivors exhibited impaired [Formula: see text]O2peak as compared with controls (25.9 ± 5.1 vs. 33.7 ± 6.5 ml kg-1 min-1, p = 0.002), which coincided with reduced CIpeak (6.6 ± 0.8 vs. 8.6 ± 1.9 L min-1 m-2; p = 0.001) secondary to reduced SVIpeak (48 ± 4 vs. 61 ± 8 ml m-2; p < 0.001) rather than chronotropic impairment, and higher %BF (difference, 7.9%, p = 0.007) due to greater FM (5.8 kg; p = 0.069) and lower LM (4.3 kg, p = 0.25). All other measures were similar between groups. Despite comparable resting cardiac function and biomarker profiles, survivors exhibited reduced [Formula: see text]O2peak and exercise cardiac function and increased %BF relative to controls. These results highlight potential therapeutic avenues and the utility of exercise-based cardiovascular assessment in unmasking cardiovascular dysfunction in allo-SCT survivors.
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Affiliation(s)
- Hayley T Dillon
- Baker Heart and Diabetes Institute, Melbourne, Australia.,Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong, Australia
| | - Stephen Foulkes
- Baker Heart and Diabetes Institute, Melbourne, Australia.,Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong, Australia.,University of Melbourne, Melbourne, Australia
| | | | - David Kliman
- Malignant Haematology and Stem Cell Transplantation Service, Alfred Hospital, Melbourne, Australia
| | - David W Dunstan
- Baker Heart and Diabetes Institute, Melbourne, Australia.,Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong, Australia
| | - Robin M Daly
- Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong, Australia
| | - Steve F Fraser
- Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong, Australia
| | - Sharon Avery
- Malignant Haematology and Stem Cell Transplantation Service, Alfred Hospital, Melbourne, Australia
| | - Bronwyn A Kingwell
- Baker Heart and Diabetes Institute, Melbourne, Australia.,CSL Ltd, Melbourne, Australia
| | - Andre La Gerche
- Baker Heart and Diabetes Institute, Melbourne, Australia.,University of Melbourne, Melbourne, Australia.,Cardiology Department, St Vincent's Hospital Melbourne, Fitzroy, Australia
| | - Erin J Howden
- Baker Heart and Diabetes Institute, Melbourne, Australia. .,University of Melbourne, Melbourne, Australia.
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20
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Dzakpasu FQS, Koster A, Owen N, Galan BED, Carver A, Brakenridge CJ, Boonen A, Bosma H, Dagnelie PC, Eussen SJPM, Sethi P, Stehouwer CDA, Schaper NC, Dunstan DW. Device-measured sitting time and musculoskeletal pain in adults with normal glucose metabolism, prediabetes and type 2 diabetes-The Maastricht Study. PLoS One 2023; 18:e0285276. [PMID: 37141228 PMCID: PMC10159126 DOI: 10.1371/journal.pone.0285276] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2022] [Accepted: 04/18/2023] [Indexed: 05/05/2023] Open
Abstract
BACKGROUND Detrimental associations of sedentary behaviour (time spent sitting) with musculoskeletal pain (MSP) conditions have been observed. However, findings on those with, or at risk of, type 2 diabetes (T2D) have not been reported. We examined the linear and non-linear associations of device-measured daily sitting time with MSP outcomes according to glucose metabolism status (GMS). METHODS Cross-sectional data from 2827 participants aged 40-75 years in the Maastricht Study (1728 with normal glucose metabolism (NGM); 441 with prediabetes; 658 with T2D), for whom valid data were available on activPAL-derived daily sitting time, MSP [neck, shoulder, low back, and knee pain], and GMS. Associations were examined by logistic regression analyses, adjusted serially for relevant confounders, including moderate-to-vigorous intensity physical activity (MVPA) and body mass index (BMI). Restricted cubic splines were used to further examine non-linear relationships. RESULTS The fully adjusted model (including BMI, MVPA, and history of cardiovascular disease) showed daily sitting time to be significantly associated with knee pain in the overall sample (OR = 1.07, 95%CI: 1.01-1.12) and in those with T2D (OR = 1.11, 95%CI: 1.00-1.22); this was not statistically significant in those with prediabetes (OR = 1.04, 95%CI: 0.91-1.18) or NGM (OR = 1.05, 95%CI: 0.98-1.13). There were no statistically significant associations between daily sitting time and neck, shoulder, or low back pain in any of the models. Furthermore, the non-linear relationships were statistically non-significant. CONCLUSION Among middle-aged and older adults with T2D, daily sitting time was significantly associated with higher odds of knee pain, but not with neck, shoulder, or low back pain. No significant association was observed in those without T2D for neck, shoulder, low back, or knee pain. Future studies, preferably those utilising prospective designs, could examine additional attributes of daily sitting (e.g., sitting bouts and domain-specific sitting time) and the potential relationships of knee pain with mobility limitations.
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Affiliation(s)
- Francis Q S Dzakpasu
- Mary MacKillop Institute for Health Research, Australian Catholic University, Melbourne, Victoria, Australia
- Physical Activity Laboratory, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
| | - Annemarie Koster
- Department of Social Medicine, Maastricht University, Maastricht, the Netherlands
- CAPHRI Care and Public Health Research Institute, Maastricht University, Maastricht, the Netherlands
| | - Neville Owen
- Physical Activity Laboratory, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
- Centre for Urban Transitions, Swinburne University of Technology, Melbourne, Victoria, Australia
| | - Bastiaan E de Galan
- Department of Internal Medicine, Maastricht University Medical Centre, Maastricht, the Netherlands
- CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, the Netherlands
- Department of Internal Medicine, Radboud University Medical Centre, Nijmegen, the Netherlands
| | - Alison Carver
- National Centre for Healthy Ageing, Peninsula Clinical School, Monash University, Frankston, Victoria, Australia
| | - Christian J Brakenridge
- Physical Activity Laboratory, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
- Active Life Lab, South-Eastern Finland University of Applied Sciences, Mikkeli, Finland
| | - Annelies Boonen
- CAPHRI Care and Public Health Research Institute, Maastricht University, Maastricht, the Netherlands
- Division of Rheumatology, Department of Internal Medicine, Maastricht University Medical Centre+, Maastricht, the Netherlands
| | - Hans Bosma
- Department of Social Medicine, Maastricht University, Maastricht, the Netherlands
- CAPHRI Care and Public Health Research Institute, Maastricht University, Maastricht, the Netherlands
| | - Pieter C Dagnelie
- Department of Internal Medicine, Maastricht University Medical Centre, Maastricht, the Netherlands
- CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, the Netherlands
| | - Simone J P M Eussen
- CAPHRI Care and Public Health Research Institute, Maastricht University, Maastricht, the Netherlands
- CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, the Netherlands
- Department of Epidemiology, Maastricht University, Maastricht, the Netherlands
| | - Parneet Sethi
- Physical Activity Laboratory, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
| | - Coen D A Stehouwer
- Department of Internal Medicine, Maastricht University Medical Centre, Maastricht, the Netherlands
- CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, the Netherlands
| | - Nicolaas C Schaper
- CAPHRI Care and Public Health Research Institute, Maastricht University, Maastricht, the Netherlands
- Department of Internal Medicine, Maastricht University Medical Centre, Maastricht, the Netherlands
- CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, the Netherlands
| | - David W Dunstan
- Physical Activity Laboratory, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
- Institute for Physical Activity and Nutrition (IPAN), School of Exercise and Nutrition Sciences, Deakin University, Geelong, Victoria, Australia
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Sudholz B, Contardo Ayala AM, Timperio A, Dunstan DW, Conroy DE, Abbott G, Holland B, Arundell L, Salmon J. The impact of height-adjustable desks and classroom prompts on classroom sitting time, social, and motivational factors among adolescents. J Sport Health Sci 2023; 12:97-105. [PMID: 32445902 PMCID: PMC9923396 DOI: 10.1016/j.jshs.2020.05.002] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/07/2019] [Revised: 03/02/2020] [Accepted: 04/07/2020] [Indexed: 06/11/2023]
Abstract
PURPOSE This quasi-experimental study examined the impact of height-adjustable desks in combination with prompts to break up prolonged sitting time during class time and identified social and motivational factors associated with breaking up sitting time among adolescents. Teachers' perceptions of strategies were also examined. METHODS Over 17 weeks, 1 classroom in a government secondary school in Melbourne, Australia, was equipped with 27 height-adjustable desks and prompts (posters and desk stickers) to break up classroom sitting time. Teachers received professional development in the use of the desks and prompts. One group of adolescents (n = 55) had 2-5 lessons/week using the height-adjustable desks in an intervention classroom, and a comparison group matched by year level and subject (n = 50) was taught in traditional "seated" classrooms. Adolescents wore an activPAL monitor at baseline (T0), 4 weeks (T1), and 17 weeks (T2) and completed a survey at T0 and T2. Six teachers participated in interviews at T2. Effect sizes were calculated (d). RESULTS Linear mixed models found that, compared to the traditional "seated" classrooms, the adolescents in the intervention classroom had significantly lower sitting time (T1: -9.7 min/lesson, d = -0.96; T2: -6.7 min/lesson, d = -0.70) and time spent in sitting bouts >15 min (T2: -11.2 min/lesson, d = -0.62), and had significantly higher standing time (T1: 7.3 min/lesson, d = 0.84; T2: 5.8 min/lesson, d = 0.91), number of breaks from sitting (T1: 1.3 breaks/lesson, d = 0.49; T2: 1.8 breaks/lesson, d = 0.67), and stepping time (T1: 2.5 min/lesson, d = 0.66). Intervention classroom adolescents reported greater habit strength (d = 0.58), self-efficacy for breaking up sitting time (d = 0.75), and indicated that having a teacher/classmate remind them to stand as helpful (d = 0.50). CONCLUSION This intervention shows promise for targeting sitting behaviors in the classroom and indicates that incorporating social and motivational strategies may further enhance outcomes.
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Affiliation(s)
- Bronwyn Sudholz
- Pomegranate Community Mental Health, St John of God Social Outreach, Ballarat, VIC 3350, Australia
| | - Ana María Contardo Ayala
- Institute for Physical Activity and Nutrition (IPAN), School of Exercise and Nutrition Sciences, Deakin University, Geelong, VIC 3128, Australia.
| | - Anna Timperio
- Institute for Physical Activity and Nutrition (IPAN), School of Exercise and Nutrition Sciences, Deakin University, Geelong, VIC 3128, Australia
| | - David W Dunstan
- Institute for Physical Activity and Nutrition (IPAN), School of Exercise and Nutrition Sciences, Deakin University, Geelong, VIC 3128, Australia; Physical Activity Laboratory, Baker Heart and Diabetes Institute, Melbourne, VIC 3004, Australia; Mary MacKillop Institute for Health Research, Australian Catholic University, Melbourne, VIC 3000, Australia
| | - David E Conroy
- Department of Kinesiology, Pennsylvania State University, University Park, PA 16802, USA; Department of Preventive Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Gavin Abbott
- Institute for Physical Activity and Nutrition (IPAN), School of Exercise and Nutrition Sciences, Deakin University, Geelong, VIC 3128, Australia
| | - Bernie Holland
- The Australian Council for Health and Physical Education and Recreation, Abbotsford, VIC 3067, Australia
| | - Lauren Arundell
- Institute for Physical Activity and Nutrition (IPAN), School of Exercise and Nutrition Sciences, Deakin University, Geelong, VIC 3128, Australia
| | - Jo Salmon
- Institute for Physical Activity and Nutrition (IPAN), School of Exercise and Nutrition Sciences, Deakin University, Geelong, VIC 3128, Australia
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22
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Dillon HT, Foulkes S, Horne-Okano YA, Kliman D, Dunstan DW, Daly RM, Fraser SF, Avery S, Kingwell BA, La Gerche A, Howden EJ. Rapid cardiovascular aging following allogeneic hematopoietic cell transplantation for hematological malignancy. Front Cardiovasc Med 2022; 9:926064. [PMID: 36588564 PMCID: PMC9797839 DOI: 10.3389/fcvm.2022.926064] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2022] [Accepted: 11/18/2022] [Indexed: 12/23/2022] Open
Abstract
Introduction Allogeneic hematopoietic cell transplantation (allo-HCT) offers a potential cure for high-risk hematological malignancy; however, long-term survivors experience increased cardiovascular morbidity and mortality. It is unclear how allo-HCT impacts cardiovascular function in the short-term. Thus, this 3-month prospective study sought to evaluate the short-term cardiovascular impact of allo-HCT in hematological cancer patients, compared to an age-matched non-cancer control group. Methods Before and ~3-months following allo-HCT, 17 hematological cancer patients (45 ± 18 years) underwent cardiopulmonary exercise testing to quantify peak oxygen uptake (VO2peak)-a measure of integrative cardiovascular function. Then, to determine the degree to which changes in VO2peak are mediated by cardiac vs. non-cardiac factors, participants underwent exercise cardiac MRI (cardiac reserve), resting echocardiography (left-ventricular ejection fraction [LVEF], global longitudinal strain [GLS]), dual-energy x-ray absorptiometry (lean [LM] and fat mass [FM]), blood pressure (BP) assessment, hemoglobin sampling, and arteriovenous oxygen difference (a-vO2diff) estimation via the Fick equation. Twelve controls (43 ± 13 years) underwent identical testing at equivalent baseline and 3-month time intervals. Results Significant group-by-time interactions were observed for absolute VO2peak (p = 0.006), bodyweight-indexed VO2peak (p = 0.015), LM (p = 0.001) and cardiac reserve (p = 0.019), which were driven by 26, 24, 6, and 26% reductions in the allo-HCT group (all p ≤ 0.001), respectively, as no significant changes were observed in the age-matched control group. No significant group-by-time interactions were observed for LVEF, GLS, FM, hemoglobin, BP or a-vO2diff, though a-vO2diff declined 12% in allo-HCT (p = 0.028). Conclusion In summary, allo-HCT severely impairs VO2peak, reflecting central and peripheral dysfunction. These results indicate allo-HCT rapidly accelerates cardiovascular aging and reinforces the need for early preventive cardiovascular intervention in this high-risk group.
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Affiliation(s)
- Hayley T. Dillon
- Clinical Research Domain, Baker Heart and Diabetes Institute, Melbourne, VIC, Australia,Institute of Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong, VIC, Australia
| | - Stephen Foulkes
- Clinical Research Domain, Baker Heart and Diabetes Institute, Melbourne, VIC, Australia,Institute of Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong, VIC, Australia
| | - Yuki A. Horne-Okano
- Clinical Research Domain, Baker Heart and Diabetes Institute, Melbourne, VIC, Australia
| | - David Kliman
- Malignant Haematology and Stem Cell Transplantation Service, Alfred Hospital, Melbourne, VIC, Australia
| | - David W. Dunstan
- Clinical Research Domain, Baker Heart and Diabetes Institute, Melbourne, VIC, Australia,Institute of Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong, VIC, Australia
| | - Robin M. Daly
- Institute of Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong, VIC, Australia
| | - Steve F. Fraser
- Institute of Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong, VIC, Australia
| | - Sharon Avery
- Malignant Haematology and Stem Cell Transplantation Service, Alfred Hospital, Melbourne, VIC, Australia
| | - Bronwyn A. Kingwell
- Clinical Research Domain, Baker Heart and Diabetes Institute, Melbourne, VIC, Australia,CSL Ltd, Melbourne, VIC, Australia
| | - Andre La Gerche
- Clinical Research Domain, Baker Heart and Diabetes Institute, Melbourne, VIC, Australia
| | - Erin J. Howden
- Clinical Research Domain, Baker Heart and Diabetes Institute, Melbourne, VIC, Australia,*Correspondence: Erin J. Howden
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23
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Bellettiere J, Nakandala S, Tuz-Zahra F, Winkler EAH, Hibbing PR, Healy GN, Dunstan DW, Owen N, Greenwood-Hickman MA, Rosenberg DE, Zou J, Carlson JA, Di C, Dillon LW, Jankowska MM, LaCroix AZ, Ridgers ND, Zablocki R, Kumar A, Natarajan L. CHAP-Adult: A Reliable and Valid Algorithm to Classify Sitting and Measure Sitting Patterns Using Data From Hip-Worn Accelerometers in Adults Aged 35. J Meas Phys Behav 2022; 5:215-223. [PMID: 38260182 PMCID: PMC10803054 DOI: 10.1123/jmpb.2021-0062] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
Background Hip-worn accelerometers are commonly used, but data processed using the 100 counts per minute cut point do not accurately measure sitting patterns. We developed and validated a model to accurately classify sitting and sitting patterns using hip-worn accelerometer data from a wide age range of older adults. Methods Deep learning models were trained with 30-Hz triaxial hip-worn accelerometer data as inputs and activPAL sitting/nonsitting events as ground truth. Data from 981 adults aged 35-99 years from cohorts in two continents were used to train the model, which we call CHAP-Adult (Convolutional Neural Network Hip Accelerometer Posture-Adult). Validation was conducted among 419 randomly selected adults not included in model training. Results Mean errors (activPAL - CHAP-Adult) and 95% limits of agreement were: sedentary time -10.5 (-63.0, 42.0) min/day, breaks in sedentary time 1.9 (-9.2, 12.9) breaks/day, mean bout duration -0.6 (-4.0, 2.7) min, usual bout duration -1.4 (-8.3, 5.4) min, alpha .00 (-.04, .04), and time in ≥30-min bouts -15.1 (-84.3, 54.1) min/day. Respective mean (and absolute) percent errors were: -2.0% (4.0%), -4.7% (12.2%), 4.1% (11.6%), -4.4% (9.6%), 0.0% (1.4%), and 5.4% (9.6%). Pearson's correlations were: .96, .92, .86, .92, .78, and .96. Error was generally consistent across age, gender, and body mass index groups with the largest deviations observed for those with body mass index ≥30 kg/m2. Conclusions Overall, these strong validation results indicate CHAP-Adult represents a significant advancement in the ambulatory measurement of sitting and sitting patterns using hip-worn accelerometers. Pending external validation, it could be widely applied to data from around the world to extend understanding of the epidemiology and health consequences of sitting.
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Affiliation(s)
- John Bellettiere
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, CA, USA
| | - Supun Nakandala
- Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA, USA
| | - Fatima Tuz-Zahra
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, CA, USA
| | | | - Paul R Hibbing
- Center for Children's Healthy Lifestyles & Nutrition, Children's Mercy Hospital, Kansas City, MO, USA
| | - Genevieve N Healy
- School of Public Health, the University of Queensland, Brisbane, QLD, Australia
| | - David W Dunstan
- Baker Heart and Diabetes Institute, Melbourne, VIC, Australia
- Mary MacKillop Institute for Health Research, Australian Catholic University, Melbourne, VIC, Australia
| | - Neville Owen
- Baker Heart and Diabetes Institute, Melbourne, VIC, Australia
- Centre for Urban Transitions, Swinburne University of Technology, Melbourne, VIC, Australia
| | | | - Dori E Rosenberg
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
| | - Jingjing Zou
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, CA, USA
| | - Jordan A Carlson
- Center for Children's Healthy Lifestyles & Nutrition, Children's Mercy Hospital, Kansas City, MO, USA
- Department of Pediatrics, University of Missouri-Kansas City, Kansas City, MO, USA
| | - Chongzhi Di
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Lindsay W Dillon
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, CA, USA
| | - Marta M Jankowska
- Qualcomm Institute/Calit2, University of California San Diego, La Jolla, CA, USA
| | - Andrea Z LaCroix
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, CA, USA
| | - Nicola D Ridgers
- School of Exercise and Nutrition Sciences, Institute for Physical Activity and Nutrition, Deakin University, Geelong, VIC, Australia
| | - Rong Zablocki
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, CA, USA
| | - Arun Kumar
- Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA, USA
| | - Loki Natarajan
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, CA, USA
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24
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Cox E, Walker S, Edwardson CL, Biddle SJH, Clarke-Cornwell AM, Clemes SA, Davies MJ, Dunstan DW, Eborall H, Granat MH, Gray LJ, Healy GN, Maylor BD, Munir F, Yates T, Richardson G. The Cost-Effectiveness of the SMART Work & Life Intervention for Reducing Sitting Time. Int J Environ Res Public Health 2022; 19:14861. [PMID: 36429578 PMCID: PMC9690649 DOI: 10.3390/ijerph192214861] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Revised: 11/08/2022] [Accepted: 11/09/2022] [Indexed: 06/16/2023]
Abstract
Sedentary behaviours continue to increase and are associated with heightened risks of morbidity and mortality. We assessed the cost-effectiveness of SMART Work & Life (SWAL), an intervention designed to reduce sitting time inside and outside of work, both with (SWAL-desk) and without (SWAL-only) a height-adjustable workstation compared to usual practice (control) for UK office workers. Health outcomes were assessed in quality-adjusted life-years (QALY) and costs in pound sterling (2019-2020). Discounted costs and QALYs were estimated using regression methods with multiply imputed data from the SMART Work & Life trial. Absenteeism, productivity and wellbeing measures were also evaluated. The average cost of SWAL-desk was £228.31 and SWAL-only £80.59 per office worker. Within the trial, SWAL-only was more effective and costly compared to control (incremental cost-effectiveness ratio (ICER): £12,091 per QALY) while SWAL-desk was dominated (least effective and most costly). However, over a lifetime horizon, both SWAL-only and SWAL-desk were more effective and more costly than control. Comparing SWAL-only to control generated an ICER of £4985 per QALY. SWAL-desk was more effective and costly than SWAL-only, generating an ICER of £13,378 per QALY. Findings were sensitive to various worker, intervention, and extrapolation-related factors. Based on a lifetime horizon, SWAL interventions appear cost-effective for office-workers conditional on worker characteristics, intervention cost and longer-term maintenance in sitting time reductions.
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Affiliation(s)
- Edward Cox
- Centre for Health Economics, University of York, York YO10 5DD, UK
| | - Simon Walker
- Centre for Health Economics, University of York, York YO10 5DD, UK
| | - Charlotte L. Edwardson
- Diabetes Research Centre, University of Leicester, Leicester General Hospital, Leicester, LE5 4PW, UK
- NIHR Leicester Biomedical Research Centre, Leicester LE5 4PW, UK
| | - Stuart J. H. Biddle
- Centre for Health Research, University of Southern Queensland, Springfield, QLD 4300, Australia
| | | | - Stacy A. Clemes
- NIHR Leicester Biomedical Research Centre, Leicester LE5 4PW, UK
- School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough LE11 3TU, UK
| | - Melanie J. Davies
- Diabetes Research Centre, University of Leicester, Leicester General Hospital, Leicester, LE5 4PW, UK
- NIHR Leicester Biomedical Research Centre, Leicester LE5 4PW, UK
- Leicester Diabetes Centre, University Hospitals of Leicester, Leicester LE5 4PW, UK
| | - David W. Dunstan
- Baker Heart and Diabetes Institute, Melbourne, VIC 3004, Australia
- Baker-Deakin Department Lifestyle and Diabetes, Deakin University, Melbourne, VIC 3004, Australia
| | - Helen Eborall
- Department of Health Sciences, University of Leicester, Leicester LE1 7RH, UK
- Deanery of Molecular, Genetic and Population Health Sciences, The University of Edinburgh, Edinburgh EH16 4UX, UK
| | - Malcolm H. Granat
- School of Health & Society, University of Salford, Salford M6 6PU, UK
| | - Laura J. Gray
- Department of Health Sciences, University of Leicester, Leicester LE1 7RH, UK
| | - Genevieve N. Healy
- School of Human Movement and Nutrition Sciences, The University of Queensland, Brisbane, QLD 4067, Australia
| | - Benjamin D. Maylor
- Diabetes Research Centre, University of Leicester, Leicester General Hospital, Leicester, LE5 4PW, UK
| | - Fehmidah Munir
- School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough LE11 3TU, UK
| | - Thomas Yates
- Diabetes Research Centre, University of Leicester, Leicester General Hospital, Leicester, LE5 4PW, UK
- NIHR Leicester Biomedical Research Centre, Leicester LE5 4PW, UK
| | - Gerry Richardson
- Centre for Health Economics, University of York, York YO10 5DD, UK
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25
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Smallcombe JW, Biddle GJH, Slater T, Thackray AE, Dunstan DW, Barrett LA, Tolfrey K. Breaking Sitting Time with Physical Activity Increases Energy Expenditure but Does Not Alter Postprandial Metabolism in Girls. Med Sci Sports Exerc 2022; 54:1850-1860. [PMID: 35714076 DOI: 10.1249/mss.0000000000002979] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
PURPOSE Young people spend a substantial proportion of their time at school sedentary; therefore, this setting represents an important target for interventions aimed at displacing sedentary time with physical activity. This study aimed to examine the postprandial metabolic effects of breaking sedentary time by accumulating walking and repeated bouts of nonambulatory standing during simulated school days in inactive adolescent girls. METHODS Seventeen girls (mean ± SD = 12.8 ± 0.4 yr) completed two 3-d experimental conditions. On days 1 and 2 of the standing + walking (STD-WLK) experimental trial, participants interrupted sedentary time by completing 4 × 10 min bouts of self-paced walking and accumulated 18 × 5 min standing bouts during each simulated school day. On day 3 of STD-WLK, participants attended school as normal with no additional physical activity or standing prescribed. On all 3 d of the control condition (CON), participants attended school as normal with no physical activity intervention. On days 2 and 3 of both STD-WLK and CON, a baseline capillary blood sample was provided to determine fasting [TAG] and [glucose]. Participants then consumed a standardized breakfast (0 h) and lunch (4.7 h), and blood samples were provided postprandially at 2.7, 5.3, and 7.3 h for [TAG] and [glucose]. RESULTS Energy expenditure was 28% (95% confidence interval = 8% to 52%) higher during school hours on day 1 and day 2 during STD-WLK compared with CON (2171 vs 1693 kJ; effect size = 0.89, P = 0.008). However, no reduction of fasting or postprandial [TAG] or [glucose] was observed on day 2 or day 3 ( P ≥ 0.245). CONCLUSIONS Two consecutive days of breaking prolonged sitting with self-paced walking and intermittent standing had no meaningful effect on postprandial metabolism in adolescent girls.
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Affiliation(s)
| | - Gregory J H Biddle
- School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, UNITED KINGDOM
| | - Tommy Slater
- School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, UNITED KINGDOM
| | | | | | - Laura A Barrett
- School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, UNITED KINGDOM
| | - Keith Tolfrey
- School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, UNITED KINGDOM
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26
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Ringin E, Meyer D, Neill E, Phillipou A, Tan EJ, Toh WL, Sumner PJ, Owen N, Hallgren M, Dunstan DW, Rossell SL, Van Rheenen TE. Psychological-health correlates of physical activity and sedentary behaviour during the COVID pandemic. Ment Health Phys Act 2022; 23:100481. [PMID: 36406837 PMCID: PMC9664206 DOI: 10.1016/j.mhpa.2022.100481] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Revised: 10/04/2022] [Accepted: 10/05/2022] [Indexed: 11/17/2022]
Abstract
BACKGROUND While physical inactivity is associated with adverse psychological outcomes, less is known about the psychological outcomes associated with sedentary behaviour, and specifically, its mentally active and passive forms. The COVID-19 pandemic represents a unique opportunity to study associations between these variables in light of widespread stay-at-home mandates and restrictions on outdoor exercise/social activities. Using a cross-sectional dataset acquired during the COVID-19 pandemic in Australia, we examined whether physical activity and sedentary behaviour were associated with subjective quality of life (sQoL) and subjective cognitive dysfunction, and whether these associations were mediated by depressive symptoms. METHODS 658 participants (males = 169, females = 489) self-reported data on physical activity and sedentary behaviour in an online survey during May 2020-May 2021. Data on physical activity and sedentary behaviour (both mentally active and passive types) was compared according to whether it was collected during or out of a lockdown period. Regression models were used to test associations of physical activity and sedentary behaviour with sQoL and subjective cognitive dysfunction, and whether these associations were mediated by depression severity. RESULTS Physical activity was beneficially associated with sQoL, whereas sedentary behaviour (both total hours and the reduction of mentally active/increase in mentally passive behaviour) was detrimentally associated with sQoL. These associations were mediated by depression severity. Physical activity and sedentary behaviour were also indirectly associated with subjective cognitive dysfunction by virtue of their associations with depression severity. CONCLUSIONS There are important differences in the psychological correlates of mentally passive and active sedentary behaviours. Our findings suggest that health promotion strategies should focus on not only increasing physical activity but also reducing passive sedentary behaviours as a means of maintaining good psychological health.
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Affiliation(s)
- Elysha Ringin
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Melbourne, Australia
| | - Denny Meyer
- Centre for Mental Health, School of Health Sciences, Swinburne University, Melbourne, Australia
| | - Erica Neill
- Centre for Mental Health, School of Health Sciences, Swinburne University, Melbourne, Australia
- St Vincent's Mental Health, St Vincent's Hospital, Victoria, Australia
| | - Andrea Phillipou
- Centre for Mental Health, School of Health Sciences, Swinburne University, Melbourne, Australia
- Department of Mental Health, Austin Hospital, Melbourne, Victoria, Australia
| | - Eric J Tan
- Centre for Mental Health, School of Health Sciences, Swinburne University, Melbourne, Australia
- St Vincent's Mental Health, St Vincent's Hospital, Victoria, Australia
| | - Wei Lin Toh
- Centre for Mental Health, School of Health Sciences, Swinburne University, Melbourne, Australia
| | - Philip J Sumner
- Centre for Mental Health, School of Health Sciences, Swinburne University, Melbourne, Australia
| | - Neville Owen
- Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
- Centre for Urban Transitions, Swinburne University of Technology, Melbourne, Victoria, Australia
| | - Mats Hallgren
- Epidemiology of Psychiatric Conditions, Substance Use and Social Environment (EPiCSS), Department of Global Public Health Sciences, Karolinska Institutet, Stockholm, 171 77, Sweden
| | - David W Dunstan
- Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
- Institute for Physical Activity and Nutrition (IPAN), School of Exercise and Nutrition Sciences, Deakin University, Geelong, Australia
| | - Susan L Rossell
- Centre for Mental Health, School of Health Sciences, Swinburne University, Melbourne, Australia
- St Vincent's Mental Health, St Vincent's Hospital, Victoria, Australia
| | - Tamsyn E Van Rheenen
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne and Melbourne Health, Melbourne, Australia
- Centre for Mental Health, School of Health Sciences, Swinburne University, Melbourne, Australia
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27
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Freer CL, George ES, Tan SY, Abbott G, Dunstan DW, Daly RM. Effect of progressive resistance training with weight loss compared with weight loss alone on the fatty liver index in older adults with type 2 diabetes: secondary analysis of a 12-month randomized controlled trial. BMJ Open Diabetes Res Care 2022; 10:10/5/e002950. [PMID: 36220197 PMCID: PMC9557256 DOI: 10.1136/bmjdrc-2022-002950] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/19/2022] [Accepted: 08/31/2022] [Indexed: 11/05/2022] Open
Abstract
INTRODUCTION Non-alcoholic fatty liver disease (NAFLD) is highly prevalent (~75%) in people with type 2 diabetes (T2D). Since exercise and weight loss (WL) are recommended for the management of both NAFLD and T2D, this study examined whether progressive resistance training (PRT) plus WL could lead to greater improvements in the fatty liver index (FLI), an indicator of NAFLD, compared with WL alone in older adults with T2D. RESEARCH DESIGN AND METHODS This study represents a secondary analysis of a 12-month, two-arm randomised controlled trial including 36 overweight and obese adults (60-80 years) with T2D randomly allocated to supervised PRT plus WL (hypocaloric diet) (n=19) or WL plus sham (stretching) (n=17) for 6 months (phase I), followed by 6-months home-based training with ad libitum diet (phase II). FLI, which is an algorithm based on waist circumference, body mass index, triglycerides and gamma-glutamyl transferase, was assessed at baseline and every 3 months. Linear mixed models were used to analyse between-group differences over time, adjusting for baseline values. RESULTS At baseline, the mean±SD FLI was 76.6±18.5 and the likelihood of NAFLD (FLI >60) in all participants was 86%. Following phase I, both groups had similar statistically significant improvements in FLI (mean change (95% CI): PRT+WL, -12 (-20 to -4); WL, -9 (-15 to -4)), with no significant between-group difference. After the subsequent 6-month home-based phase, the improvements in FLI tended to persist in both groups (PRT+WL, -7 (-11 to -2); WL, -4 (-10 to 1)), with no between-group differences. CONCLUSIONS In older overweight adults with T2D, PRT did not enhance the benefits of WL on FLI, a predictor of NAFLD. TRIAL REGISTRATION NUMBER ACTRN12622000640707.
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Affiliation(s)
- Christine L Freer
- Institute for Physical Activity and Nutrition, Deakin University Faculty of Health, Geelong, Victoria, Australia
| | - Elena S George
- Institute for Physical Activity and Nutrition, Deakin University Faculty of Health, Geelong, Victoria, Australia
| | - Sze-Yen Tan
- Institute for Physical Activity and Nutrition, Deakin University Faculty of Health, Geelong, Victoria, Australia
| | - Gavin Abbott
- Institute for Physical Activity and Nutrition, Deakin University Faculty of Health, Geelong, Victoria, Australia
| | - David W Dunstan
- Institute for Physical Activity and Nutrition, Deakin University Faculty of Health, Geelong, Victoria, Australia
- Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
| | - Robin M Daly
- Institute for Physical Activity and Nutrition, Deakin University Faculty of Health, Geelong, Victoria, Australia
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28
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Koorts H, Timperio A, Abbott G, Arundell L, Ridgers ND, Cerin E, Brown H, Daly RM, Dunstan DW, Hume C, Chinapaw MJM, Moodie M, Hesketh KD, Salmon J. Is level of implementation linked with intervention outcomes? Process evaluation of the TransformUs intervention to increase children’s physical activity and reduce sedentary behaviour. Int J Behav Nutr Phys Act 2022; 19:122. [PMID: 36115963 PMCID: PMC9482275 DOI: 10.1186/s12966-022-01354-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2022] [Accepted: 08/23/2022] [Indexed: 01/16/2023] Open
Abstract
Background TransformUs was a four-arm school-based intervention to increase physical activity and reduce sedentary behaviour among primary school children. Pedagogical and environmental strategies targeted the classroom, school grounds and family setting. The aims of this study were to evaluate program fidelity, dose, appropriateness, satisfaction and sustainability, and associations between implementation level and outcomes among the three intervention arms. Methods At baseline, 18-months (mid-intervention) and 30-months (post-intervention), teachers, parents and children completed surveys, and children wore GT3X ActiGraph accelerometers for 8 days at each time point to determine physical activity and sedentary time. Implementation data were pooled across the three intervention groups and teachers were categorised by level of implementation: (i) ‘Low’ (< 33% delivered); (ii) ‘Moderate’ (33–67% delivered); and (iii) ‘High’ (> 67% delivered). Linear and logistic mixed models examined between group differences in implementation, and the association with children’s physical activity and sedentary time outcomes. Qualitative survey data were analysed thematically. Results Among intervention recipients, 52% (n = 85) of teachers, 29% (n = 331) of parents and 92% (n = 407) of children completed baseline evaluation surveys. At 18-months, teachers delivered on average 70% of the key messages, 65% set active/standing homework, 30% reported delivering > 1 standing lesson/day, and 56% delivered active breaks per day. The majority of teachers (96%) made activity/sports equipment available during recess and lunch, and also used this equipment in class (81%). Fidelity and dose of key messages and active homework reduced over time, whilst fidelity of standing lessons, active breaks and equipment use increased. TransformUs was deemed appropriate for the school setting and positively received. Implementation level and child behavioural outcomes were not associated. Integration of TransformUs into existing practices, children’s enjoyment, and teachers’ awareness of program benefits all facilitated delivery and sustainability. Conclusions This study demonstrated that intervention dose and fidelity increased over time, and that children’s enjoyment, senior school leadership and effective integration of interventions into school practices facilitated improved intervention delivery and sustainability. Teacher implementation level and child behavioural outcomes were unrelated, suggesting intervention efficacy was achieved irrespective of implementation variability. The potential translatability of TransformUs into practice contexts may therefore be increased. Findings have informed scale-up of TransformUs across Victoria, Australia. Trial registration International Standard Randomized Controlled Trial Number ISRCTN83725066; Australian New Zealand Clinical Trials Registry Number ACTRN12609000715279. Registered 19 August 2009. Available at: https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=308387&isReview=true Supplementary Information The online version contains supplementary material available at 10.1186/s12966-022-01354-5.
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Barnett A, Martino E, Knibbs LD, Shaw JE, Dunstan DW, Magliano DJ, Donaire-Gonzalez D, Cerin E. The neighbourhood environment and profiles of the metabolic syndrome. Environ Health 2022; 21:80. [PMID: 36057588 PMCID: PMC9440568 DOI: 10.1186/s12940-022-00894-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2021] [Accepted: 08/29/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND There is a dearth of studies on how neighbourhood environmental attributes relate to the metabolic syndrome (MetS) and profiles of MetS components. We examined the associations of interrelated aspects of the neighbourhood environment, including air pollution, with MetS status and profiles of MetS components. METHODS We used socio-demographic and MetS-related data from 3681 urban adults who participated in the 3rd wave of the Australian Diabetes, Obesity and Lifestyle Study. Neighbourhood environmental attributes included area socio-economic status (SES), population density, street intersection density, non-commercial land use mix, percentages of commercial land, parkland and blue space. Annual average concentrations of NO2 and PM2.5 were estimated using satellite-based land-use regression models. Latent class analysis (LCA) identified homogenous groups (latent classes) of participants based on MetS components data. Participants were then classified into five metabolic profiles according to their MetS-components latent class and MetS status. Generalised additive mixed models were used to estimate relationships of environmental attributes with MetS status and metabolic profiles. RESULTS LCA yielded three latent classes, one including only participants without MetS ("Lower probability of MetS components" profile). The other two classes/profiles, consisting of participants with and without MetS, were "Medium-to-high probability of high fasting blood glucose, waist circumference and blood pressure" and "Higher probability of MetS components". Area SES was the only significant predictor of MetS status: participants from high SES areas were less likely to have MetS. Area SES, percentage of commercial land and NO2 were associated with the odds of membership to healthier metabolic profiles without MetS, while annual average concentration of PM2.5 was associated with unhealthier metabolic profiles with MetS. CONCLUSIONS This study supports the utility of operationalising MetS as a combination of latent classes of MetS components and MetS status in studies of environmental correlates. Higher socio-economic advantage, good access to commercial services and low air pollution levels appear to independently contribute to different facets of metabolic health. Future research needs to consider conducting longitudinal studies using fine-grained environmental measures that more accurately characterise the neighbourhood environment in relation to behaviours or other mechanisms related to MetS and its components.
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Affiliation(s)
- Anthony Barnett
- Mary MacKillop Institute for Health Research, Australian Catholic University, 215 Spring St, Melbourne, VIC, Australia.
| | - Erika Martino
- Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC, 3010, Australia
| | - Luke D Knibbs
- School of Public Health, The University of Sydney, Sydney, NSW, 2006, Australia
| | - Jonathan E Shaw
- Department of Diabetes and Population Health, Baker Heart and Diabetes Institute, Melbourne, Australia
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - David W Dunstan
- Baker-Deakin Department of Lifestyle and Diabetes, Deakin University, Melbourne, Australia
| | - Dianna J Magliano
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
| | - David Donaire-Gonzalez
- Mary MacKillop Institute for Health Research, Australian Catholic University, 215 Spring St, Melbourne, VIC, Australia
| | - Ester Cerin
- Mary MacKillop Institute for Health Research, Australian Catholic University, 215 Spring St, Melbourne, VIC, Australia
- Department of Community Medicine, UiT The Artic University of Norway, Tromsø, Norway
- School of Public Health, The University of Hong Kong, 7 Sassoon Rd., Sandy Bay, Hong Kong, Hong Kong, SAR, China
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Contardo Ayala AM, Salmon J, Dunstan DW, Arundell L, Timperio A. Does light-intensity physical activity moderate the relationship between sitting time and adiposity markers in adolescents? J Sport Health Sci 2022; 11:613-619. [PMID: 32407803 PMCID: PMC9532587 DOI: 10.1016/j.jshs.2020.04.002] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/10/2019] [Revised: 11/02/2019] [Accepted: 01/16/2020] [Indexed: 06/11/2023]
Abstract
BACKGROUND While the relationship between sedentary time and adiposity markers may be independent of moderate-to-vigorous intensity physical activity (MVPA) among adolescents, little is known about the role of light-intensity physical activity (LIPA) in this relationship. The aim of this cross-sectional study was to examine whether device-measured LIPA and MVPA moderate the associations between objectively measured sitting time and adiposity markers (body mass index (BMI)) and waist circumference (WC)) among adolescents. METHODS This study included accelerometer and inclinometer data obtained from 219 adolescents (age = 14.9 ± 1.6 years, mean ± SD), collected during 2014 and 2015 in Melbourne, Australia. ActiGraph GT3X accelerometers were used to determine time spent in total-LIPA (101 counts/min to 3.99 metabolic equivalents (METs)) was dichotomized into low-LIPA (101-799 counts/min) and high LIPA (800 counts/min to 3.99 METs), and MVPA (≥ 4 METs). The average time spent sitting was obtained from activPAL inclinometers. Anthropometric measures were assessed by trained staff. Interactions between sitting and total-LIPA, low-LIPA, high-LIPA, and MVPA on BMI z-score (zBMI) and WC z-score (zWC), respectively, were examined using linear regression, adjusting for age and sex; and moderation by total-LIPA, low-LIPA, high-LIPA, and MVPA were examined by adding interaction terms. Significant interaction effects were probed by comparing associations at the mean and at 1 SD below and above the mean. RESULTS Total-LIPA significantly moderated the association between sitting time and zBMI, and low-LIPA significantly moderated the association between sitting time and zBMI and zWC. No other associations were found for total-LIPA, high-LIPA, or MVPA. Specifically, at high levels of total-LIPA (+1 SD), there is a negative association between sitting time and zBMI. In addition, at high levels of low-LIPA (+1 SD), there is a negative association between sitting time and zBMI and zWC. CONCLUSION Associations between sitting and adiposity depended on time spent in total-LIPA and low-LIPA, but not high-LIPA or MVPA. Results suggest that increasing time spent in LIPA may provide protection from the deleterious effects of sitting on adiposity markers among adolescents. Experimental evidence is needed to support these conclusions.
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Affiliation(s)
- Ana María Contardo Ayala
- Institute for Physical Activity and Nutrition (IPAN), School of Exercise and Nutrition Sciences, Deakin University, Geelong, VIA 3125, Australia.
| | - Jo Salmon
- Institute for Physical Activity and Nutrition (IPAN), School of Exercise and Nutrition Sciences, Deakin University, Geelong, VIA 3125, Australia
| | - David W Dunstan
- Institute for Physical Activity and Nutrition (IPAN), School of Exercise and Nutrition Sciences, Deakin University, Geelong, VIA 3125, Australia; Physical Activity Laboratory, Baker Heart and Diabetes Institute, Melbourne, VIA 3004, Australia; Mary MacKillop Institute for Health Research, Australian Catholic University, Melbourne, VIA 3000, Australia
| | - Lauren Arundell
- Institute for Physical Activity and Nutrition (IPAN), School of Exercise and Nutrition Sciences, Deakin University, Geelong, VIA 3125, Australia
| | - Anna Timperio
- Institute for Physical Activity and Nutrition (IPAN), School of Exercise and Nutrition Sciences, Deakin University, Geelong, VIA 3125, Australia
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Dillon HT, Saner NJ, Ilsley T, Kliman D, Spencer A, Avery S, Dunstan DW, Daly RM, Fraser SF, Owen N, Lynch BM, Kingwell BA, La Gerche A, Howden EJ. Preventing the adverse cardiovascular consequences of allogeneic stem cell transplantation with a multi-faceted exercise intervention: the ALLO-Active trial protocol. BMC Cancer 2022; 22:898. [PMID: 35978289 PMCID: PMC9383666 DOI: 10.1186/s12885-022-09793-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Accepted: 06/17/2022] [Indexed: 11/20/2022] Open
Abstract
BACKGROUND Allogeneic stem cell transplantation (allo-SCT) is a potentially lifesaving treatment for high-risk hematological malignancy, but survivors experience markedly elevated rates of cardiovascular disease and associated functional impairment. Mounting evidence suggests regular exercise, combined with a reduction in sedentary time through replacement with light exercise may be a useful therapeutic strategy for the prevention of cardiovascular comorbidities. However, this type of intervention has yet to be evaluated in patients undergoing allo-SCT. The ALLO-Active study will evaluate the efficacy of a ~ 4 month multi-faceted exercise intervention, commenced upon admission for allo-SCT, to preserve peak oxygen uptake (VO2peak) and peak cardiac output, compared with usual care. The study will also evaluate the effect of the intervention on functional independence, quality of life, and symptoms of fatigue. METHODS Sixty adults with hematological malignancy scheduled for allo-SCT will be randomly assigned to usual care (n = 30) or the exercise and sedentary behaviour intervention (n = 30). Participants assigned to the intervention will complete a thrice weekly aerobic and progressive resistance training program and concomitantly aim to reduce daily sedentary time by 30 min with short, frequent, light-intensity exercise bouts. Participants will undergo testing prior to, immediately after inpatient discharge, and 12 weeks after discharge. To address aim 1, VO2peak and peak cardiac output (multiple primary outcomes, p < 0.025) will be assessed via cardiopulmonary exercise testing and exercise cardiac magnetic resonance imaging, respectively. Secondary outcomes include functional independence (defined as VO2peak ≥ 18.mL.kg-1.min-1), quality of life, and fatigue (assessed via validated questionnaire). Exploratory outcomes will include indices of resting cardiac, vascular, and skeletal muscle structure and function, cardiovascular biomarkers, anxiety and depression, transplant outcomes (e.g., engraftment, graft-versus-host disease), and habitual physical activity, sedentary time, and sleep. DISCUSSION Multi-faceted exercise programs are a promising approach for ameliorating the cardiovascular consequences of allo-SCT. If this intervention proves to be effective, it will contribute to the development of evidence-based exercise guidelines for patients undergoing allo-SCT and assist with optimising the balance between acute cancer management and long-term health. TRIAL REGISTRATION Australian New Zealand Clinical Trials Registry (ANZCTR), ID: 12619000741189 . Registered 17 May 2019.
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Affiliation(s)
- Hayley T Dillon
- Baker Heart and Diabetes Institute, Melbourne, Australia.
- Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong, Australia.
| | | | - Tegan Ilsley
- Baker Heart and Diabetes Institute, Melbourne, Australia
- Central Clinical School, Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, Australia
| | - David Kliman
- Malignant Haematology and Stem Cell Transplantation Service, Alfred Hospital, Melbourne, Australia
| | - Andrew Spencer
- Malignant Haematology and Stem Cell Transplantation Service, Alfred Hospital, Melbourne, Australia
| | - Sharon Avery
- Malignant Haematology and Stem Cell Transplantation Service, Alfred Hospital, Melbourne, Australia
| | - David W Dunstan
- Baker Heart and Diabetes Institute, Melbourne, Australia
- Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong, Australia
- Mary MacKillop Institute for Health Research, Australian Catholic University, Melbourne, Australia
| | - Robin M Daly
- Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong, Australia
| | - Steve F Fraser
- Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong, Australia
| | - Neville Owen
- Baker Heart and Diabetes Institute, Melbourne, Australia
- Centre for Urban Transitions, Swinburne University of Technology, Melbourne, Australia
| | - Brigid M Lynch
- Baker Heart and Diabetes Institute, Melbourne, Australia
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Parkville, Australia
| | - Bronwyn A Kingwell
- Baker Heart and Diabetes Institute, Melbourne, Australia
- CSL Ltd, Melbourne, Australia
| | | | - Erin J Howden
- Baker Heart and Diabetes Institute, Melbourne, Australia
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Edwardson CL, Biddle SJH, Clemes SA, Davies MJ, Dunstan DW, Eborall H, Granat MH, Gray LJ, Healy GN, Jaicim NB, Lawton S, Maylor BD, Munir F, Richardson G, Yates T, Clarke-Cornwell AM. Effectiveness of an intervention for reducing sitting time and improving health in office workers: three arm cluster randomised controlled trial. BMJ 2022; 378:e069288. [PMID: 35977732 PMCID: PMC9382450 DOI: 10.1136/bmj-2021-069288] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
OBJECTIVES To evaluate the effectiveness of an intervention, with and without a height adjustable desk, on daily sitting time, and to investigate the relative effectiveness of the two interventions, and the effectiveness of both interventions on physical behaviours and physical, biochemical, psychological, and work related health and performance outcomes. DESIGN Cluster three arm randomised controlled trial with follow-up at three and 12 months. SETTING Local government councils in Leicester, Liverpool, and Greater Manchester, UK. PARTICIPANTS 78 clusters including 756 desk based employees in defined offices, departments, or teams from two councils in Leicester, three in Greater Manchester, and one in Liverpool. INTERVENTIONS Clusters were randomised to one of three conditions: the SMART Work and Life (SWAL) intervention, the SWAL intervention with a height adjustable desk (SWAL plus desk), or control (usual practice). MAIN OUTCOMES MEASURES The primary outcome measure was daily sitting time, assessed by accelerometry, at 12 month follow-up. Secondary outcomes were accelerometer assessed sitting, prolonged sitting, standing and stepping time, and physical activity calculated over any valid day, work hours, workdays, and non-workdays, self-reported lifestyle behaviours, musculoskeletal problems, cardiometabolic health markers, work related health and performance, fatigue, and psychological measures. RESULTS Mean age of participants was 44.7 years, 72.4% (n=547) were women, and 74.9% (n=566) were white. Daily sitting time at 12 months was significantly lower in the intervention groups (SWAL -22.2 min/day, 95% confidence interval -38.8 to -5.7 min/day, P=0.003; SWAL plus desk -63.7 min/day, -80.1 to -47.4 min/day, P<0.001) compared with the control group. The SWAL plus desk intervention was found to be more effective than SWAL at changing sitting time (-41.7 min/day, -56.3 to -27.0 min/day, P<0.001). Favourable differences in sitting and prolonged sitting time at three and 12 month follow-ups for both intervention groups and for standing time for the SWAL plus desk group were observed during work hours and on workdays. Both intervention groups were associated with small improvements in stress, wellbeing, and vigour, and the SWAL plus desk group was associated with improvements in pain in the lower extremity, social norms for sitting and standing at work, and support. CONCLUSIONS Both SWAL and SWAL plus desk were associated with a reduction in sitting time, although the addition of a height adjustable desk was found to be threefold more effective. TRIAL REGISTRATION ISRCTN Registry ISRCTN11618007.
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Affiliation(s)
- Charlotte L Edwardson
- Diabetes Research Centre, University of Leicester, Leicester, LE5 4PW, UK
- NIHR Leicester Biomedical Research Centre, Leicester, UK
| | - Stuart J H Biddle
- Centre for Health Research, University of Southern Queensland, Springfield Central, QLD, Australia
| | - Stacy A Clemes
- NIHR Leicester Biomedical Research Centre, Leicester, UK
- School of Sport, Exercise and Health Sciences, Loughborough University, Leicester, UK
| | - Melanie J Davies
- Diabetes Research Centre, University of Leicester, Leicester, LE5 4PW, UK
- NIHR Leicester Biomedical Research Centre, Leicester, UK
- Leicester Diabetes Centre, University Hospitals of Leicester, Leicester, UK
| | - David W Dunstan
- Baker Heart and Diabetes Institute, Melbourne, VIC, Australia
- Mary MacKillop Institute for Health Research, The Australian Catholic University, Melbourne, VIC, Australia
| | - Helen Eborall
- Department of Health Sciences, University of Leicester, Leicester, UK
- Deanery of Molecular, Genetic and Population Health Sciences, The University of Edinburgh, UK
| | - Malcolm H Granat
- School of Health and Society, University of Salford, Salford, Greater Manchester, UK
| | - Laura J Gray
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - Genevieve N Healy
- School of Human Movement and Nutrition Sciences, The University of Queensland, Brisbane, QLD, Australia
| | | | - Sarah Lawton
- School of Health and Society, University of Salford, Salford, Greater Manchester, UK
| | - Benjamin D Maylor
- Diabetes Research Centre, University of Leicester, Leicester, LE5 4PW, UK
| | - Fehmidah Munir
- School of Sport, Exercise and Health Sciences, Loughborough University, Leicester, UK
| | | | - Thomas Yates
- Diabetes Research Centre, University of Leicester, Leicester, LE5 4PW, UK
- NIHR Leicester Biomedical Research Centre, Leicester, UK
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Verswijveren SJJM, Ridgers ND, Martín-Fernández JA, Chastin S, Cerin E, Chinapaw MJM, Arundell L, Dunstan DW, Hume C, Brown H, Della Gatta J, Salmon J. Intervention effects on children's movement behaviour accumulation as a result of the Transform-Us! school- and home-based cluster randomised controlled trial. Int J Behav Nutr Phys Act 2022; 19:76. [PMID: 35799258 PMCID: PMC9261108 DOI: 10.1186/s12966-022-01314-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Accepted: 06/07/2022] [Indexed: 11/12/2022] Open
Abstract
Background It is unknown if and how children’s movement behaviour accumulation patterns change as a result of physical activity and/or sedentary behaviour interventions. It is important to establish the effectiveness of interventions targeting changes in such accumulation patterns. This study aimed to investigate the effect of the Transform-Us! school- and home-based intervention program on children’s movement behaviour accumulation patterns, focusing on sporadic accumulation versus time in bouts. Methods Baseline and post-intervention (18 months) accelerometer data from the Transform-Us! 2 × 2 factorial design cluster randomised controlled trial was used (Melbourne, 2010–2012; analytical sample n = 267; aged 8–9 years). Linear mixed models were fitted to examine effects of three different interventions (targeting increases in physical activity [PA-I], reductions in sedentary time [SB-I], or both [PA + SB-I]) compared to a usual practice (control) group on post-intervention movement behaviour accumulation compositions with eight components, including sporadic time and bouts of sedentary time, and light-, moderate- and vigorous-intensity physical activity. Results Intervention effects on distribution of time in the post-intervention waking movement behaviour accumulation composition (adjusted for baseline composition) were small and not significant. However, visual inspection of the change in compositions over time revealed that only groups with a sedentary behaviour intervention component (SB-I and PA + SB-I) reduced time in sedentary bouts, compared to the overall sample compositional mean. In addition, the SB-I group was the only group with an increase in vigorous-intensity physical activity. The combined intervention group (PA + SB-I) was characterized by the largest proportional increase in MPA bouts. The usual practice group was characterized by the largest proportional increases in both sporadic and bouts of sedentary time. Conclusions This study showed some early evidence to suggest that the “break up your sitting” message may result in greater impact than the “move more” message. Future research, including larger sample sizes, should investigate if this type of messaging is indeed more effective in changing movement behaviours and ultimately child health. Trial registration International Standard Randomized Controlled Trial Number ISRCTN83725066; Australian New Zealand Clinical Trials Registry Number ACTRN12609000715279. Supplementary Information The online version contains supplementary material available at 10.1186/s12966-022-01314-z.
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Affiliation(s)
| | - Nicola D Ridgers
- Alliance for Research in Exercise, Nutrition and Activity (ARENA), University of South Australia, Adelaide, South Australia, Australia
| | - Josep A Martín-Fernández
- Department of Computer Science, Applied Mathematics and Statistics, University of Girona, Girona, Spain
| | - Sebastien Chastin
- School of Health and Life Sciences, Glasgow Caledonian University, Glasgow, UK
| | - Ester Cerin
- Mary McKillop Institute for Health Research, Australian Catholic University, Melbourne, Victoria, Australia
| | - Mai J M Chinapaw
- Department of Public and Occupational Health, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Public Health Research Institute, Amsterdam, the Netherlands
| | - Lauren Arundell
- Institute for Physical Activity and Nutrition (IPAN), Deakin University, Geelong, Australia
| | - David W Dunstan
- Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
| | - Clare Hume
- School of Public Health, University of Adelaide, Adelaide, South Australia, Australia
| | - Helen Brown
- Institute for Physical Activity and Nutrition (IPAN), Deakin University, Geelong, Australia
| | - Jacqueline Della Gatta
- Institute for Physical Activity and Nutrition (IPAN), Deakin University, Geelong, Australia
| | - Jo Salmon
- Institute for Physical Activity and Nutrition (IPAN), Deakin University, Geelong, Australia
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Shibata A, Ishii K, Koohsari MJ, Sugiyama T, Dunstan DW, Owen N, Oka K. Linear and non-linear associations of device-measured sedentary time with older adults' skeletal muscle mass. Exp Gerontol 2022; 166:111870. [PMID: 35716867 DOI: 10.1016/j.exger.2022.111870] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Revised: 05/24/2022] [Accepted: 06/10/2022] [Indexed: 11/17/2022]
Abstract
BACKGROUND Time spent sitting is associated adversely with health outcomes in older adults. Nevertheless, it is not clear how sedentary time may be related to appendicular skeletal muscle mass (ASM) - a key attribute of sarcopenia. This cross-sectional study examined associations of total sedentary time with ASM among community-dwelling older Japanese males and females. METHODS Participants (n = 281, 74.3 ± 5.2 yr) wore a tri-axial accelerometer for seven days. Body mass index-adjusted ASM (kg/BMI) was derived from bioimpedance measures. Multivariate linear and quadratic regression models examined the associations of ASM with total sedentary time, stratified by sex. Restricted cubic spline models were fitted to estimate non-linear associations. Isotemporal substitution (IS) models were used to estimate the impacts of replacing 30-minute of sedentary time with light physical activity (LPA) and moderate-to-vigorous physical activity (MVPA). RESULTS After adjustment, total sedentary time had a significant linear and negative association with ASM among females (β = -0.014; p = 0.023). For males, total sedentary time had a significant quadratic association (p = 0.020). Spline models indicated a reverse U-shaped association (p < 0.001) with total sedentary time over 9.3 h/day being associated with lower ASM. The IS models indicated that replacing 30 min/day of sedentary time with LPA would be positively and significantly associated with older females' ASM (β = 0.007, p = 0.022). CONCLUSIONS In older Japanese adults, higher volumes of time spent sedentary were associated with lower ASM. For males, only very high volumes of sedentary time appeared to be detrimental. These adverse relationships may in part be offset by more time spent in either LPA or MVPA.
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Affiliation(s)
- Ai Shibata
- Faculty Health and Sport Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8575, Japan; Faculty of Sport Sciences, Waseda University, 2-579-15 Mikajima, Tokorozawa, Saitama 359-1192, Japan.
| | - Kaori Ishii
- Faculty of Sport Sciences, Waseda University, 2-579-15 Mikajima, Tokorozawa, Saitama 359-1192, Japan.
| | - Mohammad Javad Koohsari
- Faculty of Sport Sciences, Waseda University, 2-579-15 Mikajima, Tokorozawa, Saitama 359-1192, Japan.
| | - Takemi Sugiyama
- Centre for Urban Transitions, Swinburne University of Technology, John Street, Hawthorn, Victoria 3122, Australia; Baker Heart & Diabetes Institute, 75 Commercial Road, Melbourne, Victoria 3004, Australia.
| | - David W Dunstan
- Baker Heart & Diabetes Institute, 75 Commercial Road, Melbourne, Victoria 3004, Australia; Mary MacKillop Institute for Health Research, Australian Catholic University, 215 Spring Street, Melbourne, Victoria 3000, Australia.
| | - Neville Owen
- Centre for Urban Transitions, Swinburne University of Technology, John Street, Hawthorn, Victoria 3122, Australia; Baker Heart & Diabetes Institute, 75 Commercial Road, Melbourne, Victoria 3004, Australia.
| | - Koichiro Oka
- Faculty of Sport Sciences, Waseda University, 2-579-15 Mikajima, Tokorozawa, Saitama 359-1192, Japan.
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Dogra S, Copeland JL, Altenburg TM, Heyland DK, Owen N, Dunstan DW. Start with reducing sedentary behavior: A stepwise approach to physical activity counseling in clinical practice. Patient Educ Couns 2022; 105:1353-1361. [PMID: 34556383 DOI: 10.1016/j.pec.2021.09.019] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/05/2021] [Revised: 09/07/2021] [Accepted: 09/08/2021] [Indexed: 06/13/2023]
Abstract
UNLABELLED Recently, sedentary behavior recommendations have been included in the public health guidelines of multiple countries, pointing to new opportunities for prevention of chronic disease as well as a potential strategy for initiating long-term behavior change. OBJECTIVE To propose an evidence-informed approach to physical activity counseling that starts with a focus on reducing sedentary time. METHODS We put forward a case for addressing changes in sedentary behavior in clinical practice using a narrative review. We also propose a new approach for the assessment and counselling of patients with respect to movement behaviors. RESULTS There is evidence to support a stepwise approach to physical activity counseling that starts with targeting sedentary behavior, particularly in those who are highly sedentary, or those who have chronic disease, or physical impairments. CONCLUSIONS Our approach encourages clinicians to consider sedentary behavior counseling as a critical first step to physical activity counseling. For many patients, this initial step of reducing sedentary behavior could build a pathway to an active lifestyle. PRACTICAL IMPLICATIONS A shift from long periods of sedentary time to daily routines incorporating more light intensity physical activity could result in meaningful health improvements. Importantly, this approach may be more feasible for highly inactive patients.
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Affiliation(s)
- Shilpa Dogra
- Faculty of Health Sciences (Kinesiology), University of Ontario Institute of Technology, Canada.
| | - Jennifer L Copeland
- Department of Kinesiology, University of Lethbridge, Lethbridge, Alberta, Canada
| | - Teatske M Altenburg
- Department of Public and Occupational Health, UMC Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Daren K Heyland
- Department of Critical Care Medicine and Public Health, Queen's University, Kingston, Canada
| | - Neville Owen
- Baker Heart and Diabetes Institute, Melbourne, Australia; Centre for Urban Transitions, Swinburne University of Technology, Melbourne, Australia
| | - David W Dunstan
- Baker Heart and Diabetes Institute, Melbourne, Australia; Mary MacKillop Institute for Health Research, Australian Catholic University, Melbourne, Australia
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Brakenridge CJ, Gardiner PA, Grigg RV, Winkler EAH, Fjeldsoe BS, Schaumberg MA, Owen N, Eakin EG, Biddle SJH, Moodie M, Daly RM, Green DJ, Cohen N, Gray L, Comans T, Buman MP, Goode AD, Nguyen P, Gao L, Healy GN, Dunstan DW. Sitting less and moving more for improved metabolic and brain health in type 2 diabetes: 'OPTIMISE your health' trial protocol. BMC Public Health 2022; 22:929. [PMID: 35538430 PMCID: PMC9086419 DOI: 10.1186/s12889-022-13123-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Accepted: 03/16/2022] [Indexed: 01/21/2023] Open
Abstract
Background Clinical 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. Methods This 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. Discussion The 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 registration ANZCTRN12618001159246. Supplementary Information The online version contains supplementary material available at 10.1186/s12889-022-13123-x.
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Affiliation(s)
- Christian J Brakenridge
- Baker Heart & Diabetes Institute, 99 Commercial Rd, Melbourne, VIC, 3004, Australia. .,Australian Catholic University, Mary Mackillop Institute of Health Research, Melbourne, Australia.
| | - Paul A Gardiner
- University of Southern Queensland, School of Health and Medical Sciences, Ipswich, Australia.,University of Southern Queensland, Centre for Health Research, Springfield, Australia.,The University of Queensland, Centre for Health Services Research, Brisbane, Australia
| | - Ruth V Grigg
- Baker Heart & Diabetes Institute, 99 Commercial Rd, Melbourne, VIC, 3004, Australia
| | - Elisabeth A H Winkler
- The University of Queensland, School of Human Movement and Nutrition Sciences, Brisbane, Australia
| | - Brianna S Fjeldsoe
- The University of Queensland, School of Public Health, Brisbane, Australia
| | - Mia A Schaumberg
- The University of Queensland, School of Human Movement and Nutrition Sciences, Brisbane, Australia.,University of Sunshine Coast, School of Health and Behavioural Sciences, Sunshine Coast, Australia.,Sunshine Coast Health Institute, Sunshine Coast Hospital and Health Service, Birtinya, Australia
| | - Neville Owen
- Baker Heart & Diabetes Institute, 99 Commercial Rd, Melbourne, VIC, 3004, Australia.,Swinburne University, School of Health Sciences, Melbourne, Australia
| | - Elizabeth G Eakin
- The University of Queensland, School of Public Health, Brisbane, Australia
| | - Stuart J H Biddle
- University of Southern Queensland, Centre for Health Research, Springfield, Australia
| | - Marjory Moodie
- Deakin University, School of Health and Social Development, Melbourne, Australia
| | - Robin M Daly
- Deakin University, Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Melbourne, Australia
| | - Daniel J Green
- University of Western Australia, School of Sport Science, Exercise & Health, Perth, Australia
| | - Neale Cohen
- Baker Heart & Diabetes Institute, 99 Commercial Rd, Melbourne, VIC, 3004, Australia
| | - Len Gray
- The University of Queensland, Centre for Health Services Research, Brisbane, Australia
| | - Tracy Comans
- The University of Queensland, Centre for Health Services Research, Brisbane, Australia
| | - Matthew P Buman
- Arizona State University, College of Health Solutions, Tempe, USA
| | - Ana D Goode
- The University of Queensland, School of Human Movement and Nutrition Sciences, Brisbane, Australia
| | - Phuong Nguyen
- Deakin University, School of Health and Social Development, Melbourne, Australia
| | - Lan Gao
- Deakin University, School of Health and Social Development, Melbourne, Australia
| | - Genevieve N Healy
- Baker Heart & Diabetes Institute, 99 Commercial Rd, Melbourne, VIC, 3004, Australia.,The University of Queensland, School of Human Movement and Nutrition Sciences, Brisbane, Australia
| | - David W Dunstan
- Baker Heart & Diabetes Institute, 99 Commercial Rd, Melbourne, VIC, 3004, Australia.,Deakin University, Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Melbourne, Australia.,School of Public Health & Preventive Medicine, Monash University, Melbourne, Australia
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Mundell NL, Sethi P, Anstey KJ, Macpherson H, Dunstan DW, Fraser SF, Daly RM. The influence of adiposity on the interactions between strength, physical function and cognition among older adults in the Australian Diabetes, Obesity and Lifestyle (AusDiab) study. BMC Geriatr 2022; 22:357. [PMID: 35459099 PMCID: PMC9034532 DOI: 10.1186/s12877-022-03033-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Accepted: 04/06/2022] [Indexed: 11/10/2022] Open
Abstract
Background Being overweight or obese may be associated with lower physical and cognitive function, but in late-adulthood (≥ 65 years) evidence is mixed. This study aimed to investigate how being overweight or obese affected interactions between muscle strength, function and cognition in Australians aged ≥ 50 years, and whether interactions varied according to age (i.e. ≥ 50–65 vs > 65 years). Methods This study included 2368 adults [mean (standard deviation) age: 63 (7) years; 56% female] from the 2011/2012 Australian Diabetes, Obesity and Lifestyle (AusDiab) follow-up. Physical function was assessed via timed up-and-go (TUG) and muscle strength from knee extensor strength (KES). Cognition was assessed using Mini-Mental-State Exam (MMSE), Spot-the-Word (STW), California Verbal Learning Test (CVLT) and Symbol–Digit-Modalities Test (SDMT). Beta binomial regression was used to evaluate how being overweight or obese influenced strength, physical and cognitive function associations. Results Being overweight or obese did not affect strength-cognition associations regardless of sex or age. With slower physical function; obese females showed better STW (odds ratio [OR] 95% CI]: 1.070 [1.016, 1.127], P = 0.011); obese men better MMSE (OR [95% CI]: 1.157 [1.012, 1.322], P = 0.033); and obese men aged > 65 better CVLT (OR [95% CI]: 1.122 [1.035, 1.217], P = 0.019) and MMSE (OR [95% CI]: 1.233 [1.049, 1.449], P = 0.017) compared to normal weight participants. Conclusion Slower physical function was associated with better performance in some cognitive domains in obese, but not in non-obese adults aged ≥ 50 years. These findings suggest some benefits of obesity to aspects of cognition when physical function is slower, but longitudinal follow-up studies are needed. Supplementary Information The online version contains supplementary material available at 10.1186/s12877-022-03033-3.
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Affiliation(s)
- Niamh L Mundell
- Institute for Physical Activity and Nutrition (IPAN), School of Exercise and Nutrition Sciences, Deakin University, Geelong, Australia.
| | - Parneet Sethi
- Physical Activity Laboratory, Baker Heart and Diabetes Institute, Melbourne, Australia
| | - Kaarin J Anstey
- UNSW Ageing Futures Institute, University of New South Wales, Sydney, Australia.,Neuroscience Research Australia, Sydney, Australia
| | - Helen Macpherson
- Institute for Physical Activity and Nutrition (IPAN), School of Exercise and Nutrition Sciences, Deakin University, Geelong, Australia
| | - David W Dunstan
- Institute for Physical Activity and Nutrition (IPAN), School of Exercise and Nutrition Sciences, Deakin University, Geelong, Australia.,Physical Activity Laboratory, Baker Heart and Diabetes Institute, Melbourne, Australia
| | - Steve F Fraser
- Institute for Physical Activity and Nutrition (IPAN), School of Exercise and Nutrition Sciences, Deakin University, Geelong, Australia
| | - Robin M Daly
- Institute for Physical Activity and Nutrition (IPAN), School of Exercise and Nutrition Sciences, Deakin University, Geelong, Australia
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Nguyen P, Ananthapavan J, Tan EJ, Crosland P, Bowe SJ, Gao L, Dunstan DW, Moodie M. Modelling the potential health and economic benefits of reducing population sitting time in Australia. Int J Behav Nutr Phys Act 2022; 19:28. [PMID: 35305678 PMCID: PMC8934131 DOI: 10.1186/s12966-022-01276-2] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2021] [Accepted: 02/28/2022] [Indexed: 01/22/2023] Open
Abstract
Background Strong evidence indicates that excessive time spent sitting (sedentary behaviour) is detrimentally associated with multiple chronic diseases. Sedentary behaviour is prevalent among adults in Australia and has increased during the COVID-19 pandemic. Estimating the potential health benefits and healthcare cost saving associated with reductions in population sitting time could be useful for the development of public health initiatives. Methods A sedentary behaviour model was developed and incorporated into an existing proportional, multi-state, life table Markov model (ACE-Obesity Policy model). This model simulates the 2019 Australian population (age 18 years and above) and estimates the incidence, prevalence and mortality of five diseases associated with sedentary behaviour (type 2 diabetes, stroke, endometrial, breast and colorectal cancer). Key model inputs included population sitting time estimates from the Australian National Health Survey 2014–2015, healthcare cost data from the Australian Institute of Health and Welfare (2015) and relative risk estimates assessed by conducting literature reviews and meta-analyses. Scenario analyses estimated the potential change in disease incidence as a result of changes in population sitting time. This, in turn, resulted in estimated improvements in long term health outcomes (Health-adjusted life years (HALYs)) and healthcare cost-savings. Results According to the model, if all Australian adults sat no more than 4 h per day, the total HALYs gained would be approximately 17,211 with health care cost savings of approximately A$185 million over one year. Under a more feasible scenario, where sitting time was reduced in adults who sit 4 or more hours per day by approximately 36 min per person per day (based on the results of the Stand Up Victoria randomised controlled trial), potential HALYs gained were estimated to be 3,670 and healthcare cost saving could reach A$39 million over one year. Conclusions Excessive sedentary time results in considerable population health burden in Australia. This paper describes the development of the first Australian sedentary behaviour model that can be used to predict the long term consequences of interventions targeted at reducing sedentary behaviour through reductions in sitting time. These estimates may be used by decision makers when prioritising healthcare resources and investing in preventative public health initiatives. Supplementary Information The online version contains supplementary material available at 10.1186/s12966-022-01276-2.
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Swain CTV, Bassett JK, Hodge AM, Dunstan DW, Owen N, Yang Y, Jayasekara H, Hébert JR, Shivappa N, MacInnis RJ, Milne RL, English DR, Lynch BM. Television viewing time and all-cause mortality: interactions with BMI, physical activity, smoking, and dietary factors. Int J Behav Nutr Phys Act 2022; 19:30. [PMID: 35305675 PMCID: PMC8934515 DOI: 10.1186/s12966-022-01273-5] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2021] [Accepted: 03/07/2022] [Indexed: 11/10/2022] Open
Abstract
Background Higher levels of time spent sitting (sedentary behavior) contribute to adverse health outcomes, including earlier death. This effect may be modified by other lifestyle factors. We examined the association of television viewing (TV), a common leisure-time sedentary behavior, with all-cause mortality, and whether this is modified by body mass index (BMI), physical activity, smoking, alcohol intake, soft drink consumption, or diet-associated inflammation. Methods Using data from participants in the Melbourne Collaborative Cohort Study, flexible parametric survival models assessed the time-dependent association of self-reported TV time (three categories: < 2 h/day, 2–3 h/day, > 3 h/day) with all-cause mortality. Interaction terms were fitted to test whether there was effect modification of TV time by the other risk factors. Results From 19,570 participants, 4,417 deaths were reported over a median follow up of 14.5 years. More TV time was associated with earlier mortality; however, this relationship diminished with increasing age. The hazard ratio (HR) and 95% confidence interval (95% CI) for > 3 h/day compared with < 2 h/day of TV time was 1.34 (1.16, 1.55) at 70 years, 1.14 (1.04, 1.23) at 80 years, and 0.95 (0.84, 1.06) at 90 years. The TV time/mortality relationship was more evident in participants who were physically inactive (compared with active; p for interaction < 0.01) or had a higher dietary inflammatory index score (compared with a lower score; p for interaction = 0.03). No interactions were detected between TV time and BMI, smoking, alcohol intake, nor soft-drink consumption (all p for interaction > 0.16). Conclusions The relationship between TV time and all-cause mortality may change with age. It may also be more pronounced in those who are otherwise inactive or who have a pro-inflammatory diet. Supplementary Information The online version contains supplementary material available at 10.1186/s12966-022-01273-5.
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Kandola A, Del Pozo Cruz B, Hayes JF, Owen N, Dunstan DW, Hallgren M. Impact on adolescent mental health of replacing screen-use with exercise: A prospective cohort study. J Affect Disord 2022; 301:240-247. [PMID: 34999126 DOI: 10.1016/j.jad.2021.12.064] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/08/2021] [Revised: 10/27/2021] [Accepted: 12/19/2021] [Indexed: 01/12/2023]
Abstract
BACKGROUND Screen-based device use could increase the risk of adolescent depression. Distinct modalities of screen-use may have differential effects on mental health. We used compositional data analysis to examine how theoretically replacing different screen-uses with exercise might influence future adolescent emotional distress. METHODS In 4,599 adolescents (55% female) from a nationally-representative, prospective cohort, we used time-use diary data at age 14 to estimate daily screen use (television, social media, video game, general computer use) and exercise (team sport and individual exercise). The outcome was emotional distress at age 17, assessed using the emotional symptoms subscale of the Strengths and Difficulties Questionnaire. RESULTS Theoretically replacing 60 min of total screen time with exercise at age 14 was associated with a 0.05 (95%CI -0.08, -0.02) score reduction on the emotional symptoms' subscale at 17 in fully-adjusted models. Replacing 60 min of television or social media use with team sports was associated with a reduction of 0.17 (95%CI, -0.31, -0.04) and 0.15 (95%CI, -0.29, -0.01) in emotional symptom scores, respectively. We found no change in emotional symptom scores when replacing video game or general computer use with team sport, or when replacing any screen time with individual exercise. LIMITATIONS No direct measure of depressive symptoms at follow-up. CONCLUSIONS Replacing any screen time with exercise could reduce emotional distress, but the largest effect sizes were associated with replacing time in television watching and social media with team sports. Recommendations to limit screen-use in adolescents may require a nuanced approach for protecting mental health.
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Affiliation(s)
- Aaron Kandola
- Division of Psychiatry, University College London, London, UK; Institute of Mental Health, University College London, London, UK.
| | - Borja Del Pozo Cruz
- Centre for Active and Healthy Ageing, Department of Sports Science and Clinical Biomechanics, University of Southern Denmark, Campusvej 55, Odense 5230, Denmark
| | - Joseph F Hayes
- Division of Psychiatry, University College London, London, UK; Camden and Islington NHS Foundation Trust, London, UK
| | - Neville Owen
- Behavioural Epidemiology Laboratory, Baker Heart & Diabetes Institute, Melbourne, Australia; Centre for Urban Transitions, Swinburne University of Technology, Melbourne, Australia
| | - David W Dunstan
- Physical Activity Laboratory, Baker Heart & Diabetes Institute, Melbourne, Australia; Mary MacKillop Institute for Health Research, Australian Catholic University, Melbourne, Australia
| | - Mats Hallgren
- Epidemiology of Psychiatric Conditions, Substance Use and Social Environment (EPiCSS), Department of Public Health Sciences, Karolinska Institutet, Solna, Sweden
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Verswijveren SJJM, Lamb KE, Martín-Fernández JA, Winkler E, Leech RM, Timperio A, Salmon J, Daly RM, Cerin E, Dunstan DW, Telford RM, Telford RD, Olive LS, Ridgers ND. Using compositional data analysis to explore accumulation of sedentary behavior, physical activity and youth health. J Sport Health Sci 2022; 11:234-243. [PMID: 33737239 PMCID: PMC9068553 DOI: 10.1016/j.jshs.2021.03.004] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/22/2020] [Revised: 12/23/2020] [Accepted: 01/22/2021] [Indexed: 06/02/2023]
Abstract
PURPOSE The study aimed to describe youth time-use compositions, focusing on time spent in shorter and longer bouts of sedentary behavior and physical activity (PA), and to examine associations of these time-use compositions with cardiometabolic biomarkers. METHODS Accelerometer and cardiometabolic biomarker data from 2 Australian studies involving youths 7-13 years old were pooled (complete cases with accelerometry and adiposity marker data, n = 782). A 9-component time-use composition was formed using compositional data analysis: time in shorter and longer bouts of sedentary behavior; time in shorter and longer bouts of light-, moderate-, or vigorous-intensity PA; and "other time" (i.e., non-wear/sleep). Shorter and longer bouts of sedentary time were defined as <5 min and ≥5 min, respectively. Shorter bouts of light-, moderate-, and vigorous-intensity PA were defined as <1 min; longer bouts were defined as ≥1 min. Regression models examined associations between overall time-use composition and cardiometabolic biomarkers. Then, associations were derived between ratios of longer activity patterns relative to shorter activity patterns, and of each intensity level relative to the other intensity levels and "other time", and cardiometabolic biomarkers. RESULTS Confounder-adjusted models showed that the overall time-use composition was associated with adiposity, blood pressure, lipids, and the summary score. Specifically, more time in longer bouts of light-intensity PA relative to shorter bouts of light-intensity PA was significantly associated with greater body mass index z-score (zBMI) (β = 1.79; SE = 0.68) and waist circumference (β = 18.35, SE = 4.78). When each activity intensity was considered relative to all higher intensities and "other time", more time in light- and vigorous-intensity PA, and less time in sedentary behavior and moderate-intensity PA, were associated with lower waist circumference. CONCLUSION Accumulating PA, particularly light-intensity PA, in frequent short bursts may be more beneficial for limiting adiposity compared to accumulating the same amount of PA at these intensities in longer bouts.
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Affiliation(s)
- Simone J J M Verswijveren
- Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong, VIC 3216, Australia.
| | - Karen E Lamb
- Melbourne School of Population and Global Health, University of Melbourne, Parkville, VIC 3053, Australia
| | - Josep A Martín-Fernández
- Department of Computer Science, Applied Mathematics and Statistics, University of Girona, Girona 17003, Spain
| | - Elisabeth Winkler
- School of Public Health, University of Queensland, Herston, QLD 4006, Australia
| | - Rebecca M Leech
- Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong, VIC 3216, Australia
| | - Anna Timperio
- Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong, VIC 3216, Australia
| | - Jo Salmon
- Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong, VIC 3216, Australia
| | - Robin M Daly
- Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong, VIC 3216, Australia
| | - Ester Cerin
- Mary MacKillop Institute for Health Research, Australian Catholic University, Fitzroy, VIC 3065, Australia; School of Public Health, University of Hong Kong, Hong Kong, China
| | - David W Dunstan
- Mary MacKillop Institute for Health Research, Australian Catholic University, Fitzroy, VIC 3065, Australia; Baker Heart and Diabetes Institute, Melbourne, VIC 3004, Australia
| | - Rohan M Telford
- Research Institute for Sport and Exercise, University of Canberra, Bruce, ACT 2617, Australia
| | - Richard D Telford
- Research Institute for Sport and Exercise, University of Canberra, Bruce, ACT 2617, Australia
| | - Lisa S Olive
- School of Psychology, Deakin University, Burwood, VIC 3125, Australia; IMPACT Research Institute, Deakin University, Burwood, VIC 3125, Australia; ANU Medical School, Australian National University, Garran, ACT 2605, Australia
| | - Nicola D Ridgers
- Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong, VIC 3216, Australia
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Nguyen P, Le LKD, Ananthapavan J, Gao L, Dunstan DW, Moodie M. Economics of sedentary behaviour: A systematic review of cost of illness, cost-effectiveness, and return on investment studies. Prev Med 2022; 156:106964. [PMID: 35085596 DOI: 10.1016/j.ypmed.2022.106964] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Revised: 11/20/2021] [Accepted: 01/15/2022] [Indexed: 10/19/2022]
Abstract
AIMS METHODS: RESULTS: We identified nine articles (conducted in Australia (n = 5), Europe (n = 3) and China (n = 1)); three reported healthcare costs associated with excessive sedentary time, whilst six were economic evaluations of interventions targeting sedentary behaviour. Healthcare costs associated with excessive sedentary time as reported in cost of illness studies were substantial; however, none explored non-health sector costs. In contrast, all full economics evaluations adopted a societal perspective; however, costs included differed depending on the intervention context. One sedentary behaviour intervention in children was cost-saving. The five interventions targeting occupational sitting time of adults in office workplaces were cost-effective. Physical environmental changes such as sit-stand desks, active workstations etc., were the key cost driver. CONCLUSIONS Sedentary behaviour is likely associated with excess healthcare costs, although future research should also explore costs across other sectors. Cost-effectiveness evidence of sedentary behaviour reduction interventions in workplaces is limited but consistent. Key gaps relate to the economic credentials of interventions targeting children, and modelling of long-term health benefits of interventions.
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Affiliation(s)
- Phuong Nguyen
- Deakin Health Economics, Institute for Health Transformation, Deakin University, Geelong, Victoria, Australia; Global Obesity Centre, Institute for Health Transformation, Deakin University, Geelong, Victoria, Australia.
| | - Long Khanh-Dao Le
- Deakin Health Economics, Institute for Health Transformation, Deakin University, Geelong, Victoria, Australia
| | - Jaithri Ananthapavan
- Deakin Health Economics, Institute for Health Transformation, Deakin University, Geelong, Victoria, Australia; Global Obesity Centre, Institute for Health Transformation, Deakin University, Geelong, Victoria, Australia
| | - Lan Gao
- Deakin Health Economics, Institute for Health Transformation, Deakin University, Geelong, Victoria, Australia; School of Biomedical Sciences and Pharmacy, The University of Newcastle, Callaghan, NSW, Australia
| | - David W Dunstan
- Baker Heart and Diabetes Institute, Melbourne, Australia; Mary MacKillop Institute for Health Research, Australian Catholic University, Melbourne, Victoria, Australia
| | - Marj Moodie
- Deakin Health Economics, Institute for Health Transformation, Deakin University, Geelong, Victoria, Australia; Global Obesity Centre, Institute for Health Transformation, Deakin University, Geelong, Victoria, Australia
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Garduno AC, LaCroix AZ, LaMonte MJ, Dunstan DW, Evenson KR, Wang G, Di C, Schumacher BT, Bellettiere J. Associations of Daily Steps and Step Intensity With Incident Diabetes in a Prospective Cohort Study of Older Women: The OPACH Study. Diabetes Care 2022; 45:339-347. [PMID: 35050362 PMCID: PMC8914434 DOI: 10.2337/dc21-1202] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/07/2021] [Accepted: 11/12/2021] [Indexed: 02/03/2023]
Abstract
OBJECTIVE The primary aim was to assess associations between total steps per day and incident diabetes, whereas the secondary aim was to assess whether the intensity and/or cadence of steps is associated with incident diabetes. RESEARCH DESIGN AND METHODS Women without physician-diagnosed diabetes (n = 4,838; mean [SD] age 78.9 [6.7] years) were followed up to 6.9 years; 395 developed diabetes. Hip-worn ActiGraph GT3X+ accelerometers worn for 1 week enabled measures of total, light-intensity, and moderate- to vigorous-intensity (MV-intensity) steps per day. Using Cox proportional hazards analysis we modeled adjusted change in the hazard rate for incident diabetes associated with total, light-intensity, and MV-intensity steps per day. We further estimated the proportion of the steps-diabetes association mediated by BMI. RESULTS On average, participants took 3,729 (SD 2,114) steps/day, of which 1,875 (791) were light-intensity steps and 1,854 ± 1,762 were MV-intensity. More steps per day were associated with a lower hazard rate for incident diabetes. Confounder-adjusted models for a 2,000 steps/day increment yielded hazard ratio (HR) 0.88 (95% CI 0.78-1.00; P = 0.046). After further adjustment for BMI, HR was 0.90 (95% CI 0.80-1.02; P = 0.11). BMI did not significantly mediate the steps-diabetes association (proportion mediated = 17.7% [95% CI -55.0 to 142.0]; P = 0.09]). The relationship between MV-intensity steps per day (HR 0.86 [95% CI 0.74-1.00]; P = 0.04) and incident diabetes was stronger than for light-intensity steps per day (HR 0.97 [95% CI 0.73-1.29]; P = 0.84). CONCLUSIONS These findings suggest that for older adults, more steps per day are associated with lower incident diabetes and MV-intensity steps are most strongly associated with a lower hazard of diabetes. This evidence supports that regular stepping is an important risk factor for type 2 diabetes prevention in older adults.
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Affiliation(s)
- Alexis C Garduno
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California, San Diego, San Diego, CA.,Division of Epidemiology and Biostatistics, School of Public Health, San Diego State University, San Diego, CA
| | - Andrea Z LaCroix
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California, San Diego, San Diego, CA
| | - Michael J LaMonte
- Department of Epidemiology and Environmental Health, School of Public Health and Health Professions, University at Buffalo-SUNY, Buffalo, NY
| | - David W Dunstan
- Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia.,Mary MacKillop Institute for Health Research, Australian Catholic University, Melbourne, Victoria, Australia
| | - Kelly R Evenson
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Guangxing Wang
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA
| | - Chongzhi Di
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA
| | - Benjamin T Schumacher
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California, San Diego, San Diego, CA.,Division of Epidemiology and Biostatistics, School of Public Health, San Diego State University, San Diego, CA
| | - John Bellettiere
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California, San Diego, San Diego, CA
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Hadgraft N, Winkler E, Goode AD, Gunning L, Dunstan DW, Owen N, Sugiyama T, Healy GN. How supportive are workplace environments for sitting less and moving more? A descriptive study of Australian workplaces participating in the BeUpstanding program. Prev Med Rep 2022; 24:101616. [PMID: 34976672 PMCID: PMC8684026 DOI: 10.1016/j.pmedr.2021.101616] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2021] [Revised: 10/18/2021] [Accepted: 10/22/2021] [Indexed: 01/26/2023] Open
Abstract
Workplaces varied in the number of activity-supportive characteristics present. Spatial characteristics were more common than resource or policy characteristics. Characteristics absent in most workplaces were likely to be modifiable or low cost (“easy wins”). Almost all workplaces had some room for improvement in terms of activity-supportive factors.
Desk-based workers are highly sedentary; this has been identified as an emerging work health and safety issue. To reduce workplace sitting time and promote physical activity it is important to understand what factors are already present within workplaces to inform future interventions. This cross-sectional study examined the prevalence of supportive environmental factors, prior to workplaces taking part in a ‘sit less, move more’ initiative (BeUpstanding). Participants were 291 Australian-based workplace champions (representing 230 organisations) who unlocked the BeUpstanding program’s online toolkit between September 2017 and mid-November 2020, and who completed surveys relating to champion characteristics, organisation and workplace characteristics, and the availability of environmental factors to support sitting less and moving more. Factors were characterized using descriptive statistics and compared across key sectors and factor categories (spatial; resources/initiatives; policy/cultural) using mixed logistic regression models. Of the 42 factors measured, only 11 were present in > 50% of workplaces. Spatial design factors were more likely to be present than resources/initiatives or policy/cultural factors. Centralised printers were the most commonly reported attribute (94%), while prompts to encourage stair use were the least common (4%). Most workplace factors with < 50% prevalence were modifiable and/or were considered modifiable with low cost. Organisations that were public sector, not small/medium, not regional/remote, and not blue-collar had higher odds of having supportive factors than their counterparts; however, workplaces varied considerably in the number of factors present. These findings can assist with developing and targeting initiatives and promoting feasible strategies for desk-based workers to sit less and move more.
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Affiliation(s)
- Nyssa Hadgraft
- Centre for Urban Transitions, Swinburne University of Technology, Melbourne, Australia.,Baker Heart & Diabetes Institute, Melbourne, Australia
| | - Elisabeth Winkler
- The University of Queensland, School of Public Health, Brisbane, Australia
| | - Ana D Goode
- The University of Queensland, School of Public Health, Brisbane, Australia
| | | | - David W Dunstan
- Baker Heart & Diabetes Institute, Melbourne, Australia.,Mary MacKillop Institute for Health Research, Australian Catholic University, Melbourne, Australia
| | - Neville Owen
- Centre for Urban Transitions, Swinburne University of Technology, Melbourne, Australia.,Baker Heart & Diabetes Institute, Melbourne, Australia
| | - Takemi Sugiyama
- Centre for Urban Transitions, Swinburne University of Technology, Melbourne, Australia.,Baker Heart & Diabetes Institute, Melbourne, Australia
| | - Genevieve N Healy
- The University of Queensland, School of Public Health, Brisbane, Australia.,Baker Heart & Diabetes Institute, Melbourne, Australia
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Taylor FC, Pinto AJ, Maniar N, Dunstan DW, Green DJ. The Acute Effects of Prolonged Uninterrupted Sitting on Vascular Function: A Systematic Review and Meta-analysis. Med Sci Sports Exerc 2022; 54:67-76. [PMID: 34334722 DOI: 10.1249/mss.0000000000002763] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
OBJECTIVE This study aimed to determine the dose-response relationship between prolonged sitting and vascular function in healthy individuals and those with metabolic disturbances and to investigate the acute effects, on vascular function, of interventions that target interrupting prolonged sitting. DESIGN This is a systematic review with meta-analysis. DATA SOURCES Ovid Embase, Ovid Medline, PubMed, and CINAHL were searched from inception to 4 December 2020. ELIGIBILITY CRITERIA Randomized crossover trials, quasi-randomized trials, and parallel group trials where vascular function (flow-mediated dilation [FMD]) was assessed before and after an acute period of sedentary behavior was used in this study. RESULTS Prolonged sitting resulted in a significant decrease in the standardized mean change (SMC) for lower-limb FMD at the 120-min (SMC = -0.85, 95% confidence interval [CI] = -1.32 to -0.38) and 180-min (SMC = -1.18, 95% CI = -1.69 to -0.66) time points. A similar pattern was observed for lower-limb shear rate. No significant changes were observed for any outcomes in the upper limb. Subgroup analysis indicated that prolonged sitting decreased lower-limb FMD in healthy adults (SMC = -1.33, 95% CI = -1.89 to -0.78) who had higher a priori vascular endothelial function, but not in those with metabolic and vascular dysfunction (SMC = -0.51, 95% CI = -1.18 to 0.15). Interrupting sitting with active interruptions increased the standardized mean difference for FMD, relative to prolonged sitting, but it was not statistically significant (0.13, 95% CI = -0.20 to 0.45). CONCLUSIONS Lower-limb vascular function is progressively impaired as a consequence of prolonged sitting, up to 180 min. A similar trend was not observed in upper-limb vascular function. Subgroup analysis indicated that prolonged sitting negatively affects healthy populations, a finding not observed in those with metabolic disturbances. Regularly interrupting sitting with activity may be beneficial for those with metabolic disturbances.
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Affiliation(s)
| | - Ana J Pinto
- Applied Physiology and Nutrition Research Group, Laboratory of Assessment and Conditioning in Rheumatology, School of Physical Education and Sport, Faculdade de Medicina FMUSP, Universidade de São Paulo, São Paulo, BRAZIL
| | | | | | - Daniel J Green
- Department of Exercise and Sport Science, School of Human Sciences, The University of Western Australia, Perth, AUSTRALIA
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Abstract
By 2050, 20% of the world's population will be over the age of 65 years, with projections that 80% of older adults will be living in low- to middle-income countries. Physical inactivity and sedentary time are particularly high in older adults, presenting unique public health challenges. In this article, we first review evidence that points to multiple beneficial outcomes of active aging, including better physical function, cognitive function, mental health, social health, and sleep and suggest the need to shift the research focus from chronic disease outcomes to more relevant outcomes that affect independence and quality of life. Second, we review the critical role of age-friendly environments in facilitating active aging equitably across different countries and cultures. Finally, we consider emerging opportunities related to social engagement and technology-enabled mobility that can facilitate active aging. In all these contexts, it is a priority to understand and address diversity within the global aging population. Expected final online publication date for the Annual Review of Public Health, Volume 43 is April 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
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Affiliation(s)
- Shilpa Dogra
- Faculty of Health Sciences (Kinesiology), University of Ontario Institute of Technology, Ontario, Canada;
| | - David W Dunstan
- Physical Activity Laboratory, Baker Heart and Diabetes Institute, Melbourne 3004, Victoria, Australia.,Mary MacKillop Institute for Health Research, Australian Catholic University, Melbourne, Victoria, Australia
| | - Takemi Sugiyama
- Centre for Urban Transitions, Swinburne University of Technology, Hawthorn, Victoria, Australia.,Behavioural Epidemiology Laboratory, Baker Heart and Diabetes Institute, Melbourne 3004, Victoria, Australia
| | - Afroditi Stathi
- School of Sport, Exercise and Rehabilitation Sciences, University of Birmingham, Edgbaston, Birmingham, United Kingdom
| | - Paul A Gardiner
- School of Health and Wellbeing, University of Southern Queensland, Ipswich, Queensland, Australia.,School of Kinesiology, The University of Western Ontario, London, Canada.,Centre for Health Services Research, The University of Queensland, Brisbane, Queensland, Australia
| | - Neville Owen
- Centre for Urban Transitions, Swinburne University of Technology, Hawthorn, Victoria, Australia.,Behavioural Epidemiology Laboratory, Baker Heart and Diabetes Institute, Melbourne 3004, Victoria, Australia
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47
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Dzakpasu FQS, Carver A, Brakenridge CJ, Cicuttini F, Urquhart DM, Owen N, Dunstan DW. Musculoskeletal pain and sedentary behaviour in occupational and non-occupational settings: a systematic review with meta-analysis. Int J Behav Nutr Phys Act 2021; 18:159. [PMID: 34895248 PMCID: PMC8666269 DOI: 10.1186/s12966-021-01191-y] [Citation(s) in RCA: 33] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2021] [Accepted: 08/23/2021] [Indexed: 01/07/2023] Open
Abstract
BACKGROUND Sedentary behaviour (SB; time spent sitting) is associated with musculoskeletal pain (MSP) conditions; however, no prior systematic review has examined these associations according to SB domains. We synthesised evidence on occupational and non-occupational SB and MSP conditions. METHODS Guided by a PRISMA protocol, eight databases (MEDLINE, CINAHL, PsycINFO, Web of Science, Scopus, Cochrane Library, SPORTDiscus, and AMED) and three grey literature sources (Google Scholar, WorldChat, and Trove) were searched (January 1, 2000, to March 17, 2021) for original quantitative studies of adults ≥ 18 years. Clinical-condition studies were excluded. Studies' risk of bias was assessed using the QualSyst checklist. For meta-analyses, random effect inverse-variance pooled effect size was estimated; otherwise, best-evidence synthesis was used for narrative review. RESULTS Of 178 potentially-eligible studies, 79 were included [24 general population; 55 occupational (incuding15 experimental/intervention)]; 56 studies were of high quality, with scores > 0.75. Data for 26 were meta-synthesised. For cross-sectional studies of non-occupational SB, meta-analysis showed full-day SB to be associated with low back pain [LBP - OR = 1.19(1.03 - 1.38)]. Narrative synthesis found full-day SB associations with knee pain, arthritis, and general MSP, but the evidence was insufficient on associations with neck/shoulder pain, hip pain, and upper extremities pain. Evidence of prospective associations of full-day SB with MSP conditions was insufficient. Also, there was insufficient evidence on both cross-sectional and prospective associations between leisure-time SB and MSP conditions. For occupational SB, cross-sectional studies meta-analysed indicated associations of self-reported workplace sitting with LBP [OR = 1.47(1.12 - 1.92)] and neck/shoulder pain [OR = 1.73(1.46 - 2.03)], but not with extremities pain [OR = 1.17(0.65 - 2.11)]. Best-evidence synthesis identified inconsistent findings on cross-sectional association and a probable negative prospective association of device-measured workplace sitting with LBP-intensity in tradespeople. There was cross-sectional evidence on the association of computer time with neck/shoulder pain, but insufficient evidence for LBP and general MSP. Experimental/intervention evidence indicated reduced LBP, neck/shoulder pain, and general MSP with reducing workplace sitting. CONCLUSIONS We found cross-sectional associations of occupational and non-occupational SB with MSP conditions, with occupational SB associations being occupation dependent, however, reverse causality bias cannot be ruled out. While prospective evidence was inconclusive, reducing workplace sitting was associated with reduced MSP conditions. Future studies should emphasise prospective analyses and examining potential interactions with chronic diseases. PROTOCOL REGISTRATION PROSPERO ID # CRD42020166412 (Amended to limit the scope).
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Affiliation(s)
- Francis Q S Dzakpasu
- Mary MacKillop Institute of Health Research, Australian Catholic University, Melbourne, VIC, Australia.
- Physical Activity Laboratory, Baker Heart and Diabetes Institute, Melbourne, VIC, Australia.
- Behavioural Epidemiology Laboratory, Baker Heart and Diabetes Institute, Melbourne, VIC, Australia.
| | - Alison Carver
- Mary MacKillop Institute of Health Research, Australian Catholic University, Melbourne, VIC, Australia
| | - Christian J Brakenridge
- Mary MacKillop Institute of Health Research, Australian Catholic University, Melbourne, VIC, Australia
- Physical Activity Laboratory, Baker Heart and Diabetes Institute, Melbourne, VIC, Australia
- Behavioural Epidemiology Laboratory, Baker Heart and Diabetes Institute, Melbourne, VIC, Australia
| | - Flavia Cicuttini
- Central Clinical School/Department of Epidemiology and Preventive Medicine, Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, VIC, Australia
| | - Donna M Urquhart
- Central Clinical School/Department of Epidemiology and Preventive Medicine, Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, VIC, Australia
| | - Neville Owen
- Behavioural Epidemiology Laboratory, Baker Heart and Diabetes Institute, Melbourne, VIC, Australia
- Centre for Urban Transitions, Swinburne University of Technology, Melbourne, VIC, Australia
| | - David W Dunstan
- Mary MacKillop Institute of Health Research, Australian Catholic University, Melbourne, VIC, Australia
- Physical Activity Laboratory, Baker Heart and Diabetes Institute, Melbourne, VIC, Australia
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48
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Brakenridge CJ, Healy GN, Sethi P, Carver A, Bellettiere J, Salim A, Chastin SFM, Owen N, Dunstan DW. Contrasting compositions of sitting, standing, stepping, and sleeping time: associations with glycaemic outcome by diabetes risk. Int J Behav Nutr Phys Act 2021; 18:155. [PMID: 34863205 PMCID: PMC8642848 DOI: 10.1186/s12966-021-01209-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2021] [Accepted: 10/05/2021] [Indexed: 01/21/2023] Open
Abstract
BACKGROUND Recent evidence suggests that prolonged sitting and its adverse impact on glycaemic indicators appear to be proportional to the degree of insulin resistance. To investigate this finding in a free-living context, we aimed to examine associations of device-measured 24-h time-use compositions of sitting, standing, stepping, and sleeping with fasting glucose (FPG) and 2 h post-load glucose (2hPLG) levels, and to examine separately the associations with time-use compositions among those at lower and at higher risk of developing type 2 diabetes. METHODS Cross-sectional analyses examined thigh-worn inclinometer data (activPAL, 7 day, 24 h/day protocol) from 648 participants (aged 36-80 years) at either lower (< 39 mmol/mol; < 5.7% HbA1c) or higher (≥39 mmol/mol; ≥5.7% HbA1c) diabetes risk from the 2011-2012 Australian Diabetes, Obesity and Lifestyle study. Multiple linear regression models were used to examine associations of differing compositions with FPG and 2hPLG, with time spent in each behaviour allowed to vary up to 60 min. RESULTS In general, the associations with the FPG within the time-use compositions were small, with statistically significant associations observed for sitting and sleeping (in the lower diabetes risk group) and standing (in higher diabetes risk group) only. For 2hPLG, statistically significant associations were observed for stepping only, with findings similar between lower (β = - 0.12 95%CI:-0.22, - 0.02) and higher (β = - 0.13 95%CI:-0.26, - 0.01) risk groups. Varying the composition had minimal impact on FPG; however 1 h less sitting time and equivalent increase in standing time was associated with attenuated FPG levels in higher risk only (Δ FPG% = - 1.5 95%CI: - 2.4, - 0.5). Large differences in 2hPLG were observed for both groups when varying the composition. One hour less sitting with equivalent increase in stepping was associated with attenuated 2hPLG, with estimations similar in lower (Δ 2hPLG% = - 3.8 95%CI: - 7.3, - 0.2) and higher (Δ 2hPLG% = - 5.0 95%CI: - 9.7, - 0.0) risk for diabetes. CONCLUSIONS In middle-aged and older adults, glycaemic control could be improved by reducing daily sitting time and replacing it with stepping. Standing could also be beneficial for those at higher risk of developing type 2 diabetes.
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Affiliation(s)
- Christian J Brakenridge
- Baker Heart and Diabetes Institute, 99 Commercial Rd, Melbourne, VIC, 3004, Australia. .,Mary Mackillop Institute for Health Research, Australian Catholic University, Melbourne, VIC, Australia.
| | - Genevieve N Healy
- School of Public Health, The University of Queensland, Brisbane, QLD, Australia
| | - Parneet Sethi
- Baker Heart and Diabetes Institute, 99 Commercial Rd, Melbourne, VIC, 3004, Australia
| | - Alison Carver
- Mary Mackillop Institute for Health Research, Australian Catholic University, Melbourne, VIC, Australia
| | - John Bellettiere
- Herbert Wertheim School of Public Health and Longevity Science, University of California San Diego, La Jolla, CA, USA
| | - Agus Salim
- Baker Heart and Diabetes Institute, 99 Commercial Rd, Melbourne, VIC, 3004, Australia.,School of Population and Global Health, The University of Melbourne, Melbourne, VIC, Australia
| | - Sebastien F M Chastin
- School of Health and Life Sciences, Glasgow Caledonian University, Glasgow, UK.,Department of Movement and Sports Science, Ghent University, Ghent, Belgium
| | - Neville Owen
- Baker Heart and Diabetes Institute, 99 Commercial Rd, Melbourne, VIC, 3004, Australia.,Centre for Urban Transitions, Swinburne University of Technology, Melbourne, VIC, Australia
| | - David W Dunstan
- Baker Heart and Diabetes Institute, 99 Commercial Rd, Melbourne, VIC, 3004, Australia.,Mary Mackillop Institute for Health Research, Australian Catholic University, Melbourne, VIC, Australia
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49
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Pinto AJ, Meireles K, Peçanha T, Mazzolani BC, Smaira FI, Rezende D, Benatti FB, Ribeiro ACM, Pinto ALS, Lima FR, Shinjo SK, Dantas WS, Mellett NA, Meikle PJ, Owen N, Dunstan DW, Roschel H, Gualano B. Acute cardiometabolic effects of brief active breaks in sitting for patients with rheumatoid arthritis. Am J Physiol Endocrinol Metab 2021; 321:E782-E794. [PMID: 34693756 DOI: 10.1152/ajpendo.00259.2021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
Exercise is a treatment in rheumatoid arthritis, but participation in moderate-to-vigorous exercise is challenging for some patients. Light-intensity breaks in sitting could be a promising alternative. We compared the acute effects of active breaks in sitting with those of moderate-to-vigorous exercise on cardiometabolic risk markers in patients with rheumatoid arthritis. In a crossover fashion, 15 women with rheumatoid arthritis underwent three 8-h experimental conditions: prolonged sitting (SIT), 30-min bout of moderate-to-vigorous exercise followed by prolonged sitting (EX), and 3-min bouts of light-intensity walking every 30 min of sitting (BR). Postprandial glucose, insulin, c-peptide, triglycerides, cytokines, lipid classes/subclasses (lipidomics), and blood pressure responses were assessed. Muscle biopsies were collected following each session to assess targeted proteins/genes. Glucose [-28% in area under the curve (AUC), P = 0.036], insulin (-28% in AUC, P = 0.016), and c-peptide (-27% in AUC, P = 0.006) postprandial responses were attenuated in BR versus SIT, whereas only c-peptide was lower in EX versus SIT (-20% in AUC, P = 0.002). IL-1β decreased during BR, but increased during EX and SIT (P = 0.027 and P = 0.085, respectively). IL-1ra was increased during EX versus BR (P = 0.002). TNF-α concentrations decreased during BR versus EX (P = 0.022). EX, but not BR, reduced systolic blood pressure (P = 0.013). Lipidomic analysis showed that 7 of 36 lipid classes/subclasses were significantly different between conditions, with greater changes being observed in EX. No differences were observed for protein/gene expression. Brief active breaks in sitting can offset markers of cardiometabolic disturbance, which may be particularly useful for patients who may find it difficult to adhere to exercise.NEW & NOTEWORTHY Exercise is a treatment in rheumatoid arthritis but is challenging for some patients. Light-intensity breaks in sitting could be a promising alternative. Our findings show beneficial, but differential, cardiometabolic effects of active breaks in sitting and exercise in patients with rheumatoid arthritis. Breaks in sitting mainly improved glycemic and inflammatory markers, whereas exercise improved lipidomic and hypotensive responses. Breaks in sitting show promise in offsetting aspects of cardiometabolic disturbance associated with prolonged sitting in rheumatoid arthritis.
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Affiliation(s)
- Ana J Pinto
- Applied Physiology and Nutrition Research Group, School of Physical Education and Sport, Laboratory of Assessment and Conditioning in Rheumatology, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, Brazil
| | - Kamila Meireles
- Applied Physiology and Nutrition Research Group, School of Physical Education and Sport, Laboratory of Assessment and Conditioning in Rheumatology, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, Brazil
| | - Tiago Peçanha
- Applied Physiology and Nutrition Research Group, School of Physical Education and Sport, Laboratory of Assessment and Conditioning in Rheumatology, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, Brazil
| | - Bruna C Mazzolani
- Applied Physiology and Nutrition Research Group, School of Physical Education and Sport, Laboratory of Assessment and Conditioning in Rheumatology, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, Brazil
| | - Fabiana I Smaira
- Applied Physiology and Nutrition Research Group, School of Physical Education and Sport, Laboratory of Assessment and Conditioning in Rheumatology, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, Brazil
| | - Diego Rezende
- Applied Physiology and Nutrition Research Group, School of Physical Education and Sport, Laboratory of Assessment and Conditioning in Rheumatology, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, Brazil
| | - Fabiana B Benatti
- Applied Physiology and Nutrition Research Group, School of Physical Education and Sport, Laboratory of Assessment and Conditioning in Rheumatology, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, Brazil
- School of Applied Sciences, State University of Campinas, Limeira, Brazil
| | - Ana C M Ribeiro
- Rheumatology Division, School of Medicine FMUSP, University of Sao Paulo, Sao Paulo, Brazil
| | - Ana L S Pinto
- Applied Physiology and Nutrition Research Group, School of Physical Education and Sport, Laboratory of Assessment and Conditioning in Rheumatology, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, Brazil
- Rheumatology Division, School of Medicine FMUSP, University of Sao Paulo, Sao Paulo, Brazil
| | - Fernanda R Lima
- Applied Physiology and Nutrition Research Group, School of Physical Education and Sport, Laboratory of Assessment and Conditioning in Rheumatology, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, Brazil
- Rheumatology Division, School of Medicine FMUSP, University of Sao Paulo, Sao Paulo, Brazil
| | - Samuel K Shinjo
- Rheumatology Division, School of Medicine FMUSP, University of Sao Paulo, Sao Paulo, Brazil
| | - Wagner S Dantas
- Integrated Physiology and Molecular Medicine Laboratory, Pennington Biomedical Research Center, Louisiana State University, Baton Rouge, Louisiana
| | - Natalie A Mellett
- Physical Activity, Behavioural Epidemiology and/or Metabolomics Laboratories, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
| | - Peter J Meikle
- Physical Activity, Behavioural Epidemiology and/or Metabolomics Laboratories, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
| | - Neville Owen
- Physical Activity, Behavioural Epidemiology and/or Metabolomics Laboratories, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
- Centre for Urban Transitions, Swinburne University of Technology, Melbourne, Victoria, Australia
| | - David W Dunstan
- Physical Activity, Behavioural Epidemiology and/or Metabolomics Laboratories, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
- Mary MacKillop Institute for Health Research, Australian Catholic University, Melbourne, Victoria, Australia
| | - Hamilton Roschel
- Applied Physiology and Nutrition Research Group, School of Physical Education and Sport, Laboratory of Assessment and Conditioning in Rheumatology, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, Brazil
- School of Applied Sciences, State University of Campinas, Limeira, Brazil
| | - Bruno Gualano
- Applied Physiology and Nutrition Research Group, School of Physical Education and Sport, Laboratory of Assessment and Conditioning in Rheumatology, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, Brazil
- School of Applied Sciences, State University of Campinas, Limeira, Brazil
- Food Research Center, University of São Paulo, Sao Paulo, Brazil
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50
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Homer AR, Taylor FC, Dempsey PC, Wheeler MJ, Sethi P, Grace MS, Green DJ, Cohen ND, Larsen RN, Kingwell BA, Owen N, Dunstan DW. Different frequencies of active interruptions to sitting have distinct effects on 22 h glycemic control in type 2 diabetes. Nutr Metab Cardiovasc Dis 2021; 31:2969-2978. [PMID: 34364775 DOI: 10.1016/j.numecd.2021.07.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Revised: 07/01/2021] [Accepted: 07/01/2021] [Indexed: 11/23/2022]
Abstract
BACKGROUND & AIMS Whether the frequency of interruptions to sitting time involving simple resistance activities (SRAs), compared to uninterrupted sitting, differentially affected 22 h glycemic control in adults with medication-controlled type 2 diabetes (T2D). METHODS & RESULTS Twenty-four participants (13 men; mean ± SD age 62 ± 8 years) completed three 8 h laboratory conditions: SIT: uninterrupted sitting; SRA3: sitting interrupted with 3 min of SRAs every 30 min; and, SRA6: sitting interrupted with 6 min of SRAs every 60 min. Flash glucose monitors assessed glycemic control over a 22 h period. No differences were observed between conditions for overall 22 h glycemic control as measured by AUCtotal, mean glucose and time in hyperglycemia. During the 3.5 h post-lunch period, mean glucose was significantly lower during SRA6 (10.1 mmol·L-1, 95%CI 9.2, 11.0) compared to SIT (11.1 mmol·L-1, 95%CI 10.2, 12.0; P = 0.006). Post-lunch iAUCnet was significantly lower during SRA6 (6.2 mmol·h·L-1, 95%CI 3.3, 9.1) compared to SIT (9.9 mmol·h·L-1, 95%CI 7.0, 12.9; P = 0.003). During the post-lunch period, compared to SIT (2.2 h, 95%CI 1.7, 2.6), time in hyperglycemia was significantly lower during SRA6 (1.5 h, 95%CI 1.0, 1.9, P = 0.001). Nocturnal mean glucose was significantly lower following the SRA3 condition (7.6 mmol·L-1, 95%CI 7.1, 8.1) compared to SIT (8.1 mmol·L-1, 95%CI 7.6, 8.7, P = 0.024). CONCLUSIONS With standardized total activity time, less-frequent active interruptions to sitting may acutely improve glycemic control; while more-frequent interruptions may be beneficial for nocturnal glucose in those with medication-controlled T2D.
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Affiliation(s)
- Ashleigh R Homer
- Baker Heart & Diabetes Institute, Melbourne, VIC, Australia; Mary MacKillop Institute for Health Research, Australian Catholic University, Australia.
| | - Frances C Taylor
- Baker Heart & Diabetes Institute, Melbourne, VIC, Australia; Mary MacKillop Institute for Health Research, Australian Catholic University, Australia
| | - Paddy C Dempsey
- Baker Heart & Diabetes Institute, Melbourne, VIC, Australia; MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK; Diabetes Research Centre, University of Leicester, Leicester General Hospital, Leicester, UK
| | - Michael J Wheeler
- Baker Heart & Diabetes Institute, Melbourne, VIC, Australia; Mary MacKillop Institute for Health Research, Australian Catholic University, Australia; School of Sport Science, Exercise and Health, University of Western Australia, Perth, Australia
| | - Parneet Sethi
- Baker Heart & Diabetes Institute, Melbourne, VIC, Australia
| | - Megan S Grace
- Baker Heart & Diabetes Institute, Melbourne, VIC, Australia; School of Clinical Medicine, University of Queensland, Brisbane, QLD, Australia
| | - Daniel J Green
- School of Sport Science, Exercise and Health, University of Western Australia, Perth, Australia
| | - Neale D Cohen
- Baker Heart & Diabetes Institute, Melbourne, VIC, Australia
| | - Robyn N Larsen
- Baker Heart & Diabetes Institute, Melbourne, VIC, Australia; School of Agriculture and Food, University of Melbourne, Melbourne, VIC, Australia
| | - Bronwyn A Kingwell
- Baker Heart & Diabetes Institute, Melbourne, VIC, Australia; CSL Ltd, Bio21, Parkville, Australia; Department of Physiology, School of Biomedical Science, University of Melbourne, Melbourne, VIC, Australia; Department of Physiology, School of Medicine, Nursing and Health Sciences, Monash University, Melbourne, VIC, Australia
| | - Neville Owen
- Baker Heart & Diabetes Institute, Melbourne, VIC, Australia; Centre for Urban Transitions, Swinburne University of Technology, Melbourne, Victoria, Australia
| | - David W Dunstan
- Baker Heart & Diabetes Institute, Melbourne, VIC, Australia; Mary MacKillop Institute for Health Research, Australian Catholic University, Australia
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