Monday, October 14, 2013

Quantum Mechanics and Dietary Intake - The Role of the Observer

Many of us this time of year are preparing for Canadian Thanksgiving - a holiday that's about giving thanks, family, friends, and of course...the food.

Ah yes, the turkey, the gravy, the stuffing and who could forget the pumpkin pie? As an aspiring obesity researcher I can't help but be fascinated by food intake patterns on holidays such as thanksgiving. These holidays are a good example of how people's dietary patterns are more closely related to the patterns of others than they are to the individual - the thanksgiving feast is common to millions, but it's not everyday we sit down and stuff ourselves full of turkey.

My fascination with food and holidays extends to our ability to measure peoples' food intake patterns - something this field is not terribly good at. In fact, a study just published in the Public Library of Science journal, PLOS One, by Edward Archer has identified some major flaws in the reporting of dietary intake in the US' National Health and Nutrition Examination Survey (NHANES)- the largest survey of the dietary habits of Americans. They reported that throughout the 39-year history of the NHANES the majority of respondents reported physiologically implausible dietary intakes - essentially, they were under-reporting how many calories they ate compared to how many they burn. Their conclusion? "The ability to estimate population trends in caloric intake and generate empirically supported public policy relevant to diet-health relationships from U.S. nutritional surveillance is extremely limited." It's thought that this effect is largely due to measurement error (the tools aren't good enough) and response bias - people who know they're being observed will change their behavior (see Hawthorne effect), or in this case, misreport their behavior.

While I may be disappointed with our measurement techniques for food intake I take solace in the fact that other researchers have it worse than I - namely the quantum physicists. Observer effects exist everywhere in science - altering the path of an electron by measuring it with a photon, the measurement of the momentum or position of a particle where improvement in one leads to reductions the other, and of course the observer-expectancy effects in clinical trials. Even when measuring the air pressure in a tire, some of the air must be let out by the observer! The quantum physicists, however, have to put with a nasty concept called the wave function collapse - this is where, simply put, the type of measurement being used on a particular system affects the outcome or end state of the system. Consider the quantum Zeno effect, where the very existence of a system relies upon it's being measured (or else otherwise decaying).

There just doesn't seem to be a good way around the overall systematic bias of measuring food intake - just like the physicists measuring the momentum and position of a particle, there are trade-offs in the different measurements of food intake. I'm not sure that we'll ever obtain a true record of the diet of a population (prospective or retrospective), and we may be forced to reduce measurement bias wherever possible, but ultimately accept its existence and its effect on our outcomes of interest. Research in this area may forever be required to add the phrase 'interpret with caution' to every paper or book published. I should note that some advancements have been made - recent tools involve taking pictures of food, sometimes with a smart phone, for assessment of serving size and composition. These tools have a long way to go, and they may introduce other forms of bias, but they seem promising for energy balance research.

However, even if measurement error is reduced to null, or an acceptably low level, there will always be physiological differences in the food we consume, digest, and store. Rob Dunn notes several of these in his recent article (Scientific American, September issue, 'Everything you know about calories is wrong'), including variation in: the 'appetites' of gut bacteria, rates of absorption of different foods and alteration in these rates due to co-consumption of other foods (think interaction effects), and proportion of digestion of many foods (nuts and legumes in particular). There are other factors that influence the number of calories we consume and store as well, such as the preparation of food which can partially digest some compounds making it easier for the body to digest them (and thus requiring less energy from the body to do so), and the immune response that some foods prompt in the body - something that has not been considered from an energy balance perspective.

I suppose all scientists - be they measuring the particles of the universe or those in a slice of a pizza - have to put up with observer effects. For many of us, learning to live and work with these effects is difficult to swallow - but alas the observer effects are here to stay, giving us something to chew on over the holidays.

Thursday, July 11, 2013

Childhood Obesity and Active Video Games- part of the problem or the solution?

This post is in response to an excellent round table discussion put together by the journal Games for Health, entitled: "Gaming, Adiposity, and Obesogenic Behaviors Among Children".

The experts at the round table did an excellent job discussing the relevant literature surrounding active video games (AVGs). I had a few concerns while reading the article that centre around the idea that we should use AVGs to reduce the prevalence of childhood obesity.

Some concerns/points of discussion:

1) There is much talk about getting children to play AVGs, although as Kristi Adamo points out, we don't understand why children play these games, let alone why they would replace other sedentary behaviors with them. The premise that the reasons for playing non-AVGs are the same as those for playing AVGs is flawed- I suspect that research will soon show that children play non-AVGs and AVGs for different reasons, and that it may be unreasonable to expect a direct replacement of non-AVGs for AVGs. Also, children who play non-AVGs may not be interested in playing AVGs - again, if they're playing them for different reasons. Monique Simons says this very well “To be effective at preventing overweight, children must enjoy playing active games and be willing to replace the non-active games with active ones.” Ralph Maddison suggests that non-AVGs could mistakenly be replaced with other sedentary behaviors (such as TV watching). While this is possible, it is also likely that children will simply add this type of video gaming to their repertoire of sedentary behaviors- leading to an additive effect, and thus more screen time.

2) The idea of inducing automatic shut-offs or other time-based controls on AVGs is interesting- for example, a child can only play the game for one hour at a time before the game shuts off for 12 hours, or a child must maintain a pre-determined activity level (assessed by heart rate or accelerometry) or the game will shut off. If we program AVGs with an automatic shut-off, or limited amount of time that the game can be played, there is the possibility that children will then turn to the seated video games. Further, if a child doesn't meet the activity intensity threshold required to keep an AVG running, this could have negative consequences. Such negative reinforcement may frustrate children and they may stop playing. Why not switch to the seated video game, where you can play for hours without being interrupted or by having to move around at a given intensity. After all, I'm playing video games, not exercising :) (my own personal jab at the AVG people - not reflective of the article)

3) By enhancing AVGs through deeper narratives and character development we would be encouraging children to spend more time indoors (active or otherwise). I suspect that games meant to simulate authentic activities will not lead to the same energy expenditure as the authentic activity itself - although I'm not aware of any study comparing energy expenditure between these two. Further, with deeper narratives and character development, as well as more detailed story line and plot, there may be less of a social aspect to these games. If the goal is to capitalize on what makes seated games so appealing (again, detailed story lines, narratives and character development) I think we can expect these games to become less, not more, social in nature. The benefit of this is that children are likely to play them longer by themselves (assuming point #2 is not an issue) and each individual child playing may achieve higher energy expenditure alone than in a group – each child would be playing instead of one playing and 3 sitting watching on the couch, as is the current model. The drawback of this is obviously the lack of social interaction with peers – video games can be a dangerous path to social isolation, and I for one don’t think that children need any more enticing to go down this path than they currently have.

4) The round table experts begin talking about the 'energy in' component of video games – in fact, some suggest that the link between video games and childhood obesity may have more to do with energy in (eating food) than energy out (exercise/activity). However, the majority of the solutions or areas for future direction for AVGs revolve around energy expenditure, save for a few examples of what might work for reducing food intake. If, as Amanda Staiano suggests, the driving factor for the link between video games and childhood obesity is increased caloric intake instead of the displacement of physical activity, why is there so much emphasis on making games more active? To the outsider, it would make more sense to do one of two things: the first would be to design games that promote less food intake (ie/ with less food advertisements)- however, there are still factors such as distraction mechanisms, habituation to food cues through non-food stimuli, associated learning to eat when gaming, increased stress response which may lead to over consumption and caloric compensation throughout the rest of the day. Suffice it say, this option doesn't seem realistic. In my opinion the best option to minimize the effect of screen time on childhood obesity is to reduce the amount of time kids spend in front of screens – period. TV, video games, computers, smart phones, tablets, etc. Kristi Adamo states an excellent point in her premise “if video games are a non-negotiable priority for children, [then] the ‘active’ gaming direction is logical”. Video games are not non-negotiable – like any behavior, moderation is key, and parents have a major role in demonstrating (through word and action) to their children that alternatives to screen time are feasible, enjoyable and salubrious.

So what then of AVGs? By using AVGs to reduce the prevalence of childhood obesity we may be missing the forest for the trees - video games, and screen-based sedentary behaviors in general, primarily through their associations with increased caloric intake, are a part of the obesogenic environment and thus play a role in the development of obesity. Using screens to reduce the prevalence of childhood obesity from a population perspective is not a viable or sustainable approach, no matter how "active" these screens are.

Sunday, May 26, 2013

Timely and accessible publication of research - is it too much to ask?

Recently, I was made aware of some the questionable tactics employed by the OMICS group, an open access publisher of over 200 journals which uses an 'author-pays' model. Traditional print journals rely on funding from subscriptions from individuals and institutions to support their publishing of scientific literature; publishing companies such as OMICS rely on authors' payments to publish their work. They claim to publish content within 21 days (as opposed to 6 months to 1 year, like most print journals).

The article which discusses this in much more detail is available to you if you have access to The Chronicle of Higher Education through your institution or professional association, or if you would like to subscribe to the journal for one ($76.00) or two ($132.00) years:

Stratford M (2012). 'Predadotry' Online Journals Lure Scholars who are Eager to Publish. The Chronicle of Higher Education, 3/9/2012 58(27): A1-A8. 

The article does raise some serious concerns about some open access publishing companies, and while I fully  support the publishing of scientific content in reputable, honestly peer-reviewed journals, there are some serious drawbacks to which I can understand as a young, budding researcher.

Step back for a second and ask yourself why these journals exist.

1) The publish or perish model of academic/scientific success does promote the advancement of science through competition; however, as with all competition, there are those who will look to 'cheat' to get ahead. 50 years ago, in the journal Science, Bernard Forscher from the Mayo Clinic in Rochester, Minnesota, published a story entitled Chaos in the Brickyard. This story describes the consequences of a publish or perish model of success in academia - with peer-reviewed publication as the currency of academia (the more you publish, the 'richer' you are), the emergence of author-pays model of publication should come as no surprise. By placing such an emphasis on competition, we have enabled the creation of the many bricks, not to mention brick-making factories.

2) The timeliness of scientific publication is of utmost importance, especially in my field of research (bio-medical sciences and population health). New research functions to inform clinicians and policy makers whose primary goal is to improve the health of millions of people. The amount of time required to publish in traditional journals can be down-right disappointing - I personally find it difficult reading 'new' papers with primary analyses, published say last week, where the data was collected anywhere from 1-3 years ago. In a field that is growing and expanding more rapidly than ever, this is unacceptable. I can empathize with scientists who are enticed by the quick turn around time of open access online journals, especially when operating in the publish or perish model.

3) Access - as I mentioned above, you will not be able to access the article that I am referring to without an individual or institutional subscription - frustrating, isn't it? The goal of scientific research should be to advance scientific knowledge and understanding, and while for the most part this is true, historically this did not refer solely to a select few in society with the right connections or available finances. The owner of OMICS group,
Mr. Srinu Babu Gedela started his open-access publishing company because he had difficulty getting access to academic literature when he was a Ph.D. student at Andhra University in India (Stratford, 2012).

If this timely and accessible method of publishing promotes the dilution of scientific integrity, then we are to blame. If this new world of open access, online publishing is the monster that it is often made out to be, then we are the ones who have created it. We have no one to blame but ourselves for creating an academic competition, timeliness and accessibility void - in a free market society, the void will always be filled.

Researchers absolutely need to be made aware of the publishing tactics and strategies, unethical or otherwise, of many of the new online journals - and I would applaud Mr. Stratford for bravely doing so. However, instead of trying to police journals and point fingers, I would suggest that we (the scientific community as whole) need to learn a few lessons from this. The reputable, peer-reviewed journals in which most researchers desire to publish should aim to become more timely and accessible in their publishing of scientific content. All the while, we as researchers should begin to move away from the publish or perish model of academic success, and towards one which values the impact and originality of publications, the quality of peer review, and the building of edifices instead of bricks.

Please feel free to discuss in the comments box- this is science, after all!

Sunday, April 21, 2013

Endocrinological Hypothesis and Obesity: Cause or Mechanism?

I wanted to comment on a well-written essay recently published in the British Medical Journal by Gary Taubes, entitled:

The science of obesity: what do we really know about what makes us fat?

From the essay: The history of obesity research is a history of two competing hypotheses. Gary Taubes argues that the wrong hypothesis won out and that it is this hypothesis, along with substandard science, that has exacerbated the obesity crisis and the related chronic diseases. If we are to make any progress, he says, we have to look again at what really makes us fat

This essay, in my view, has two components - the first is the comment on the competing hypotheses for the cause of obesity, while the second concerns the 'sub-standard' research that has been undertaken throughout the past half-century in obesity research, regardless of the hypothesis.

1) I feel as though Taubes presents a straw-man of the energy balance hypothesis of weight gain. While it may be true that die-hard supporters will cite the 1st Law of Thermodynamics until they are blue in the face, I expect that most of the researchers, clinicians and academics who spend their lives trying to better understand obesity also understand that this Law its limits with respect to weight gain. Clearly, an individual who lives with a chronic, mild negative energy balance will not waste away until they disappear. There are metabolic compensation mechanisms to prevent this from happening (reduction in basal metabolism). Finally, the circular logic presented by Taubes that weight gain is caused by overeating, and that we can tell if an individual is overeating if they have weight gain, does not refute this hypothesis - it only supports it.

2) Taubes refers to the endocrinological hypothesis of obesity - although this hypothesis is never explicitly stated. It goes like this: due to intrinsic physiological abnormalities (say, altered insulin response) a positive energy balance is the result, rather than a cause of the condition of obesity. Sure, so weight gain is the result of aberrant physiological processes. This seems to substitute one mystery for another - what causes these aberrations in physiology? I think that Taubes is confusing this endocrinological hypothesis for a cause, when it is actually a mechanism of the cause. The cause of obesity is now believed to be an obesogenic environment, one that promotes abnormalities in a number of physiological processes associated with weight gain. But these processes are not the cause of weight gain, they are the mechanism through which weight gain results.

3) Taubes also compares smoking and lung cancer with eating and obesity. As previously mentioned on my blog (Obesity Prevention: applying lessons from anti-tobacco campaigns), eating is compulsory, often beneficial, and complex, while tobacco is optional, not beneficial, and simple. A poor comparison, and one that obesity researchers, clinicians and academics alike should discontinue using, especially in published literature.

4) Kudos to Taubes for pointing out that the majority of the research used to inform policy and public health messages is not exactly top-notch. He is correct to suggest that we absolutely need better quality research - that we need to go beyond associations to assess causation. However, there are many ethical considerations that cannot be avoided in this type of research. Also, I would personally agree with Taubes that the money we will save in health care expenditures and personal health (and productivity, quality of life, etc) will outweigh the amount of money that we put in to research obesity, should we conduct the required studies. Convincing the powers that be of this long-term financial benefit is another matter.

Overall, an interesting piece. I don't expect people to abandon the energy balance hypothesis just yet. We do need better quality research - more longitudinal studies and intervention studies - and I think the field is headed in the right direction here, albeit slowly. Do we have to "look again at what really makes us fat", as Taubes suggests? I don't believe so...but have a look and decide for yourself :)


Thursday, February 21, 2013

Bisphenol A and Childhood Obesity - Evidence for Reverse Causality?

The paper: Association between Urinary Bisphenol A Concentration and Obesity Prevalence in Children and Adolescents
View the abstract
The author:  Leonardo Trasande
The Journal: Journal of the American Medical Association 2012

Bisphenol A

This is bisphenol A (BPA), a chemical that's been used the in manufacturing sector for about 50 years in United States to make everything from CDs to car parts (1). Recently, BPA has received a lot of exposure (pun intended) in the media because it is found in the linings of aluminum cans, and other food products.

In the US, 92.7% of people aged 6 and above have detectable levels of BPA in their urine (1); similar numbers can be seen here in Canada from the Canadian Health Measures Survey (2). The human health effects of BPA at low, environmentally relevant doses (meaning, what we would typically be exposed to in our environment) are currently unknown. Of course, giving mice an incredibly high dose acutely can cause the mice to develop health consequences...but this can be said about almost anything at a high enough dose (See Toxicology 101: the dose makes the poison).

Finally, the primary route of exposure to BPA is oral (by mouth), and the primary source of exposure is through food containing BPA (1). The half-life is estimated to be 4-43 hours, with 24 hours being the average for most people.

Absorption: Readily absorbed orally (primary route of exposure)
DistributionThere is little free BPA in blood, and there may be some storage in adipose tissue
Metabolism: It is rapidly metabolized by the liver (glucuronidation)
Excretion: Rapidly excreted through the urine

The paper:

This paper uses data from a sub-sample of  the 2003-2008 National Health and Nutrition Examination Survey (NHANES), including 2838 participants aged 6-19. They first looked at correlations between BPA and weight status (overweight/obese). Then they used multivariate logistic regression to predict the odds of being obese if you are in the 1st, 2nd, 3rd, or 4th quartile of BPA concentration (so, if you're in the highest category of BPA concentration, are you at an increased risk of being obese?). They also measured three other chemically similar, but non-food related phenols as an analysis of specificity - perhaps it's just phenols in general, or perhaps there is something specific about BPA. Despite being cross-sectional, the paper is written implying forward causality (referring to the mechanisms by which BPA can modify adipose tissues, examining BPA by quartile, not BMI...etc). It's not until the end of the discussion that there is a small paragraph explaining that reverse causality may play a role too.

The study measured BPA using a one-spot urine sample. The within-day and between-day variation of urinary BPA concentration is quite large, and it would have been ideal to collect more than one sample. Seasonality might even come into play here as well - do people eat higher amounts of BPA-containing foods at different times of the year (ie/ Christmas, summertime, etc). One randomized cross-over study showed that serving people canned soup for 5 days led to a 1221% increase in urinary BPA, as compared to soup prepared without canned ingredients (3). Needless to say, multiple measurements are absolutely needed.

In lieu of multiple measurements, the authors controlled for urinary creatinine, which sort allows them to control for a dilution factor - there are two parts to a concentration measurement, the solute and and solvent, or in this case BPA and water. If you drank more water that day your BPA concentration would be lower, but this is not related to the dose, but instead to the dilution. Good on em'.

Other covariates include:
-24 hour dietary recall - they were not able to control for physical activity levels of children, so they assumed everyone to have a high physical activity level for the evaluation of caloric intake as being 'normal' or 'excessive' - a more conservative approach on their part.
-daily hours of television watching (a known correlate of obesity in children)
-serum cotinine (a metabolite of cigarette smoke) - not sure how many 6 years olds are smoking, but fair enough.
-race/ethnicity, and
-socio-economic status (education level and income)

However, they did not control for frequency of consumption of BPA-containing foods. This is a very important consideration that I'll get into later.

Essentially, they found that you are more likely to be obese if you are in the 2nd, 3rd, or 4th quartile of urinary BPA concentration, as compared to the 1st quartile, in both unadjusted and fully adjusted models (see paper for logistic regression analysis). Also the prevalence of obesity increased with the increasing quartiles. It's not exactly linear (the 2nd and 3rd groups are switched), but the authors themselves suggest that this is because of the large variation in using a one-spot urine sample.

Finally, the other three chemically similar and non-food related phenols were not associated with obesity, and did not perturb the models when they were added as covariates, both individually and together.

Up to now, it's a pretty good study. Some things they probably should have controlled for, maybe taken a few more measurements, but overall it's not bad. The interpretation is where it gets weird...

From these results the authors suggest that there is something specific about BPA that is causing it to be related to obesity. Something that other chemically similar non-food related phenols do not have.

Essentially, this is the model that the authors have come up with. BPA is related to obesity, with increased urinary BPA probably causing obesity more than obesity is causing the increase in urinary BPA. Again, it isn't until the end of the discussion that the authors finally suggest the little arrow in this relationship, saying there is a chance that this could be reverse causal as well.

So, I took some of the premises that the authors used and came up with an alternate interpretation.

Let's assume that:
1) The primary source of BPA exposure is through food, as the authors claim in the introduction. This is supported by the literature.
2) Other chemically similar, but non-food related phenols are not related to obesity.

So what we're looking for are commonly consumed foods that contain high amounts of BPA. Low and behold, an analysis using 2005-2006 NHANES data (very similar to the data that the authors here are using) suggested that “Consumption of soda is significantly associated with higher urinary BPA” (4). There is much evidence to suggest that one of the primary sources of BPA exposure in children is sugar-sweetened beverages.

Making the assumption that increases urinary BPA are not causing children to consume more sugar-sweetened beverages, if we modify the model, we get this:

The question is, are sugar-sweetened beverages associated with childhood obesity? Here, the evidence has mounted over the past several decades. Sugar-sweetened beverage consumption patterns have paralleled the rise in obesity in the United States (5), and the results  from a large meta-analysis published in the British Medical Journal in 2013 suggest that sugar-sweetened beverage consumption (along with other free sugars) is a determinant of body weight (6). It's understood in the literature that this relationship is bi-directional. If you consumer more sugar-sweetened beverages, you're more likely to be obese, and obese children tend to consume more sugar-sweetened beverages. I would argue that it's most likely the former, and that the latter is the result of behavioral patterns that the formed during the process of the former...but I'll leave this for another post.

Thus, we have the following (note the reversed arrows in the box):

Where the unidirectional association between urinary BPA and sugar-sweetened beverages, along with the bidirectional association between sugar-sweetened beverages and obesity in children, combined with the finding that other chemically similar non-food related phenols are not associated with obesity, provides evidence to suggest that the relationship between BPA and obesity may be more about reverse causality than about forward causality.

BPA and Obesity:

Forward causality?

Reverse causality?

Or both?

What do you think?

Saturday, February 16, 2013


Thank you everyone for all of the wonderful comments. I'm glad you're enjoying the content.

To answer some questions, no I did not make this myself- I use Blogger, which is an open source tool for publishing blogs.

I didn't design it myself either...I'm using one of the many templates provided by Blogger.

Hope this answers your questions.


Wednesday, January 9, 2013

Rebuttle to Health at Every Size: Life expectancy is not the only measure of health

In the December 2012 issue of Discover, Dr. Linda Bacon provides a commentary which supports the HAES approach to healthy active living. Dr. Bacon cites data from the CDC (published in the Journal of the American Medical Association in 2005 and an independent report in 2011 - not referenced) which shows that people classified as overweight live longer than normal weight people, and that despite the increases in obesity in the US between 1970 and 2007,  life expectancy has increased from 70.8 to 77.9 years.

The claims that overweight people live longer than normal weight people, and that life expectancy has increased alongside obesity are important to recognize - indeed, overweight is associated with longevity in many other species in the animal kingdom, and there are metabolically healthy obese individuals.

While all of this true, Dr. Bacon does not mention the effects of overweight and obesity on morbidity or quality of life. A paper published by the American Journal of Preventative Medicine in 2010 suggests that quality-adjusted life years lost due to obesity doubled from 1993 to 2008. Overweight and mildly obese people may be expected to live longer than their normal weight counterparts, but time and time again the research literature has shown that obesity is associated with a number of chronic diseases. Chronic diseases have a tendency to reduce an individual's quality of life. 

A meta-analysis published last week in the Journal of the American Medical Association provides a similar conclusion- while grades 2 and 3 obesity (BMI= 35-40, and 40+) are associated with an increase in all-cause mortality (basically, death from everything), grade 1 obesity (BMI=30-35) was no different than normal weight, and overweight (BMI= 25-30) was associated with lower all-cause mortality. The authors note in their discussion a major limitation of this meta-analysis - not evaluating weight status according to a measure of morbidity.

As we continue to conduct research in this area it is important to remember that life expectancy is not the only measure of health. There is much more to both health, and obesity, than meets the eye.

Please comment!

Health at Every Size - a brief comment

Let's face facts. We've lost the war on obesity - Health at Every Size community (

The health at every size (HAES) approach to healthy active living is gaining steam. Indeed, there has been collateral damage in the war against obesity, such as food and weight preoccupation, eating disorders, stress, weight bias, etc. However, to say that we've lost the war on obesity is too simplistic. Firstly, the 'war' on obesity is not really a war at all. For instance, we can have a war on tobacco, which is a much simpler concept (see previous post on XX). But our stance against obesity is more of a conquest...a life-long struggle to gain minor but significant advancements against a multi-facted disease which affects millions of people. And to say that we've lost it? Look around our environment becomes more and more obesogenic, it seems as if the 'war' has barely begun.

Indeed, one could make the argument that we have lost the war on obesity treatment:

1) lifestyle interventions may not be successful (weight regain and the associated effects of this cycle)
2) drugs don't work so well - the only approved pharmaceutical drug for weight lost in Canada (Orlistat) can provide very modest weight lost- about 3kgs on average (Lancet, 2007:
3) bariatric surgeries, while to-date the most effective method of inducing weight loss in an individual, are costly and frequently include side effects and weight re-gain (again, as well as the associated effects).

But surely not the war on obesity prevention.

Prevention of obesity through lifestyle modification is arguably the most effective way to reduce chronic disease risk, both at the individual and population levels- we must not forget this.

It is said, albeit refutable, that the current generation of children may have a lower life expectancy that that of their parents, for reasons such as our increasingly obesogenic environment. We have an opportunity with our current generation of children to change things for them - to provide them with an environment that promotes health (yes, in all shapes and sizes). 

We may not finish this conquest, but if we don't, it's up to them.

The message that we've lost the war is not productive. The last thing we need people to do is give up on preventing obesity. While I appreciate many of the other messages from the HAES movement, the notion that we've lost the war on obesity needs to go.

Feel free to refute in the comments section!