Accurate measurement is necessary for documenting levels of sitting time, understanding dose-response relationships with specific health parameters, and evaluating the efficacy and effectiveness of programs to reduce this behaviour. Both self-report and device-based measures of sitting time provide important and complementary insights, with self-report providing contextual information, and device-based measures providing quantitative information on the duration and patterns of sitting time.
However, the ability of both self-report and device-based measures to capture intervention change remains poorly understood, and additional research is needed to identify the optimal method for combining self-report and device-based data. Further, the research potential of device-based measures has been severely under-utilized, with analyses of free-living data typically restricted to the application of count thresholds or regression-based prediction models.
An emerging approach to data reduction that promises to revolutionize device-based measurement of physical activity and sedentary time is pattern recognition. With mobile phones and accelerometer-based motion sensors providing easy access to large volumes of high frequency raw tri-axial accelerometer signal, pattern recognition has enormous upside potential for device-based measurement of sitting and other activity-related behaviours.
Recent work by CI-C Trost has demonstrated standard supervised learning algorithms such as artificial neural networks_ENREF_8, and support vector machines_ENREF_19 to be highly accurate in recognizing activity type (e.g., sitting vs. standing) and predicting energy expenditure. However, before these models can be deployed to the field, additional research is needed to identify features and/or algorithms that have sufficient time resolution to reliably detect free-living activities and transitions from one activity to the next.
Moreover, user-friendly systems for storing and processing these vast volumes of data need to be established.
To further advance the development of valid, yet practical measures of sitting and physically-active time, and significantly enhance research capacity in chronic disease prevention in Australia and worldwide, we will address the following research priorities:
Our multidisciplinary research team is uniquely qualified to address the aforementioned research priorities. Theme chairs CI-C Trost and CI-F Healy are internationally recognised leaders in sedentary behaviour and activity measurement, and their broad network of collaborators and industry partners will facilitate uptake and application of findings arising from the CRE.
AI Matthews will provide expertise in both population surveillance of sitting time, as well as novel applications (e.g. online) for the collection of contextual data48,49. CI-C Trost and AI Wong have successfully developed and validated several supervised learning algorithms to detect activity type and predict energy expenditure from accelerometer data18,20.
The involvement of AI Wong in the CRE will allow our team to extend this work and develop novel data analytic approaches to reliably detect sedentary time in age-diverse free-living samples. Our collaboration with AI Wong’s laboratory will also provide a unique opportunity for our Research Fellows to work with researchers and postgraduate students from computer science and engineering, and thus enhance their multidisciplinary research skills.
AI Chastin provides expertise into measuring the patterns of sitting time change following intervention (Themes 2 & 3); he also provides a link with activity monitor industry partners for potential device refinement and development based on our CRE findings. Deakin University have pledged a 3-year ‘value-add’ domestic PhD scholarship to assess sitting time patterns in children using these devices which will provide the opportunity for CIs Salmon and Timperio to team with CI-C Trost, CI-F Healy and AI Chastin.
AI Friedenreich will provide expertise and guidance to our Research Fellows on the development and implementation of innovative sedentary behaviour outcome measures for large-scale intervention trials.
Utilising our strengths in both self-report and device-based methodologies, our CRE will develop valid and practical measures of sitting and activity time, and capacity in the use and application of such measures, within population-based investigations, intervention trials, and mechanistic studies.
Physiological adaptation to physical activity opposes many aspects of the pathophysiology of chronic diseases including that of type 2 diabetes, cardiovascular disease and the major cancers. However, the effects of acute and chronic physical activity on bodily organs, systems and processes vary substantially in relation to activity mode, frequency, intensity and duration.
Over the past 25 years, the mechanisms underlying the cardiometabolic benefits of regular Moderate to Physical Activity (MVPA) have been well characterised by us and others and provide a rationale and quantification for current physical activity guidelines for adults, children and youth. In contrast, reducing and breaking up sitting time is a new approach to enhancing daily physical movement and relatively little is known regarding the mechanisms of benefit.
In the absence of such evidence, public health guidelines for reducing sitting time and acceptable upper limits of accumulated or sustained sitting time will remain non-specific. Our team has made the first significant inroads regarding mechanisms – establishing that relative to uninterrupted sitting, breaks in sedentary time among adults acutely improves glycaemic control and reduces plasma fibrinogen.
Interestingly, we have shown that the gene expression pattern in vastus lateralis muscle associated with interrupted sitting has aspects which are both aligned with, and distinct from that of MVPA activity. This CRE will provide the platform to develop this work from laboratory studies examining the acute effects of breaks in sitting time over a single day to more meaningful and comprehensive mechanistic investigations of chronic change over weeks and months.
The use of simulated ‘real life’ settings (e.g., home, school and office) and the inclusion of younger and older age groups will ensure that study outcomes are relevant.
The next logical step in our research program is to conduct randomised controlled trials of activity breaks over periods of weeks to months and examine associated biological outcomes.
These studies will examine:
Establishing the dose-response relationships between interrupting sitting, risk markers and physiological adaptations will inform further work in specific disease groups – for example, among patients with hypertension, peripheral artery disease, osteoarthritis, overweight and obesity, the metabolic syndrome and diabetes, cognitive impairment and those with elevated thrombotic risk.
This CRE will provide a catalyst to focus the broad expertise of our team on the mechanisms underlying the benefit of breaking up sitting time. Theme chairs CI-D Dunstan and CI-G Kingwell have considerable experience in techniques to examine glycaemic control, lipid homeostasis, vascular function, hemostatic factors and muscle metabolism.
The involvement of CI-H Lambert and his laboratory provides a unique opportunity to further examine changes mediated by the autonomic nervous system, which is of particular relevance to the postural changes associated with interrupted sitting. This will be complemented by unique physiological expertise across the lifespan - specifically in children (AI Green, AI Chin A Paw), adults (AI Hamilton, AI Elisabeth Lambert) and older adults (AI Daly).
The CRE will facilitate the adaptation of Baker IDI’s ground-breaking sitting time experimental models within Deakin University to permit experimental research into children in simulated school environments. Specifically, CIs Dunstan and Salmon together with AIs Green and Chin A Paw will focus on the impact of breaking up sitting time on physiological and cognitive function in children.
Deakin University have pledged a 3-year ‘value-add’ domestic PhD scholarship to facilitate this work. Similarly, CIs Dunstan, Owen, Kingwell and Lambert, in collaboration with AIs Daly and Hamilton, will develop and test strategies in simulated ‘aged-care’ environments in older adults, informing field-based work proposed by CIs Eakin and Healy.
The establishment of our new collaboration with AI Lautenschlager will extend applications and opportunities for our Fellows and PhD students into linking metabolic and neurotransmitter changes with indices of cognitive function.
The proposed investigations will capitalise on Baker IDI’s recent investment and expertise in high throughput screening facilities allowing a discovery strategy using genomic, epigenetic and lipidomic approaches to identify candidate microRNAs, genes, proteins and regulatory pathways important in sedentary physiology. Such candidates may prove to be important risk markers for the efficacy of intervention strategies to reduce sitting time.
Building on our strong track record in intervention trials and integrative physiology, our CRE will characterise the mechanisms contributing to the health benefits of breaking up sedentary time across key age groups.
This is necessary to:
The average person spends more than 50% of the day sitting and only 3% in MVPA, yet the majority of research on physical activity and chronic disease prevention has focused on the promotion of MVPA, with relatively little and only recent emphasis on reducing sitting time. Despite more than 50 years of research focus, most of it targeting individual-level behaviour change, evidence of the efficacy of strategies to promote MVPA among very young children through to older adults is equivocal, if not underwhelming.
There are clear research gaps and therefore a public health imperative to determine ways to target those who sit the most across all life stages – and to do so more rapidly and effectively than has been the case with MVPA. Sitting time can be highly contextually-driven and often is dictated by the setting in which it occurs (e.g., most children must sit for much of the day in school, youth are often driven to destinations by car, and most office workers sit for the majority of the day at work).
Accordingly, we have hypothesised, and our research to date has shown, that interventions to reduce sitting are most effective when implemented in settings, such as schools and workplaces, with attention to individual behaviour, environmental and organizational drivers. Importantly, such settings-based approaches have strong potential for rapid, scalable and potentially sustainable behaviour change.
Our trials work to date has demonstrated that while there are challenges in reducing children’s discretionary sitting time at home, it is feasible to reduce home- and school-based sitting time in children by 13 minutes/day (findings under review), workplace sitting time among office-based workers by approximately two hours/day, and total sitting time in older free-living adults by about 30 minutes/day.
Key next steps include building on our mechanistic and dose-response studies (Theme 2) that identify intervention targets for different groups, with our settings-based intervention trials elucidating the patterns of sitting and physically-active time that will be most feasible and beneficial to change.
From recent research by CRE investigators, we have some evidence of the feasibility and acceptability of reducing sitting time at school (using pedagogical approaches) and rapidly accumulating evidence of efficacy in the workplace (using height-adjustable workstations). The key next research questions for those studies concern translation of the research into ‘real-world’ practice (see below and AC2).
In particular, we plan to examine the:
In the more nascent areas of youth and older adults’ sitting time and children’s sitting time at home, however, we need to better understand the prevalence and correlates so that potentially effective interventions can be developed.
These studies will address the:
Central to all the proposed trials will be the use of device-based measurement of sitting time, with the incorporation of markers of adverse health outcomes (eg, blood lipids, adiposity, blood pressure) and cognitive function measurements where feasible.
Our team of CRE investigators is at the forefront of sitting time intervention research internationally. Theme chairs CI-B Salmon and CI-E Eakin have extensive population intervention experience applying theoretically-framed behaviour change strategies across the age spectrum and among clinical populations.
CI-B Salmon works closely with AI Shilton through her position as Chair of the Heart Foundation’s National Physical Activity Committee. AI Shilton will play a critical role as knowledge broker and will provide important input to all of the interventions from a policy and practice perspective as well as assisting with and advising on dissemination of findings and research translation.
Our enhanced and new collaborations with AIs Chin, A Paw, Hamilton, Daly and Green (already identified in Theme 2) will extend to Theme 3 through their involvement in funded and planned intervention studies such as Transform-Us!. AI Hamilton has consulted a number of CRE investigators with plans to conduct a trial on the effectiveness of height-adjustable desks for reducing sitting time among children in elementary schools in the US and he will collaborate on our related intervention.
AI Green will provide input to non-invasive health assessment techniques (identified in Theme 2) in the child and youth studies. AI Cerin will provide mentorship and guidance in the development of innovative data-analysis methods. AI De Bourdeaudhuij will provide expertise in the application of behavioural science theory and evidence in the development of field-based interventions, as well as access to data from large Europe-wide and Belgian studies.
AI Sallis will provide valuable conceptual input into the development and delivery of the transport-based intervention to reduce sitting in youth, which will be based on findings from IPEN Adolescent (NIH-funded multi-country study, on which Salmon is a CI). AI Biddle will provide guidance and mentorship on the use of intervention trial evidence to inform chronic disease prevention guidelines and policies.