On June 26 Canada released the Canadian 24 Hour Movement Guidelines for Children and Youth. These guidelines call for at least 60 minutes per day of moderate to vigorous physical activity, no more than two hours a day of recreational screen time, limited sitting for extended periods and at least 9-11 hours of sleep per night for children 5-13 years, and 8-10 hours for those aged 14-17 years. They were developed by the Canadian Society for Exercise Physiology, the Conference Board of Canada, HALO-CHEO, ParticipACTION and the Public Health Agency of Canada, with input from research experts and stakeholders across Canada and around the world.
The process was informed by 9 peer-reviewed publications, all available for free via the journal of Applied Physiology, Nutrition and Metabolism.
Three papers of particular relevance to sedentary behaviour:
New meta-analysis: the prospective relationship between childhood sedentary behaviour and biomedical health indicators
A new paper by van Ekris et al. examines the relationship between childhood sedentary behaviour and health indicators later in life. From the abstract:
Evidence for adverse health effects of excessive sedentary behaviour in children is predominantly based on cross-sectional studies, measuring TV viewing as proxy for sedentary behaviour. This systematic review and meta-analysis summarizes the evidence on the prospective relationshipbetween childhood sedentary behaviour and biomedical health indicators, overall and stratified by type of sedentary behaviour (TV viewing, computer use/games, screen time and objective sedentary time). PubMed, EMBASE, PsycINFO and Cochrane were systematically searched till January 2015. Methodological quality of all included studies was scored, and a best evidence synthesis was applied. We included 109 studies of which 19 were of high quality. We found moderate-to-strong evidence for a relationship of overall sedentary time with some anthropometrics (overweight/obesity, weight-for-height), one cardiometabolic biomarker (HDL-cholesterol) and some fitness indicators (fitness, being unfit). For other health indicators, we found no convincing evidence because of inconsistent or non-significant findings. The evidence varied by type ofsedentary behaviour. The meta-analysis indicated that each additional baseline hour of TV viewing (β = 0.01, 95%CI = [-0.002; 0.02]) or computer use (β = 0.00, 95%CI = [-0.004; 0.01]) per day was not significantly related with BMI at follow-up. We conclude that the evidence for a prospectiverelationship between childhood sedentary behaviour and biomedical health is in general unconvincing.
The full study is available via Obesity Reviews.
In May 2014, representatives from 15 countries gathered in Toronto, Canada, for the Global Summit on Physical Activity of Children. Experts reviewed available information and assigned a grade for 9 indicators in national Physical Activity Report Cards. Australia received a grade of “D minus(–)” for sedentary behaviors, with only 29% of 5- to 17-year-olds meeting screen time recommendations. A smaller group from the Australian Report Card Research Working group conducted a study to further review available evidence about sedentary behaviour in children (available here).
They asked the following 3 questions:
Question 1: What are the main sedentary behaviors of children?
Sedentary behavior can occur in 4 areas of children’s lives—education/school/child care, transport, self-care/domestic chores, and leisure/play. For school-aged children, a main “occupation” is being a student and the majority of the school day is spent sitting. Homework also contributes to additional sitting time. Transport time is usually highly sedentary with children sitting in buses, trains and cars to get to and from school and other destinations. Sedentary self-care tasks include eating and some grooming. Leisure and play sedentary behaviors include reading from a book or an electronic screen. Sedentary behaviors are often further classified as being either based around an electronic screen or not.
Question 2: What are the potential mechanisms for sedentary behaviors to impact child health and development?
There are a number of ways by which sedentary behaviors may influence child health and development, including disrupted metabolism, limited neuromuscular activity, prolonged/awkward postures or repetitive motions, socioemotional experiences, cognitive experiences, and other mechanisms such as influencing sleep quality.
Question 3: What are the effects of different types of sedentary behaviors on child health and development?
Research suggests that sedentary behaviors impact child health and development including cardiometabolic, neuromuscular, and psychosocial implications. However, most of the research is about the effects of watching TV, and there has been less of a focus on the effects of total screen time, screens other than TV, non-screen sedentary behaviours, and total sedentary time.
The available research, while incomplete, is sufficiently convincing that sedentary behaviors are important for child health and development. Nations therefore need to balance children’s healthy and unhealthy sedentary behaivours in order to improve their sedentary behaviour grade in future report cards.
Leon Straker, Erin Kaye Howie, Dylan Paul Cliff, Melanie T. Davern, Lina Engelen, Sjaan R. Gomersall, Jenny Ziviani, Natasha K. Schranz, Tim Olds, Grant Ryan Tomkinson. Australia and Other Nations Are Failing to Meet Sedentary Behaviour Guidelines for Children: Implications and a Way Forward. JPAH 13:177 – 188, 2016.
Glasgow Caledonian University is currently hiring a Research Fellow to work in the area of physical activity and sedentary behaviour. From the website:
The School of Health and Life Sciences is looking to appoint a fixed term Research Fellow for 36 months to the Healthy Ageing and Active Living Research Group in the Institute for Applied Health Research. The post holder will contribute to the high quality and impact of the group’s research. We seek an outstanding individual with the right combination of research, numerate and public engagement skills to be part of our vibrant team. The Research Fellow will be embedded within the research team under direction from Prof Dawn Skelton and Prof Jo Booth to specifically work on our portfolio of research and develop new projects on promoting physical activity and reducing sedentary behaviour in later life.
For more details, please visit the Glasgow Caledonian University website.
From the journal PLOS ONE:
Sedentary behaviour is increasingly recognized as an important health risk, but comparable data across Europe are scarce. The objective of this study was to explore the prevalence and correlates of self-reported sitting time in adults across and within the 28 European Union Member States.
This study reports data from the Special Eurobarometer 412. In 2013, 27,919 randomly selected Europeans (approximately 1000 per Member State) were interviewed face-to-face. Sitting time on a usual day was self-reported and dichotomised into sitting less- and more than 7.5 hours per day. Uni- and multivariate odds ratios of sitting more than 7.5 hours per day were assessed by country and socio-demographic variables using binary logistic regression analyses. The analyses were stratified by country to study the socio-demographic correlates of sitting time within the different countries.
A total of 26,617 respondents were included in the analyses. Median sitting time was five hours per day. Across Europe, 18.5 percent of the respondents reported to sit more than 7.5 hours per day, with substantial variation between countries (ranging from 8.9 to 32.1 percent). In general, northern European countries reported more sitting than countries in the south of Europe. ‘Current occupation’ and ‘age when stopped education’ were found to be the strongest correlates of sitting time, both across Europe and within most Member States. Compared to manual workers, the odds ratio of sitting more than 7.5 hours per day was 5.00 for people with white collar occupations, 3.84 for students, and 3.65 for managers.
There is substantial variation in self-reported sitting time among European adults across countries as well as socio-demographic groups. While regular surveillance of (objectively measured) sedentary behaviour is needed, the results of this study provide entry points for developing targeted interventions aimed at highly sedentary populations, such as people with sedentary occupations.
The full article is available for free here.
An updated Cochrane Review has examined the impact of workplace interventions to reduce sitting. From the plain language summary, available via the Cochrane Library.
Why is the amount of time spent sitting at work important?
Physical inactivity at work, particularly sitting has increased in recent years. Long periods of sitting increase the risk for obesity, heart disease, and overall mortality. It is unclear whether interventions that aim to reduce sitting at workplaces are effective at reducing the amount of time spent sitting.
The purpose of this review
We wanted to find out the effects of interventions aimed at reducing sitting time at work. We searched the literature in various databases up to 2 June 2015.
What trials did the review find?
We found twenty studies with a total of 2174 participants from high income nations. Nine studies evaluated physical changes in the workplace, four evaluated changes in workplace policy, seven studies evaluated information and counselling interventions and one study evaluated both physical workplace changes and information and counselling components.
Effect of sit-stand desks
Sit-stand desks alone decreased workplace sitting with about half an hour to two hours per day. When combined with information and counselling sit-stand desks reduced sitting at work in the same range. Sit-stand desks also reduced total sitting time (both at work and outside work) and the duration of sitting episodes that last 30 minutes or longer.
Effect of active workstations
Treadmill desks combined with counselling reduced sitting time at work compared to no intervention. Pedalling workstations combined with information did not reduce sitting at work compared to information alone.
Effect of walking during breaks
The introduction of walking during breaks in two studies with 443 participants did not change sitting time.
Effect of information and counselling
In two studies counselling decreased sitting time with 28 minutes and in another study mindfulness training did not have any effect on sitting at work. There was no considerable increase in work engagement with counselling.
Computer prompting software did not reduce sitting time in two studies. In another study computer prompts reduced sitting time with 55 minutes compared to no intervention. One study found that prompts to stand reduced sitting 14 minutes more than prompts to step. Computer prompts did not change the number of sitting episodes that last 30 minutes or longer.
Interventions from multiple categories
When multiple categories of interventions were combined to decrease sitting, there was reduction in workplace sitting time at 12 weeks’ and six months’ follow-up but there was no considerable difference between intervention and control group at 12 months’ follow-up.
The quality of evidence was very low to low for most interventions mainly because studies were very poorly designed and because they had very few participants. We conclude that at present there is very low quality evidence that sit-stand desks can reduce sitting at work at the short term. There is no evidence for other types of interventions. We need research to assess the effectiveness of different types of interventions for decreasing sitting at workplaces in the long term.
Wishing you a healthy, active holiday season and New Year.
Best wishes from SBRN!
Recipe for a healthy day: how compositional data analysis can help us optimise our daily routine to be healthy.
Today’s post comes from Dr Sebastien Chastin at Glasgow Caledonian University.
What is the recipe for a healthy day?
This is the question we explore in our research article “Combined Effects of Time Spent in Physical Activity, Sedentary Behaviors and Sleep on Obesity and Cardio-Metabolic Health Markers: A Novel Compositional Data Analysis Approach” published by PLOS One. In this article, we argue that if we really want to know how much time we should spend; sleeping, sitting, standing, walking and exercising every day to be in good health, we have to adopt a compositional data paradigm. This is because, it is the only adequate mathematical representation of the pattern of time spent in different activities or behaviours throughout the day. In other words, one that takes into account the fact that time spent in one type of activity cannot be spent in another type of activity.
While developing this novel approach, initially just to overcome some technical issues with collinearity, we realised that it was more than just a new statistical technique. It actually provided an interesting unifying conceptual framework to study the impact and determinants of daily pattern of time use in an integrated and multidisciplinary way. In this blog piece, I would like to touch on some of these aspects.
It is helpful first to think about some analogous problems.
If I want to cook a tasty and healthy dish, nutritionists tell me that I have to combine in my recipe the right proportion of fat, carbohydrates, protein, vitamins, etc… and a good chef will tell me what ingredients to use and in what proportion. In the same way, to formulate an effective pill, pharmacologists combine active and inert compounds in the right proportions, ensuring that all ingredients are compatible and that their interactions do not alter or blunt the desired effect. Both my dish and the medical pills are fundamentally compositions. A composition is an entity of multiple non-overlapping parts which sum to a whole. Figure 1, shows different compositional representation of my dish and a medical pill, in graphical and mathematical terms. I apologise to nutritionists and pharmacologists if I did not get the number quite right to make these compositions actually healthy.
Similarly, our pattern of time use during the day is fundamentally a composition. For example we might describe the pattern of daily time use as
24 hour day = 8 hours (33.3%) sleep + 8 hours (33.3%) of work + 8 hours of leisure (33.3%)
Waking day = 2% Moderate to vigorous activity + 38% Light activity + 60% Sedentary behaviour
I am sure that you have, at least once, represented the pattern of daily time use with a pie chart as in figure 2. You might not have realised it but this is already compositional data analysis, but let’s see how we can take it further.
An interesting property of compositions is that their effect is determined by the proportion of the various basic ingredients that constitute them and not solely by the amount of one of these.
Surely, not! Let’s see how we can change the effect of my dish or pill. To make my drug more potent I need to absorb more of the active ingredient. To do this I can either take more pills of the same composition, or I can include more active ingredients in my pill, changing its composition. Similarly, I can eat less fat if I include less fat in my dish, but then its composition changed or I can eat less of the dish but I am still swallowing the same composition. In either case, the dose response depends on both the composition and the size.
This property becomes more important in the context of time use because to be healthy we can only change the composition of the day – we can’t make it any longer or shorter! In our paper we have actually shown that the composition of the day in terms of time spent in sleep, sedentary behaviour, light and moderate to vigorous activity is associated with adiposity and cardiometabolic markers. To be more active, I have to change the composition of my day. if I want to go to the gym and exercise I have to take time away from something else.
Conceptually, this is quite a departure from how we have usually considered time spent in physical activity, sleep or sedentary behaviour research. To date, we have conceptualised these as independent quantities of time and our reasoning and all the statistics we use to probe for evidence are based on this assumption. For example, we considered that health depends on the amount of time we spend exercising daily but did not address the fact that this time depends on the composition of the day. Our models and evidence rest on the underlying assumption that this time can be increased to infinity. Our current recipe for a healthy day is a minimum of daily 30 minutes of moderate to vigorous activity. This is roughly 2% of the time we have in a day. This recipe assumes that the remaining 98% of the day either has no impact on health or just the mirror opposite effect. This Manichaean concept would work if exercise was indeed the only ingredient of the day that impacts health.
However, we have more recently started to consider, that too much sitting might be bad for health, that sleep time is important for health, and that time spent in light activities might influence adiposity and glycaemic control. Since then, we have struggled to integrate and explain these within our current conceptual model of the day. This has led to some interesting controversies. A good example is contained in the article by Maher et al. 2014 published in PloS One and the comments it attracted . Some scientists claim that sitting has effects on health regardless of the amount of moderate to vigorous activity, while others respond that sitting time is just inactive time and that the associations reported are only due to sitting displacing physical activity. This will be familiar to you, and I have certainly heard the same arguments in numerous conferences. I found neither of these hypothesis satisfying. On one hand is it really reasonable to consider that the effect of sitting is independent when we know that time spent sitting and active are necessarily co-dependent and sitting necessarily displaces some active time? On the other, the dualist view activity/inactivity does not explain some of the lab results we have on sitting [2,3] and can’t account for the differences in effect we observed between sitting and light activity. Our field of research seems to be polarised in a dead lock as evidence seems to remain equivocal and flaunt by statistical difficulties such as collinearity.
This is why compositional data analysis is so attractive, it certainly enables us to overcome collinearity issues and to account in statistical models for time spent in all behaviours or categories of activity. But more importantly it offers a unifying way forward.
From a compositional stand point, the hypotheses above are not antithetic but complementary. Spending time sitting can have both specific health effects and displace active time thus contributing to the effects of inactivity. Our results clearly show this. The compositional approach does not invalidate or contradict any of our evidence to date; actually our results are consistent with it all. Instead it provides a sound theoretical framework and the practical statistical tools to integrate them so that we can move forward.
Let’s face it most of us struggle to fit in 2% of our time in exercise, so finding out how to optimise the rest of the day is of interest to a lot of people. Besides that, we cannot exercise all day, so why not act on the whole distribution of time to improve health. Compositional analysis can help us get to the recipe for healthy day.
We are currently developing resources, training material and workshops about compositional data analysis and we would like to hear from people who might be interested in these or better in helping and collaborating toward developing a larger open science project using compositional data analysis to formulate the recipe for a healthy day.
- Maher C, Olds T, Mire E, Katzmarzyk PT. Reconsidering the Sedentary Behaviour Paradigm. Johannsen D, editor. PLoS One. Public Library of Science; 2014;9: e86403. doi:10.1371/journal.pone.0086403
- Dunstan DW, Kingwell BA, Larsen R, Healy GN, Cerin E, Hamilton MT, et al. Breaking Up Prolonged Sitting Reduces Postprandial Glucose and Insulin Responses. Diabetes Care. 2012; doi: 10.2337/dc11–1931.
- Chastin SFM, Egerton T, Leask C, Stamatakis E. Meta-analysis of the relationship between breaks in sedentary behavior and cardiometabolic health. Obesity (Silver Spring). 2015;23: 1800–10. doi:10.1002/oby.21180
- Zeljko Pedisic. Measurement issues and poor adjustments for physical activity and sleep undermine sedentary behaviour research. Kinesiology. 2014;46: 135–146.
This post was originally published on Obesity Panacea.
Dr Ragnar Viir is looking for participants to complete an online survey looking at the way that sitting impacts muscle function.
From the survey:
Muscular activity, movement, keep us healthy. Excessive sitting is a risk factor for poor health and shorter life expectancy. The process starts from sitting per se – but what happen to muscles when we are sitting?
Here we explore whether the digital 3PPIUTT test (Three Position Personally Informative Upper Trapezius muscle Test) can be used to distinguish qualitative differences between standing, sitting and lying positions. Test results can enhance our understanding of how to recover from upright positions´ related muscular stress.
Method: Respondents are asked to investigate their own Upper Trapezius (UT) muscles in two ways.
1) Gently squeezing the muscle to form an opinion of muscle stiffness in sitting, standing and supine,
2) Pulling muscle, fixed by thumb and fingers´ pincer-like grip in frontal (to nose) direction alternately with pulling muscle in dorsal direction, forms opinion of muscle tension; again in three sitting, standing and supine positions.
Respondents should use thumb and fingers in a pincer-like grip and test left side muscle with right hand and right side muscle with left hand. Next page videos show location of Upper Trapezius (UT) muscle and using the thumb and fingers´ pincer-like grip to test UT muscle.
Subjective assessments of muscle stiffness and tension please mark on a scale of 1-5 where: 1 = Most relaxed and 5 = Most stiff / Most tensed.
By completing and submitting this survey you are providing consent for your results to be used for research purposes.
Tallinn Medical Research Ethics Committee (TMREC) has given acceptance nr 307 (application nr 1054, TMREC protocol nr 174) to Ragnar Viir Limited Partnership, principal investigator Dr. Ragnar Viir PhD
The survey can be found here.
Today’s post comes from Dr. Tarun Katapally. You can find more on Dr. Katapally at the bottom of this post.
We all seem to understand and experience the impact of weather on our movement patterns, yet most active living research is conducted without taking weather variation into account. In temperate climatic zones, and especially in Canada, we experience a wide variation in seasonal weather – not to mention adverse weather within seasons. Yet, in understanding the role of different contexts (i.e., urban design and neighbourhood built environment, school, home and recreational environment) in facilitating active living, weather seems to be ignored consistently.
It is true that we have no control over weather patterns. However, we do have the capacity to inform and influence policies that drive the environmental factors in our neighbourhoods, work places and schools. Individuals living in some neighbourhoods might have more access and amenities that may enable them to counter adverse weather and be active in all weather conditions. The same rationale applies to work places, schools or any other environmental context we are exposed to everyday. In informing policymakers, why aren’t we including weather variation in our analyses so that we can understand what physical and social environmental factors moderate the impact of adverse weather?
In Canada, time-stamped weather data are readily available through Environment Canada and this data could be easily linked with either accelerometry or self-report data. We appreciate that most accelerometry data are cross-sectional and hence, we have developed a methodology to link this cross-sectional data with weather data to study the influence urban design and built environment on children’s moderate to vigorous physical activity. This study has now been published in BMJ Open: bmjopen.bmj.com/content/5/11/e009045.full?keytype=ref&ijkey=3i5wwwyzlgy2cS2
Moreover, the article describing the methodology of the data linkage has itself been accepted for publication in the Canadian Journal of Public Health and will be available in early 2016. The methods used to capture weather variation and link weather data with accelerometry data could not only be replicated, but also modified or adapted. More importantly, researchers could easily adopt the overall approach of taking weather into account in active living research. We hope that weather variation, a perennial factor that interacts with all other environmental variables to influence active living, is not ignored in generating and translating knowledge to policymakers.
Dr. Katapally is a medical doctor trained in India and a population health policy researcher. He is currently a faculty member at the Johnson-Shoyama Graduate School of Public Policy that is based at the Universities of Regina and Saskatchewan. He is also an adjunct faculty member in the Department of Community Health and Epidemiology at the University of Saskatchewan. Dr. Katapally’s expertise is in the employment of advanced mixed-methods and complex analytical techniques to understand the influence of policy and policy-driven social and physical contexts on the influence of children’s physical activity and sedentary behaviour.