Arya M. Sharma, MD

Yesterday, on my flight to San Diego to attend the 28th Annual Scientific Meeting of The Obesity Society, I had the opportunity to catch up on some of my reading.

Two recent articles in the Journal of the American Medical Association (JAMA) caught my attention, as they related to topics that I have recently blogged about.

The first article, by David Kindig and John Mullahy, examines the issue of determining the comparative cost-effectiveness of public health interventions. Readers may recall the recent WHO/OECD report that concluded that the cost-effectiveness of population interventions to prevent or manage obesity is probably so low, that such efforts are unlikely to yield returns within the next three to four decades.

In a similar vein, Kindig and Mullahy point out that rather limited evidence exists to guide public and private policy makers regarding investments to address the social, economic and cultural determinants of health behaviors, which would include tackling issues like the the physical and built environment.

This is why, the authors argue, that the significant funding that the US Government has proposed for comparative effectiveness research (CER) efforts should be dedicated to understanding the effectiveness of investments across broad determinants of health instead of focusing primarily within the health care domain alone (e.g. drug-drug comparisons).

Indeed, the authors warn that “without an adequate evidence base on which to judge the effectiveness of any particular strategy or intervention launched across such multiple sectors, the [Obama] childhood obesity initiative—as well as any other broad, multisectoral initiative on important population health problems—will succeed only by chance.”

The second article, by Helene Chmura Kraemer and Ellen Frank, discusses the evaluation of comparative treatment trials. As readers will recall, I recently pointed out that evaluating drug benefits and risks by merely looking at averages (as in the case of anti-obesity agents), may lead to treatments that are safe and effective for some people being removed from the market or not being made available because they are not safe or do not work for most people.

As Kraemer and Frank point out, “The evaluation of the comparative effectiveness of treatments should not depend on the statistical effect of treatments on individual measures of outcome (benefits or harms), but rather on the clinical effects of treatments (both benefits and harms) on individual patients who experience both benefits and harms. Such evaluation requires both statistical assessment of the rates of co-occurrence of such benefits and harms and clinical assessment of their combined clinical effects on patients.”

This means that rather than simply looking for p-values, randomized controlled trials should be geared towards looking at effect sizes at the individual patient level. Analyses should thus take into account the simultaneous benefits and harms experienced by each patient, much as a physician does when deciding between two or more treatment options.

For instance, while there is concern that certain antidepressants may increase the risk of suicidal ideation and suicidality in some adolescents, if only harm is considered, individual patients may be denied a potentially lifesaving treatment; in contrast, if only benefits are considered, a small subgroup of young patients may be exposed to serious harm.

Rather, individual benefits and risks can be better represented by the calculations effect sizes expressed as area under the receiver operating characteristic curve (AUC), success rate difference (SRD) (ie, rate difference for a favorable outcome), or number needed to benefit (NNB) or harm (NNH).

Using the theoretical example of a treatment that may have different benefits and harms in men than in women, a very different assessment of individual effect sizes emerges than when looking at overall p-values. Obviously, things may not always be as clear as in the chosen example where one has easily identifiable subgroups (i.e. men vs. women), but the key point here is that evaluation of the comparative effectiveness of treatments should not depend on the effects of treatments on group averages of outcome (benefits or harms), but rather on the overall clinical effects of treatments on individual patients, which requires the statistical assessment of the rates of co-occurrences of positive and negative outcomes and clinical assessment of their combined clinical effects on each patient.

Thus in the case of an obesity drug that results in effective weight loss in both men and women but may cause teratogenicity, a decision to mak the drug unavailable to both men and women, may deprive men of a safe and effective obesity treatment.

Similarly, abandoning an obesity drug that provides measurable benefits for individuals who respond with weight loss, just because it may potentially be harmful in individuals who fail to lose weight on this agent, would deprive “responders” from an effective treatment option.

I certainly concur with Kraemer and Frank, that as we move towards an era of “personalised” medicine, we need to focus more on individual effect sizes than blindly stare at statistical averages in the interpretation of clinical trials.

AMS
San Diego, CA

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Kindig D, & Mullahy J (2010). Comparative effectiveness–of what?: evaluating strategies to improve population health. JAMA : the journal of the American Medical Association, 304 (8), 901-2 PMID: 20736476

Kraemer HC, & Frank E (2010). Evaluation of comparative treatment trials: assessing clinical benefits and risks for patients, rather than statistical effects on measures. JAMA : the journal of the American Medical Association, 304 (6), 683-4 PMID: 20699462

Today at 23rd Scientific Meeting of the International Society of Hypertension, I attended a session dedicated to sodium and its impact on hypertension.

As some readers may know, I started my research career back in the mid-eighties studying the phenomenon of “salt sensitivity”, trying to answer the question why some people appear more “sensitive” to the blood pressure effect of salt, while others appear resistant.

This interest has taken me on a long voyage of research that included studying vascular reactivity, the sympathetic nervous system, the renin-angiotensin system, insulin resistance, genetics. and adipose tissue biology.

It turns out that the obesity epidemic has created a population that is increasingly salt sensitive, as hypertension associated with excess weight is largely driven by sodium retention and volume expansion.

There is certainly no doubt, that dietary sodium restriction results in blood pressure reduction, and, as outlined in a talk by Graham MacGregor (UK), there are ample examples of population-wide “interventions” that resulted in lower salt intake and lower blood pressure levels.

The challenge of course is how to reduce salt at a population level, when most of the food in our diet comes from processed foods. Simply banning the salt shaker from the table, has a relatively minor impact on overall salt intake.

As pointed out by Darwin Labarthe (USA), various organisations have called for mandatory restriction of salt in foods. He called on the food industry to voluntarily reduce sodium levels - something that has a precedent in countries like the UK, where many large manufacturers have stealthily reduced salt content of processed foods.

In fact, there are now several companies (perhaps most natabely Campbell’s), which have considerably reduced the amount of salt in their products over the last decade and have set even lower targets for themselves.

Initiatives like the Natioanal Salt Reduction Initiative in New York City, has the goal to reduce salt use in commonly eaten products by 20% in the next five years. There is also evidence that physicians are consistently recommending sodium reduction and that a growing number of consumers do in fact opt for low-salt foods.

In the afternoon, I attended a debate between Graham MacGregor and Simon Rabkin (Canada) on whether or not we have enough evidence to support government restrictions on salt use - Rabkin elegantly argues that, if we apply the standards of “evidence-based medicine” we must acknowledge that there is not a single randomised controlled trial that has ever documented the benefit of lowering blood pressure with salt restriction in “hard” endpoints.

While my own research has moved on and I believe that obesity is probably a far more pressing issue than the amount of salt we eat, I do think that limiting salt intake can help reduce population and individual blood pressure levels. Whether or not, population-wide efforts to limit salt intake will really translate into fewer heart attacks and stroke remains to be seen.

AMS
Vancouver, BC

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Our environment is full of man-made chemicals, the biological actions of which we rarely fully understand.

There is now considerable data showing that some of these chemicals may well have biological effects that can potentially change metabolism. These compounds are, therefore, sometimes referred to as “endocrine disrupting chemicals” (EDC) and can potentially promote weight gain and cause other metabolic problems including insulin resistance.

Because of their previous extensive usage as pesticides, their inherent structural stability, their persistence in body systems and their ability to concentrate in animals that are higher up on the food chain, many EDCs are currently present in human fat in relatively high levels.

A new study by Mai Elobeid and colleagues from the University of Alabama at Birmingham, just published in the International Journal of Environmental Research and Public Health, examines the relationship between selected organic pollutants and obesity in a representative sample of the US population (NHANES 1999-2002 Data).

In their analyses, the authors found consistent positive interaction between BMI and/or waist circumference with several of the EDCs including oxychlordane, p,p’ DDT, hpcdd.

As the authors point out, “In particular, these chemicals have been shown to disrupt major weight controlling hormones, such as thyroid hormones, estrogens, testosterone, corticosteroids, insulin, growth hormone, and leptin and to alter levels of, and sensitivity to, neurotransmitters (in particular dopamine, noradrenaline, and serotonin.”

While the authors acknowledge all of the caveats and care that must be taken in interpreting these type of associations, they note that their findings are certainly in line with the hypothesis that these chemicals may be plausible contributors to the obesity epidemic.

What this may mean in terms of prevention or obesity management remains even less clear. Nevertheless, there is no doubt that the list of factors that may underly the obesity epidemic is far longer than most people consider.

AMS
Salt Lake City, UT

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Elobeid MA, Brock DW, Allison DB, Padilla MA, & Ruden DM (2010). Endocrine Disruptors and Obesity: An Examination of Selected Persistent Organic Pollutants in the NHANES 1999-2002 Data. International journal of environmental research and public health, 7 (7), 2988-3005 PMID: 20717554

Readers, who recently followed my postings from the XI International Congress on Obesity in Stockholm Stockholm last week on FaceBook, will perhaps recall a brief note on a talk by Garry Egger, Australia, raising the question whether we may have stayed too long at the “sweet spot” of economic growth resulting in both the obesity epidemic and climate change?

Together with his Australian colleague Boyd Swinburn, Egger has written a short book called, Planet Obesity, in which the two authors further elaborate on this notion.

The basic tenet of the very readable short treatise is simply put the following: obesity and climate change are both the seemingly inevitable consequences of economic growth that focusses solely on maximising (rather than optimising) consumption.

In every example cited in the book, economic development is inadvertently accompanied by an increase in body weight (first in the rich, then in the poor), till in highly economically “developed” societies obesity assumes epidemic proportions.

Readers of these pages certainly do not need to be reminded of the pandemic nature of obesity now affecting rapidly developing countries like China and India.

To state the converse, the authors present those rare examples of (involuntary) modern-era economic downturns (as in Cuba after departure of the Soviets or Nauro after the depletion of their natural super-phosphate bonanza), which were accompanied by a marked decrease in overweight and obesity associated with reduced incidence of complications like diabetes and heart disease.

While the authors fall just short of suggesting that all governments should now pursue the utopian goal of economic sustainability rather than growth, they do point to a few programs that may nudge things in a more positive direction.

Whether countries are quite ready to embrace instruments like personal carbon trading (PCT) or whether majorities can be found to support the creation of more equitable societies remains doubtful. But I certainly do support their views on the promotion of public transportation and restrictions on advertising to children.

Although I do not seriously expect anyone (especially no governments I know of) to pay the least attention to Egger’s and Swinburn’s message, I do very much recommend the read for a concise, well-rounded, and mind-opening discussion of the causes behind the causes behind the causes of the obesity epidemic.

AMS
Summerland, BC

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A single mom juggling two jobs and four kids may be right in thinking her life is complicated - but it is certainly not complex - at least not in the scientific sense of the word.

In medicine we also differentiate between procedures that are complicated (difficult, requiring skill) and complex (no clear solutions, unknown and incalculable risks, unpredictable outcome).

The best description of complexity was the “simplified” one I found in a book called Black Swans by Nassim Taleb:

“A complex domain is characterized by the following: there is a great degree of interdependence between its elements, both temporal (a variable depends on its past changes), horizontal (variables depend on one another), and diagonal (variable A depends on the past history of variable B). As a result of this interdependence, mechanisms are subjected to positive, reinforcing feedback loops, which cause “fat tails”…In lay terms, moves are exacerbated over time instead of being dampened by counterbalancing forces. Finally, we have nonlinearities that accentuate fat tails.”

As some readers may know, the term “fat tails” refers to an unexpectedly thick end or “tail” toward the edges of a distribution curve, indicating an irregularly high likelihood of extreme or catastrophic events.

How is this discussion of complexity relevant to obesity?

When we speak of obesity as a complex problem (and not simply a matter of calories in and calories out), we allude to the complex interactions of a multitude of societal, psychological, and physiological variables that do not allow a ready dissection as to cause and effect (are large portion sizes leading to obesity or do obese people drive the demand for larger portions?).

Perhaps more importantly, complex systems are difficult to model - tweaking the system at one end (e.g. banning pop machines from schools) may lead to unintended consequences elsewhere in the system (e.g. schools have less money to invest in sporting activities).

This means that coming up with system-wide interventions (or rather predicting their effect) with regard to reversing the obesity epidemic will prove challenging. Well-meaning legislators may suddenly find themselves in a game of “whack-a-mole” as the system responds in unpredictable and erratic ways. (Politicians may still choose to pass populistic laws to demonstrate that they are not unresponsive - but no results are guaranteed).

Because of the temporal dissociation that may well occur in complex system, even when solutions look like they seem to be working, only time will tell, as unintended consequences may take years (or generations?) to manifest themselves.

This should not be an excuse to throw up our hands in despair and do nothing. It should, however, be a warning to anyone, who believes to have the “simple” solution to the obesity problem, to tread cautiously and to always expect the unexpected.

AMS
Whistler, BC