Every two years the Canadian Obesity Network holds its National Obesity Summit – the only national obesity meeting in Canada covering all aspects of obesity – from basic and population science to prevention and health promotion to clinical management and health policy.
Anyone who has been to one of the past four Summits has experienced the cross-disciplinary networking and breaking down of silos (the Network takes networking very seriously).
Of all the scientific meetings I go to around the world, none has quite the informal and personal feel of the Canadian Obesity Summit – despite all differences in interests and backgrounds, everyone who attends is part of the same community – working on different pieces of the puzzle that only makes sense when it all fits together in the end.
The 5th Canadian Obesity Summit will be held at the Banff Springs Hotel in Banff National Park, a UNESCO World Heritage Site, located in the heart of the Canadian Rockies (which in itself should make it worth attending the summit), April 25-29, 2017.
Yesterday, the call went out for abstracts and workshops – the latter an opportunity for a wide range of special interest groups to meet and discuss their findings (the last Summit featured over 20 separate workshops – perhaps a tad too many, which is why the program committee will be far more selective this time around).
So here is what the program committee is looking for:
- Basic science – cellular, molecular, physiological or neuronal related aspects of obesity
- Epidemiology – epidemiological techniques/methods to address obesity related questions in populations studies
- Prevention of obesity and health promotion interventions – research targeting different populations, settings, and intervention levels (e.g. community-based, school, workplace, health systems, and policy)
- Weight bias and weight-based discrimination – including prevalence studies as well as interventions to reduce weight bias and weight-based discrimination; both qualitative and quantitative studies
- Pregnancy and maternal health – studies across clinical, health services and population health themes
- Childhood and adolescent obesity – research conducted with children and or adolescents and reports on the correlates, causes and consequences of pediatric obesity as well as interventions for treatment and prevention.
- Obesity in adults and older adults – prevalence studies and interventions to address obesity in these populations
- Health services and policy research – reaserch addressing issues related to obesity management services which idenitfy the most effective ways to organize, manage, finance, and deliver high quality are, reduce medical errors or improve patient safety
- Bariatric surgery – issues that are relevant to metabolic or weight loss surgery
- Clinical management – clinical management of overweight and obesity across the life span (infants through to older adults) including interventions for prevention and treatment of obesity and weight-related comorbidities
- Rehabilitation – investigations that explore opportunities for engagement in meaningful and health-building occupations for people with obesity
- Diversity – studies that are relevant to diverse or underrepresented populations
- eHealth/mHealth – research that incorporates social media, internet and/or mobile devices in prevention and treatment
- Cancer – research relevant to obesity and cancer
…..and of course anything else related to obesity.
Deadline for submission is October 24, 2016
To submit an abstract or workshop – click here
For more information on the 5th Canadian Obesity Summit – click here
For sponsorship opportunities – click here
Looking forward to seeing you in Banff next year!
We live in a time where most of us complain about the lack of it. Thus, I often remind myself that our “fast-food culture” is more a time than a food problem.
Now a study by Viral Patel and colleagues, published in OBESITY, takes a detailed look at how US Americans spend their time according to different BMI categories.
The researchers analyse data from over 28,503 observations of individuals aged 22 to 70 from the American Time Use Survey, a continuous cross-sectional survey on time use in the USA.
In a statistical model that adjusted for various sociodemographic, geographic, and temporal characteristics, younger age; female sex; Asian race; higher levels of education; family income >$75 k; self-employment; and residence in the West or Northeast census regions were all associated with a lower BMI relative to reference categories whereas age 50 to 59 years; Black, Hispanic, or “other” race; and not being in the labor force were associated with a higher BMI.
That said, here are the differences in time use associated with higher BMI:
Although there were no substantial differences among BMI categories in time spent sleeping, overweight individuals experienced almost 20 fewer minutes of sleeplessness on weekends/holidays than individuals with normal weight. Furthermore, there was a U-shaped relationship between BMI and sleep duration such that BMI was lowest when sleep duration was approximately 8 h per day and increased as sleep duration became both shorter and longer. Less sleep on weekends and holidays (5 to 7 h) was also associated with higher BMI than 8 to 9 h or sleep.
There were also no major differences between BMI categories and the odds of participating in work or in the amount of time working. However, working 3-4 h on weekends/holidays was associated with the lowest BMI. Individuals with obesity were more likely to be working between 3:30 a.m. and 7:00 a.m. on weekdays than normal-BMI individuals, again perhaps cutting into restful sleep.
Individuals with obesity were less likely to participate in food and drink preparation than individuals with normal weight on weekdays but spent about the same amount of time eating or drinking as the reference category.
Interestingly, individuals with obesity were more likely than individuals with normal weight to participate in health-related self-care, and overweight individuals spent over 1 h more on weekdays than individuals with normal weight on health-related self-care and also spent an additional 15 min (almost double the time) on professional and personal care services.
While individuals with higher BMI were less likely to participate in sports, exercise, and recreation on weekdays and weekends/holidays compared with individuals with normal weight, those who did participate did not differ from individuals with normal weight in the amount of time spent participating. In contrast, overweight individuals were more likely to attend sports/recreation events during the week and spent an additional 47 min (almost 25% more) on this activity than individuals with normal weight.
Overall, there was a positive and generally linear association between time spent viewing television/movies and BMI, with individuals with obesity more likely to watch television almost all hours of the day during the week and weekends.
On weekends/holidays, individuals with obesity were more likely to participate in care for household children and household adults. It was also observed that individuals with obesity spent an additional 15 min on religious and spiritual activities on weekends/holidays, compared with normal-BMI individuals (who spent 116 min).
While these data are of interest and are largely consistent with the emerging data on the role of optimal sleep duration and the detrimental impact of sedentary activities like television viewing on body weight, we must remember that the data are cross-sectional in nature and cannot be interpreted to imply causality (as, unfortunately, the authors do throughout their discussion).
Also, no correction is made for increasing medical, mental, or functional limitations associated with increasing BMI levels, which may well substantially affect time use including sleep, work, participation in sports or work-related activities.
Thus, it is not exactly clear what lessons one can learn regarding possible interventions – it is one thing to describe behaviours – it is an entirely different thing to try and understand why those behaviours occur in the first place.
Thus, unfortunately, findings from these type of studies too often feed into the simplistic and stereotypical “obesity is a choice” narrative, which does little more than promote weight bias and discrimination.
One factor accounting for this may well be the lack of timely access to sleep testing.
Now, a study by Hirsch Allen and colleagues from the University of British Columbia Hospital Sleep Clinic, published in the Annals of the American Thoracic Society, examined the relationship between severity of sleep apnea and travel times to the clinic in 1275 patients referred for suspected sleep apnea.
After controlling for a number of confounders including gender, age, obesity and education, travel time was a significant predictor of OSA severity with each 10 minute increase in travel time associated with an apnea-hypopnea-index increase of 1.4 events per hour.
The most likely explanation for these findings is probably related to the fact that the more severe the symptoms, the more likely patients are to travel longer distances to undergo a sleep study.
Thus, travel distance may well be a significant barrier for many patients accounting for a large proportion of undiagnosed sleep apnea – at least for milder forms.
Given the often vast distances in Canada one can only wonder about just how much sleep apnea goes under diagnosed because of this issue.
Now a study by Robert Eckel and colleagues, published in Current Biology, illustrates how sleep deprivation and timing of meals can markedly alter insulin sensitivity.
Studies were conducted in 16 healthy young adults (8w) with normal BMI. Following a week of 9-hr-per-night sleep schedules, subjects were studied in a crossover counterbalanced design with 9-hr-per-night adequate sleep (9-hr) and 5-hr-per-night short sleep duration (5-hr) conditions lasting 5 days each, to simulate a 5-day work week. Sleep was restricted by delaying bedtime and advancing wake time by 2 hr each.
Energy balanced diets continued during baseline, whereas food intake was ad libitum during scheduled wakefulness of 5- and 9-hr conditions.
Overall, the simulated 5-day work week of 5-hr-per-night sleep together with an ad libitum diet resulted in a 20% decrease in oral and intravenous insulin sensitivity, which was compensated for by increased insulin secretion..
These changes persisted for up to 5 days after restoring 9-hr sleep opportunities.
The authors also showed that shifting circadian rhythm resulted in morning wakefulness and eating during the biological night, a factor that may promote weight gain over time.
Now, Christophe Varin and colleagues from the Centre National de la Recherche Scientifique, Paris, France, in a paper published in the Journal of Neuroscience describe how glucose regulates key neurones in the brain to induce sleepiness.
Their studies in mice focussed on sleep-active neurons located in the ventrolateral preoptic nucleus (VLPO), critical in the induction and maintenance of slow-wave sleep (SWS).
Using both in vivo and ex vivo patch clamp studies, the researchers show that a rise in extracellular glucose concentration in the VLPO can promote sleep by increasing the activity of sleep-promoting VLPO neurons.
As the researchers note,
“The extracellular glucose concentration monitors the gating of KATP channels of sleep-promoting neurons, highlighting that these neurons can adapt their excitability according to the extracellular energy status… Glucose-induced excitation of sleep-promoting VLPO neurons should therefore be involved in the drowsiness that one feels after a high-sugar meal. This novel mechanism regulating the activity of VLPO neurons reinforces the fundamental and intimate link between sleep and metabolism.”
Apart from helping unravel the biology of a phenomenon that every parent of a young child is well aware of, this research raises a number of interesting clinical questions.
Does overconsumption of high-sugar foods necessitate counteracting these effects with caffeine? Is this why sugar-sweetened pop generally contains caffeine (to not put you to sleep)?
Does this also explain the practice of eating a bedtime snack to fight insomnia?
And what does this mean for people with poorly controlled diabetes: do they need to drink more coffee than people without diabetes to get through their day? (not something I’ve heard of).