Anyone who has closely followed my writings on this topic will know by now that health for a given individual cannot be measured by simply stepping on a scale (or for that matter using a measuring tape).
There are indeed individuals who appear rather healthy even at BMI levels considered to be well into the obesity range (just how many depends on your definition of “healthy”).
In an article and commentary that appears in the American Journal of Epidemiology, Juan Pablo Rey-López and colleagues from the School for Policy Studies, University of Bristol,UK, argue that the notion of “metabolically healthy obesity” (MHO), if anything is distracting and even counterproductive to public health efforts to prevent obesity.
They argue that,
“the MHO phenotype is not benign and as such has very limited relevance as a public health target.”
Throughout the article, the authors indeed make the oft-heard arguments for a population wide approach based on the notion that even a small left-shift in the weight distribution curve (as popularized by Geoffrey Rose) can have a potentially large influence on the population burden of excess weight.
This is not something anyone would argue with – at least at a population level and when the issue is prevention.
Unfortunately, Rey-López and colleagues then fall into the trap of pooh-poohing the research efforts around better trying to understand exactly why there is such a variation in how excess weight may (or may not) affect an individual’s health.
“More efforts must be allocated to reducing the distal and actual causal agents that lead to weight gain, instead of the current disproportionate scientific interest in the biological processes that explain the heterogeneity of obesity.”
Furthermore, they argue against further investments into obesity treatments:
“Nevertheless, it should be openly recognized that further investments in this predominantly individual approach will not reverse the obesity epidemic, because 1) medical therapies or dramatic lifestyle changes do not modify the distal causes of obesity (i.e., modern processed food and the built environment) and 2) individualized lifestyle modifications are commonly unsuccessful and inaccessible.“
The two facts that are largely ignored in this discussion are 1) that efforts at prevention (no matter how effective) are not helping the millions of people already living with this problem and 2) trying to find better treatments by learning more about the biology of this condition is exactly how we have found treatments for a host of other conditions ranging from diabetes to hypercholesterolemia and that these treatments have indeed allowed millions of people with these conditions to live productive and meaningful lives.
Personally, I find that the line of argument presented by the authors reeks of discrimination against people living with this problem. Thus, I cannot help but think that the authors consider people with obesity a “lost cause” not worthy of the investment into finding or providing better treatments.
Whether or not the discussions about MHO will help advance the field or not is certainly debatable.
Wether pitching prevention against treatment has the potential to actually harm people living with this problem is not.
Nevertheless, for what it is worth, a publication by Ruth Brown and colleagues from York University, Toronto, published in Obesity Research and Clinical Practice, suggests that people today may be more susceptible to obesity than just a few decades ago.
The study looks at self-reported dietary from 36,377 U.S. adults from the National Health and Nutrition Survey (NHANES) between 1971 and 2008 and physical activity frequency data from 14,419 adults between 1988 and 2006 (no activity data was available from earlier years).
Between 1971 and 2008, BMI, total caloric intake and carbohydrate intake increased 10-14%, and fat and protein intake decreased 5-9%.
Between 1988 and 2006, frequency of leisure time physical activity increased 47-120%.
However, for a given amount of caloric intake, macronutrient intake or leisure time physical activity, the predicted BMI was up to 2.3kg/m2 higher in 2006 that in 1988.
So unless there was some major systematic shift in what people were reporting (which seems somewhat unlikely) it is clear that factors other than diet and physical activity may be contributing to the increase in BMI over time – or in other words, it appears that people today, for the same caloric intake and physical activity, are more likely to have a higher BMI than people living a few decades ago.
There are of course several plausible biological explanations for these findings including epigenetics, obesogenic environmental toxins, alterations in gut microbiota to name a few.
If nothing else, these data support the notion that there is more to the obesity epidemic than just eating too much and not moving enough.
For readers, who like showing images that demonstrate just how increasingly prevalent obesity is across the US, here are the 2014 obesity maps released by the US Centre for Disease Control this week.
Not that much new (unless you want to quibble about a couple of percent points here or there) – the situation is bad, with no sign of getting any better (no surprise here).
Here are the basic facts:
- No state had a prevalence of obesity less than 20%.
- 5 states and the District of Columbia had a prevalence of obesity between 20% and <25%.
- 23 states, Guam and Puerto Rico had a prevalence of obesity between 25% and <30%.
- 19 states had a prevalence of obesity between 30% and <35%.
- 3 states (Arkansas, Mississippi and West Virginia) had a prevalence of obesity of 35% or greater.
- The Midwest had the highest prevalence of obesity (30.7%), followed by the South (30.6%), the Northeast (27.3%), and the West (25.7%).
What else can one say?
Yesterday, I suggested that using a cost-saving argument to justify treatments for obesity reeks of discrimination. I argued that even if obesity treatment costs the system money, it needs to be delivered in the same way that we deliver treatments for other conditions – not because they save money, but because that’s what people living with those conditions deserve.
But the “cost-saving” argument is not just used to justify treatment for obesity – it is also regularly and widely used to justify spending money on obesity prevention. The usual line of argumentation is that x dollars spent on obesity prevention will save y times x dollars in healthcare spending, which is why we need to prevent obesity.
This is nonsense. We should be preventing obesity whether or not it saves money for the healthcare system, simply because obesity (defined here as excess weight that actually causes health problems) negatively impacts health and well-being. If this costs money, so be it.
Obviously, no one is asking anyone to simply pay for everything (prevention or treatment) just because it is the right thing to do, no matter the cost.
In real life cost does matter and there is a fiscal responsibility to spend money on things that are effective and deliver real benefits – but let us not wander into weighing one disease against another in making that decision.
And most certainly the question of “fault and responsibility” leads to a very slippery slope, given that so much of what affects our health (from infections to cancer, from accidents to chronic diseases) is often avoidable.
The question really boils down to whether or not there are effective ways to prevent obesity – if there are, they need to be funded, whether they save money or not.
Readers may be aware of the “Resource Dilution Hypothesis”, which postulates that there is a dilution of familial resources available to children in large families, and a concentration of such resources in small ones.
This “dilution” effect could not only affect material factors (including food, participation in organized sports, higher education, etc.) but also emotional factors (including parents undivided attention, time, interaction, etc.).
While the importance of this “dilution” effect remains hotly debated, at face value, it sounds plausible.
Indeed, there is no doubt that in most Western countries (with increasing standard of living), recent decades have seen a substantial reduction in the number of offspring per family, resulting in a significant increase in first and second-borns as part of the overall population.
Now, a large longitudinal study by José Derraik and colleagues, published in the Journal of Epidemiology and Community Health, reports that first-born women (in Sweden) tend to be significantly heavier (and slightly taller) than second-born women, leading the authors to suggest that decreasing family size may have something to do with the increase in obesity seen over time in that country.
Indeed, based on this study involving 13,406 pairs of sisters who were either first-born or second-born (n=26 812), the first-born were about 2.4% heavier than their second-born sisters with a 30-40% greater chance of having overweight or obesity.
While this difference may seem rather subtle, at a population level, over generations, such effects can well result in substantial shifts in the population BMI, as a greater proportion of people are first-born. (if every family had 5 children, 20% of kids would be a first-born, If every family has 2 children, 50% of kids would be a first-born, if every family had only 1 kid, 100% of kids would be a first-born)
As interesting as this idea may seem, there are several issues with this type of analysis, which may well be confounded by all kinds of issues and can hardly prove causality. Nevertheless, a similar finding has been reported in male first-borns and the hypothesis certainly has significant face value.
Paradoxically, however, although overall family sizes have decreased, people in lower socioeconomic strata, who tend to have more kids, also tend to have the highest obesity rates. The obvious explanation for this would perhaps also implicate the “resource dilution hypothesis”, as more kids means less money for food, resulting in more (cheaper) caloric-dense processed foods and greater food insecurity.
Accordingly, I would predict that there may well be a “U” or “J” shaped relationship between family size and obesity in the offspring – if anyone has data on this, I’d certainly be interested.