Arya M. Sharma, MD

Hundreds of animal studies show that restricting caloric intake (while avoiding malnutrition) can expend the lifespan - often by periods, which translated into humans, would amount to an impressive number of years.

How does this work and can any of these findings be relevant to promote healthy aging in humans?

This is the topic of an article by Miranda Sung and Jason Dyck from the University of Alberta published in Heart Failure Reviews.

In animal models, the effects of caloric restriction on longevity is in part explained by a range of mechanisms that include:

1. Preventing age-associated changes in gene expression,

2. Enhancing innate cardioprotective signaling pathways that increase stress tolerance,

3. Reducing the risk factors for developing CVD,

4. Preventing and/or delaying the onset of age-related chronic diseases, including hypertension, atherosclerosis, type 2 diabetes, and cardiomyopathy

Interestingly, some of these effects can be mimicked by resveratrol, an active ingredient in red wine - one reason why the authors describe resveratrol as a ‘calorie-restriction mimetic’.

With regard to the potential benefits of caloric restriction in humans, the authors point out that:

“Due to the long lifespan of humans, the lack of universally accepted biomarkers of aging, and the difficulty of conducting long-term, randomized calorie restriction studies, there are limited data regarding longevity and dietary restriction in humans. However, epidemiological data appear to support findings in non-human primates discussed above that calorie restriction may have beneficial effects on longevity and health. For example, the inhabitants of Okinawa island in Japan consumed an estimated 15 and 40% fewer calories as compared to mainland Japanese and U.S. residents, respectively, yet Okinawans have the highest life expectancy in Japan and possibly the world and the largest percentage of centenarians in the world.”

Obviously, there could be other reasons for this ‘association’ in the Japanese and such data would be considered far from conclusive.

Thus, despite the evidence from animal studies and some indications that calorie restriction in humans may lead to similar biological effects (at least at the molecular level), it is certainly unclear whether calorie restriction (or reserveratrol) will reduce age-related cardiovascular disease in humans.

I may need a glass of red wine to relax and think about this.

AMS
Toronto, Ontario

Sung MM, & Dyck JR (2011). Age-related cardiovascular disease and the beneficial effects of calorie restriction. Heart failure reviews PMID: 22095297

Regular readers will be familiar with the rather strange but consistent finding that obese people with chronic diseases tend to do better than skinny people with chronic diseases.

This ‘paradox’ has been demonstrated for a wide range of conditions including cancers, heart failure, kidney disease, and chronic obstructive lung disease.

A new disorder that can apparently added to this growing list of conditions, where obesity seems to be of benefit, is the risk for foot amputations in younger diabetic men.

Thus, according to a study by Sohn and colleagues from Northwestern University Chicago, just published in OBESITY, the risk for amputation-free survival in diabetic men younger than 65 treated in the US Department of Veterans Affairs Healthcare System in 2003 were higher for patients with BMI <25 and lower for those with BMI ≥30 compared to overweight individuals (BMI 25-29.9).

In fact, individuals with BMI ≥40 were only half as likely to experience any major amputations during the 5-year follow-up as overweight individuals.

While the researchers do not offer any plausible reasons for this paradox, it is another remarkable finding that suggest that while being obese may increase your risk for many chronic diseases (including diabetes), once you have them, being obese may actually not be all that bad for you (at least compared to being skinny).

Go figure!

AMS
Edmonton, Alberta

Sohn MW, Budiman-Mak E, Oh EH, Park MS, Stuck RM, Stone NJ, & Pearce WB (2011). Obesity Paradox in Amputation Risk Among Nonelderly Diabetic Men. Obesity (Silver Spring, Md.) PMID: 21996669

Over the last several days I have been examining various aspects and implications of our recent publications showing that the Edmonton Obesity Staging System (EOSS) does a far better job of predicting mortality than does BMI (in fact BMI does almost nothing in this regard).

Not only does EOSS make intuitive sense to clinicians and most patients (especially the ones who are at EOSS 0) it is also a better way to individualize patient management strategies.

But, despite these two publications in three independent samples that included over 20,000 participants, many important questions remain to be addressed:

it is not clear whether all comorbidities should receive the same weight for defining the EOSS stage - for e.g. should chest pain due to reflux disease count the same as chest pain due to ischemic heart disease (probably not)?

What is the natural history of EOSS stage progression? Or in other words, how long does it take for patients to move from Stage 0 to Stage 1 or from Stage 2 to Stage 3? Are there really patients, who never progress? Are there predictors of progression? If yes, can this progression be delayed or prevented?

What does it take to reverse Stages and does reversing the obesity Stage improve prognosis (it probably does)?

How do cost-effectiveness and risk-benefit ratios of obesity treatment for patients look at different EOSS stages? I am guessing that both increase at higher stages, but is this really the case?

Can we develop a simplified version of EOSS (EOSS-lite?) that only counts certain comorbidities or only acknowledges certain dimensions of quality of life?

Is EOSS a concept that health professionals, decision makers, and funders are ready to adopt and will it improve practice and outcomes?

These are all questions that future research will need to address, some of this work is already underway, but I’d be happy to hear from potential collaborators or people wanting to do some of this research on their own.

If nothing else, I at least hope that the EOSS discussion has opened a whole new way of thinking about clinical assessment and definition of obesity and will find its way into clinical care pathways and management guidelines.

From everything I hear, this is already beginning to happen.

AMS
Edmonton, Alberta

Padwal RS, Pajewski NM, Allison DB, & Sharma AM (2011). Using the Edmonton obesity staging system to predict mortality in a population-representative cohort of people with overweight and obesity. CMAJ : Canadian Medical Association journal = journal de l’Association medicale canadienne PMID: 21844111

Kuk JL, Ardern CI, Church TS, Sharma AM, Padwal R, Sui X, & Blair SN (2011). Edmonton Obesity Staging System: association with weight history and mortality risk. Applied physiology, nutrition, and metabolism = Physiologie appliquee, nutrition et metabolisme PMID: 21838602

Regular readers of these pages will recall our recent paper in PLoS showing increased susceptibility for cardiometabolic risk factors in South Asians at substantially lower body weights than in Caucasians. These findings are consistent with a large body of evidence suggesting that the BMI definition of ‘obesity’ should likely start a lower BMI levels in South Asian and East Asian populations.

In India, not too long ago, redefinition of ‘obesity’ with lower BMI cutoffs, resulted in a major reclassification of the ‘burden of obesity’ in that country.

There is, however, good reason to assume that even at this lower BMI cutoff, the relationship between BMI and actual risk is probably as poor in this population, as it has proven to be in Caucasian samples.

We there think it reasonable to propose that the Edmonton Obesity Staging Stystem, which characterizes obesity stages based on how ’sick’ rather than simply on how ‘big’ a given patient may be, will also prove a better system to determine individual care plans than simply suggesting that everyone with a BMI that crosses a certain threshold to lose weight.

Since our recent papers on EOSS examined a predominantly white population, I very much hope that other investigators with access to South Asian or other ethnic populations will examine the relationship between EOSS and mortality in their subjects.

I would frankly be very surprised if their results turn out to be any different in that EOSS is a much better predictor of individual risk than BMI.

AMS
Edmonton, Alberta

Padwal RS, Pajewski NM, Allison DB, & Sharma AM (2011). Using the Edmonton obesity staging system to predict mortality in a population-representative cohort of people with overweight and obesity. CMAJ : Canadian Medical Association journal = journal de l’Association medicale canadienne PMID: 21844111

Kuk JL, Ardern CI, Church TS, Sharma AM, Padwal R, Sui X, & Blair SN (2011). Edmonton Obesity Staging System: association with weight history and mortality risk. Applied physiology, nutrition, and metabolism = Physiologie appliquee, nutrition et metabolisme PMID: 21838602

As not everyone may have a chance during the week to read every post, here’s a roundup of last week’s posts:

• Setting The Stage For Obesity Staging
• Health Is Not Measured In Pounds
• Will Losing Weight Make You Sick?
• Should Causality Matter In The Edmonton Staging System?
• Can The Edmonton Obesity Staging System Better Guide Indications For Bariatric Surgery?

Have a great Sunday! (or what’s left of it)

AMS
Toronto, Ontario

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