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!
And finally, to end this miniseries on the arguments I often hear against calling obesity, is the objection based on the idea that there are simply too many people living with obesity to apply the label “disease” to. Doing so, would mean that over 7 million Canadians would wake up to find themselves living with a disease.
Related to this argument, I also often encounter the argument, that calling obesity a disease would turn these 7,000,000 Canadians into “patients” thereby completely overwhelming our healthcare system that would now be called about to provide treatments to all these people. I hear from payers and policy makers that providing treatments for obesity as a disease is simply not practical because of the number of people who have it.
As I think about it, both arguments are rubbish.
Firstly, the definition of disease has nothing to do with how many people are affected. Thus, I have never heard anyone say that we need to stop calling diabetes a disease because it affects 6 million Canadians or we need to stop calling depression a disease because 2.5 million Canadians will be affected during the course of their lives.
No one would ever suggest we stop calling the flu a disease just because it affects millions of Canadians leading to 12,200 hospitalizations and 3,500 deaths in Canada each year.
So arguing that we must not call obesity a disease because that would be declaring far too many people as “diseased”, is simply irrelevant.
Even if a disease affects 100% of the population causing important health problems and complications, we’d still be calling it a disease.
As for overwhelming the healthcare system – I would say obesity is costing the health care system whether you call it a disease or not. We will still have to pay for all the health issues directly related to people having obesity – from diabetes to heart disease to joint replacements to cancers. It’s already costing billions of healthcare dollars. Except that we are now spending those dollars on the complications rather than on preventing and treating obesity itself.
Again, if there was any other “disease” threatening to overwhelm the healthcare system, our response would certainly not be to simply stop calling it a “disease” – that would make no sense at all.
This concludes my miniseries on arguments I often hear against calling obesity a disease (there are some I hear less often).
Next week, I will turn to arguments that support the idea of calling obesity a disease – so stay tuned.
Now, an analysis from a large randomised controlled trial of smoking cessation by Charles Courtemanche and colleagues published for the National Bureau of Economic Research, that this weight gain may be more that most people think.
The researchers look at data from well over 5,000 participants in the Lung Health Study.
Using various statistical models, they conclude that the average weight gain is about 12 pounds, with the effect being greatest in the young, women and those starting out with a ‘normal’ weight.
They also calculate that the reduction in smoking over the past decades accounts for about 15% of the obesity epidemic.
From the longitudinal analysis they also conclude that the weight gain is not temporary nor likely reversible. If anything, the impact of smoking cessation on weight becomes greater as time passes.
Thus, while the authors remind us that the benefits of smoking cessation on health still by far outweigh any health detriments from a 12 lb weight gain.
Nevertheless, the data should remind us that smoking cessations efforts should always go hand in hand with efforts to prevent excessive weight gain.
While there would be no discernible benefit (or say even a small risk) for 90% of people with this chronic disease, the remaining 10% would not only experience a substantial weight loss (say 20% of their initial weight) but would also reap the benefits of the concomitant improvements in health and well-being.
Now imagine that in clinical practice, finding out for whom this treatment works and for whom it doesn’t is simply a matter of trying the treatment for a few weeks – if it works, great – if it doesn’t, well then you’re probably among the 90% for whom the treatment does not work – you simply discontinue the treatment.
The problem is, that even if such a treatment were to be developed, it would never find its way to market or into guideline recommendations.
The math is simple.
If you take 100 people each weighing 100 kg of whom only 10 will experience a 20 kg weight loss, the average weight loss for the group would be a rather modest -2 kg. No regulator would approve such a treatment.
Health economists will happily calculate that the benefits of a 2 kg weight loss do not warrant the cost.
Others may point to the side-effects (experienced even by many of the 90% who do not lose weight) and argue that the “risk/benefit” ratio for this treatment would speak against its use.
Payers would use these arguments to deny payment (even if the treatment does somehow find its way to market).
The only people who stand to lose are the 10% for whom this may well be the treatment that they’ve waited for all their life – a treatment that can reduce their morbidity and greatly improve their quality of life.
While 10% may not sound like a big number, applied to Canadians living with obesity, there would in fact be 700,000 Canadians who would potentially stand to benefit from this treatment (in the US the number would be around 8 million).
Unfortunately, these 700,000 Canadians will probably never see this treatment.
Imagine any other situation, where you potentially had a treatment that would significantly reduce the pain and suffering for 700,000 Canadians.
Now, imagine if this treatment were denied to them simply because the treatment does not work for “everyone” (or even “most”) people living with this condition.
I do fully appreciate the statistical and methodological issues with “responder analyses” – the loss of statistical power, the challenges for trial design, the non-randomized nature of the response, regression to the mean, arbitrary definition of “response” (especially for continuous variables), and more.
These are problems that are recognized and discussed – but so far, this discussion has not led to practical solutions in the clinical trial world (which is often remarkably different from what happens in actual clinical practice).
A logical approach would be to first to screen people for response to enrich the final study population with people for whom the treatment may actually work.
Additional trial design elements could include cross over designs, starting and stopping the treatment (in a blinded fashion if possible).
But the most important step is one of ideology – trialists (and regulators) must ask the question, how do we bring a treatment that only works for 10% of people with the disease (and we don’t know who these are without trying) to the 700,000 Canadians who stand to benefit.
Currently, the ideology appears to be focussed on keeping treatments that don’t work for 90% of patients off the market.
I could say the same for “experts” who belittle the potential benefits of current obesity treatments – by averaging the benefits across all participants (including everyone for whom the treatment does not work), we can ensure that no effective treatments will ever find their way to market.
Incidentally, this issue applies to all types of treatment.
Take for example exercise for weight loss – the overwhelming evidence is that average sustained weight loss with exercise is perhaps 1 or 2 kg at best. Yet, there are 1,000s of patients who will attest to the fact that exercise is what helped them lose weight and keep it off.
However, if anyone tried to get regulatory approval for exercise as a treatment for obesity, regulators would probably simply laugh them out of the room – that’s how ineffective exercise is ON AVERAGE! (the same could be said for most dietary treatments for obesity)
The notion that we will one day find a single treatment that works for every (or even most) patients with obesity is perhaps far too optimistic.
On the other hand, the notion that certain subsets of patients with obesity will benefit from some treatments (while others won’t) only reflects the complex and heterogenous nature of this condition.
According to the Alberta economic dashboard, in October 2015, Alberta’s seasonally adjusted unemployment rate was 6.6%, up from the 4.4% rate a year earlier and from last month’s 6.5% rate. The youth unemployment rate was 11.6%, up from last year’s 9.0% rate, while male unemployment increased precipitously from 3.6% last October to 7.3% this year.
As no one seems to be expecting a rosier future for this industry, it may well be that many who lost their jobs in the wake of mass oil patch layoffs, will find the coming months (not to mention the festive season) both economically and emotionally challenging.
According to this report, suicide rates from January to June in Alberta this year are up 30% compared to the same period in 2014.
One challenge that may escape notice is the fact that this situation may also lead to significant weight gain in those affected.
Depression, anxiety, food insecurity, insomnia and simply being unable to afford healthy food are all important risk factors for weight gain.
Indeed it is hard to imagine how going from a high-paying job to being unemployed with little immediate hope of recovery will affect families.
Maintaining a positive spirit – necessary for eating healthy, engaging in physical activity and healthy sleep – will clearly be a challenge.
So while it may take some time for “official” statistics regarding overweight and obesity to change, I would not be surprised to see numbers go up.
Unfortunately, when this happens, people putting on the extra pounds will likely face the same blame and shame for “making poor choices” as everyone else who is struggling with this problem faces everyday.
As medical professionals, we need to acknowledge that unemployment and the worries that come with it can make our patients more susceptible to weight gain – let us not miss the opportunity for prevention.
If you’ve been affected by the economic downturn and this is affecting your health, please feel free to leave a comment.