Please support European Obesity Day
European Obesity Day (EOD) takes place this coming Saturday, 21 May, and is aimed at raising awareness and increasing knowledge about obesity and the many other diseases on which it impacts.
EOD is a major annual initiative for the European Association for the Study of Obesity (EASO) and so would like to ask you to support the activities by joining in the conversation on social media. It will help us to reach more of the policymakers, politicians, healthcare professionals, patients and the media who we are targeting with important messages about the need to take obesity more seriously.
There are several ways you can show your support:
Like the European Obesity Facebook Page
Follow EOD on Twitter @EOD2016
Join the conversations on twitter using the hashtag #EOD2016
Pledge your support on the European Obesity Day website
Visit the EOD website to see what we have been doing
Encourage your friends and colleagues to support us too
In line with the Action for a Healthier Future theme for EOD 2016, we hope we can count on your support.
Nevertheless, epidemiologists (and folks in health promotion) appear to like the notion that there is such a weight (at least at the population level), and often define it as the weight (or rather BMI level) where people have the longest life-expectancy.
Readers of this literature may have noticed that the BMI level associated with the lowest mortality has been creeping up.
Case in point, a new study by Shoaib Afzal and colleagues from Denmark, published in JAMA, that looks at the relationship between BMI and mortality in three distinct populations based cohorts.
The cohorts are from the same general population enrolled at different times: the Copenhagen City Heart Study in 1976-1978 (n = 13 704) and 1991-1994 (n = 9482) and the Copenhagen General Population Study in 2003-2013 (n = 97 362). All participants were followed up to November 2014, emigration, or death, whichever came first.
The key finding of this study is that over the various studies, there was a 3.3 unit increase in BMI associated with the lowest mortality when comparing the 1976-1978 cohort with that recruited in 2003-2013.
Thus, The BMI value that was associated with the lowest all-cause mortality was 23.7 in the 1976-1978 cohort, 24.6 in the 1991-1994 cohort, and 27.0 in the 2003-2013 cohort.
Similarly, the corresponding BMI estimates for cardiovascular mortality were 23.2, 24.0, and 26.4, respectively, and for other mortality, 24.1, 26.8, and 27.8, respectively.
At a population level, these shifts are anything but spectacular!
After all, a 3.3 unit increase in BMI for someone who is 5’7″ (1.7 m) is just over 20 lbs (~10 Kg).
In plain language, this means that to have the same life expectancy today, of someone back in the late 70s, you’d actually have to be about 20 lbs heavier.
While I am sure that these data will be welcomed by those who would argue that the whole obesity epidemic thing is overrated, I think that the data are indeed interesting for another reason.
Namely, they should prompt speculation about why heavier people are living longer today than before.
There are two general possible explanations for this:
For one these changes may be the result of a general improvement in health status of Danes related to decreased smoking, increased physical activity or changes in social determinants of health (e.g. work hours).
On the other hand, as the authors argue, this secular trend may be that improved treatment for cardiovascular risk factors or complicating diseases, which has indeed reduced mortality in all weight classes, may have had even greater beneficial effects in people with a higher BMI. Thus, obese individuals may have had a higher selective decrease in mortality.
There is in fact no doubt that medical management of problems directly linked to obesity including diabetes, hypertension and dyslipidemia have dramatically improved over the past decades.
Thus, it appears that the notion of “healthy” weight is a shifting target and that changes in lifestyle and medical management may have more than compensated for an almost 20 lb weight increase in the population.
This is all the more reason that the current BMI cutoffs and weight-centric management of obesity both at a population and individual level may need to be revisited or at least tempered with measures of health that go beyond just numbers on the scale.
As this year’s Congress President, together with World Obesity Federation President Dr. Walmir Coutinho, it will be our pleasure to welcome delegates from around the world to what I am certain will be a most exciting and memorable event in one of the world’s most beautiful and livable cities.
The program committee, under the excellent leadership of Dr. Paul Trayhurn, has assembled a broad and stimulating program featuring the latest in obesity research ranging from basic science to prevention and management.
I can also attest to the fact that the committed staff both at the World Obesity Federation and the Canadian Obesity Network have put in countless hours to ensure that delegates have a smooth and stimulating conference.
The scientific program is divided into six tracks:
Track 1: From genes to cells
- For example: genetics, metagenomics, epigenetics, regulation of mRNA and non–coding RNA, inflammation, lipids, mitochondria and cellular organelles, stem cells, signal transduction, white, brite and brown adipocytes
Track 2: From cells to integrative biology
- For example: neurobiology, appetite and feeding, energy balance, thermogenesis, inflammation and immunity, adipokines, hormones, circadian rhythms, crosstalk, nutrient sensing, signal transduction, tissue plasticity, fetal programming, metabolism, gut microbiome
Track 3: Determinants, assessments and consequences
- For example: assessment and measurement issues, nutrition, physical activity, modifiable risk behaviours, sleep, DoHAD, gut microbiome, Healthy obese, gender differences, biomarkers, body composition, fat distribution, diabetes, cancer, NAFLD, OSA, cardiovascular disease, osteoarthritis, mental health, stigma
Track 4: Clinical management
- For example: diet, exercise, behaviour therapies, psychology, sleep, VLEDs, pharmacotherapy, multidisciplinary therapy, bariatric surgery, new devices, e-technology, biomarkers, cost effectiveness, health services delivery, equity, personalised medicine
Track 5: Populations and population health
- For example: equity, pre natal and early nutrition, epidemiology, inequalities, marketing, workplace, school, role of industry, social determinants, population assessments, regional and ethnic differences, built environment, food environment, economics
Track 6: Actions, interventions and policies
- For example: health promotion, primary prevention, interventions in different settings, health systems and services, e-technology, marketing, economics (pricing, taxation, distribution, subsidy), environmental issues, government actions, stakeholder and industry issues, ethical issues
I look forward to welcoming my friends and colleagues from around the world to what will be a very busy couple of days.
For more information on the International Congress on Obesity click here
For more information on the World Obesity Federation click here
For more information on the Canadian Obesity Network click here
There are now more overweight than underweight people in the world today and there is little hope that there will be any noticeable reduction in this trend till 2025.
That essentially is the key message from a “landmark” paper with data from almost 20 million people (and a similar number of authors) from around the world published in The Lancet.
The researchers looked at data from 1698 population-based data sources from 200 countries for obesity prevalence data between 1975 and 2014.
The paper has wonderful maps and graphics that I am sure will find their way into many presentations on obesity (including mine) to demonstrate both the magnitude and ubiquity of the problem (not to say that underweight still remains a substantial problem in many parts of the world with problems at both ends of the weight spectrum often co-existing within the same countries).
Most alarmingly, as the authors point out, is the trend for severe obesity which will soon affect as many as 6-9% of the population in some high- and middle-income countries.
According to the authors,
“Even anti-hypertensive drugs, statins, and glucose-lowering drugs will not be able to fully address the hazards of such high BMI levels, and bariatric surgery might be the most effective intervention for weight loss and disease prevention and remission.”
Now may may well be true but it is also highly unrealistic.
At the rates that bariatric surgery is currently accessible in most countries, it will only take a 100 years (or more) to treat everyone who already meets the criteria today.
What we really need are better medical treatments that are effective, safe and scaleable (in the same manner that we have scaled the use of anti-hypertensive drugs, statins and glucose-lowering drugs to address hypertension, dyslipidemia or diabetes, respectively).
Better obesity treatments will be desperately needed while we wait for population interventions to hopefully begin reducing obesity rates by 2025.
San Diego, CA
While poor research methodology, flawed statistical analyses and overstating of findings is by no means particular to obesity research, the wide public interest in the topic of obesity (causes, prevention, treatments) means that flawed outcomes from flawed studies get transmitted to a much larger audience of individuals with a keen interest in this topic.
Thus, the danger of flawed research contributing to widely held misconceptions about obesity can directly lead to poor public policy and ineffective interventions that perhaps have a much broader impact that in other fields of health research.
Thus, it is admirable, that the latest issue of OBESITY features three articles on issues related to the quality of research in this field, highlighting some of the most common and pervasive methodological shortcomings of much of the work.
Thus, for e.g. a paper by Brandon George and colleagues list the 10 most common errors and problems in the statistical analysis, design, interpretation, and reporting of obesity research.
These include, in no particular order, issues related to
1) misinterpretation of statistical significance,
2) inappropriate testing against baseline values,
3) excessive and undisclosed multiple testing and “P-value hacking,”
4) mishandling of clustering in cluster randomized trials,
5) misconceptions about nonparametric tests,
6) mishandling of missing data,
7) miscalculation of effect sizes,
8) ignoring regression to the mean,
9) ignoring confirmation bias, and
10) insufficient statistical reporting.
The authors go on to explain each of these errors, citing specific examples from the literature on each.
Most importantly, they also discuss ways to identify such errors and (even better) minimise or avoid them.
As most of these problems are related to statistical handling of the data, the authors passionately argue for the inclusion or at least consultation of statisticians in the both the research and reporting stages of the scientific process, to hopefully produce higher quality, more valid, and more reproducible results.