Arya M. Sharma, MD

While I am taking a brief break from clinics and other obligations (including daily blog posts), I will be reposting past articles, which I still believe to be relevant but may have escaped the attention of the 100s of new readers who have signed up in the past months.

The following was first posted on 08/25/08

I have previously blogged on the profound effect of second generation antipsychotics (SGA) on weight gain. A new article by Melissa Blouin and co-workers from Laval University (Quebec City, Canada), published in this month’s issue of OBESITY, now examines the effect of these compounds on appetite, hunger, satiety, restraint and food preferences in SGA-treated patients (n=20) compared to controls (n=18).

Following a standardised breakfast, SGA patients had more hunger, higher cognitive dietary restraint, disinhibition and susceptibility to hunger than controls. In contrast to the controls, disinhibition in SGA-patients was largely triggered by internal cues. Although SGA-patients displayed higher strategic restraint behaviour, they also reported lower satiation after the buffet meal. No differences were found in food preferences.

This study has a number of interesting angles. Not only were the SGA-treated patients more susceptible to hunger, they were also more likely to consciously restrain their food intake, perhaps as a strategy to control their weight. This of course explains in part the fact that they were less likely to feel full or satiated after a meal than the controls.

It is well known that cognitive restraint (i.e. voluntarily trying to limit food intake) produces a tendency to overeat or even binge when restrictions are lifted (e.g. social disinhibition). The ultimate result, paradoxically, is weight gain or re-gain. This counter-regulatory phenomenon has been well described by Janet Polivy (University of Toronto) and essentially shows that food deprivation amongst dieters (achieved with cognitive dietary restriction) produces a tendency to overeat, explaining why long-term dieting does not work for restrained eaters. In other words - trying to simply eat less as a treatment for obesity is doomed to failure!

On a humanitarian note, the SGA-patients appear to be caught in an unfortunate vicious cycle: The antipsychotics alter eating behaviour to increase body weight - patients try to avoid further weight gain by cognitively restraining their food intake - as a result they feel less satiated and end up eating even more.

Complicated!

Of course, from this study, we don’t really know if the patients’ abnormal behaviour is due to their medications or simply due to their underlying disease. A third group of subjects consisting of psychotic patients treated with older antipsychotic medications may have answered this question.

Nevertheless, the study does demonstrate that we need to be very cautious in simply blaming someone with obesity for their condition. As this study reminds us - trying to not gain weight by simply eating less, is often a prescription for weight gain.

AMS
Edmonton, Alberta

While I am taking a brief break from clinics and other obligations (including daily blog posts), I will be reposting past articles, which I still believe to be relevant but may have escaped the attention of the 100s of new readers who have signed up in the past months.

The following was first posted on 30/03/08 (the Edmonton Obesity Staging System suggested in this original post, is now published in the International Journal of Obesity. Also note the foresight expressed in this post in light of Margaret Wente’s thought-provoking comment published in yesterday’s Globe and Mail - as this “classic” blog post demonstrates, we were well over a year ahead of Margaret in our thinking about what constitutes obesity and who needs treatment - good to see the mainstream media catch up!).

Current definitions of obesity based on BMI and waist circumference (WC), while widely accepted, are hardly helpful in counseling individual patients. Readers of my blog are probably quite familiar with my views on this.

As most clinicians will readily agree, when dealing with indiviual patients, both measures lack sensitivity and specificity with regard to identifying the presence or risk of obesity-related risk factors, comorbidities, psychopathology, global functioning or quality of life.

In fact recent epidemiological studies emphasize that good health including low morbidity and mortality is possible over a wide range of BMI. Thus, basing the decision on who to treat and who to leave well alone solely on measures of weight or size is neither sensible nor does justice to the complexity of the relationship between excess body fat and its impact on health and well-being. The well-established obesity-chronic disease paradox makes decisions on who to treat and who not to treat even more uncertain.

Telling healthy large people who have no apparent comorbidities, functional limitations or reduced well-being to lose weight may be counterproductive in that it can introduce and reinforce dissatisfaction with body image, foster frustrations and despair (given the poor long-term success of weight loss attempts) and lead to unhealthy behaviours focusing on weight loss (e.g. excessive exercise or dieting) rather than on healthy lifestyles (which are possible at almost any weight).

Thus, for practical purposes, it is important to move beyond defining who needs obesity treatment simply based on BMI and/or WC to a more clinically meaningful system.

Indeed, what we direly need is a classification of obesity that is clinically relevant in that it helps identify patients who have or are at high-risk of obesity-related complications and are most likely to benefit from treatment.

In this context, it may be worthwhile to look at the systems of classification and staging used for other disease states.

Oncologists have long used the TNM system to classify the extent of cancer spread. This system has established itself for the classification and staging of the vast majority of cancers not only because it is clinically meaningful in that it reflects extent of disease, indicates prognosis and allows evaluation of treatment response but also facilitates surveillance and research.

Psychiatrists and other mental health workers now routinely report on their patients using the five axes set out in the DSM-IV, each of which refers to a different domain of information that help the clinician plan treatment and predict outcome. The five axes are:

Axis I Clinical Disorders (all mental disorders except Personality Disorders and Mental Retardation)

Axis II Personality Disorders and Mental Retardation

Axis III General Medical Conditions (must be connected to a Mental Disorder)

Axis IV Psychosocial and Environmental Problems (for example limited social support network)

Axis V Global Assessment of Functioning (Psychological, social and job-related functions are evaluated on a continuum between mental health and extreme mental disorder)

While these systems are by no means simple or easy for the layman to understand, they are clinically useful and provide a standardized framework within which it is possible to describe the extent and impact of disease in a way that all clinicians, researchers and payors will understand.

Contrast these systems to the rather simplistic obesity classification, where knowing that a given person has Class II obesity (BMI 35-39.9) tells you virtually nothing about that person’s health or well being. Furthermore, it provides no meaningful guide in determining outcomes: e.g. someone who weighs 120 Kg with a BMI of 39 (Class 2 obesity) despite losing 10 Kg (8% weight loss) still has Class II obesity (BMI 36). This classification neither tells us what (if any) comorbities were actually present or whether (or not) these actually got better.

Now I am no expert on disease classification and realise the large amount of work and consensus meetings that go into developing these classification systems. But I am a clinician, who regularly sees patients and would be happy to see even the simplest form of staging that provides a meaningful framework.

The simplest classification I can think of would be to use a staging system similar to the following:

Stage 0: no apparent obesity-related risk factors (blood pressure, lipids, glucose, etc.), physical symptoms, psychopathology, functional limitations, or impairment of well-being

Stage 1: presence of obesity-related sub-clinical risk factors (elevated blood pressure, impaired fasting glucose, fatty liver, etc.), mild physical symptoms (dyspnea on moderate exertion, occasional aches and pains, etc.), mild psychopathology, mild functional limitations or mild impairment of well-being

Stage 2: presence of established obesity-related chronic disease like hypertension, type 2 diabetes, sleep apnea, osteoarthritis, reflux disease, polycystic ovary syndrome, depression, anxiety disorder, moderate limitations in activities of daily living and/or well being.

Stage 3: established end-organ damage like myocardial infarction, diabetic complications, severe osteoarthritis, significant psychopathology, significant functional limitations and impairment of well-being

Stage 4: severe (end-stage?) disabilities from obesity-related chronic disease, severe disabling psychopathology, severe functional limitations and severe impairment of well-being

Thus for e.g. a 24 year-old physically active female with a BMI of 32 with no measurable risk factors, functional limitations or self-esteem issues would have Class I, Stage 0 Obesity - benefits of treatment will be marginal or non-existent.

A 32 year-old male with BMI of 36 with hypertension and sleep apnea would have Class III, Stage 2 Obesity - definite indication for obesity treatment.

A 45 year-old female with BMI of 54 who is in a wheel chair because of severe gonarthritis with severe hypoventilaltion would have Class III, Stage 4 Obesity - will require aggressive obesity treatment unless deemed palliative.

But this may not be the only conceivable system. In fact, given the significant importance of psychopathology, personality traits, physical disease, psychosocial and enviromental factors as well as global functioning, I wonder if an approach similar to the axes in DSM-IV may be best. Of course, one could easily envision combinations of both systems, e.g. applying staging to Axis III disorders.

Obviously any such system would need careful definitions and perhaps a complex manual of diagnostics and classifications similar to DSM-IV - but at least we would have a way to assess, describe, treat, monitor and research obesity in a way that goes beyond the relatively meaningless anthropometry-based classification, which is nothing short of useless in clinical practice.

I can see why health authorities, professional organisations and even clinicians may be reluctant to devise a more complex classification of obesity - all I can say is that the present classification does not provide a meaningful framework in which to make clinical decisions or evaluate outcomes. There is certainly a need for a more complex system to guide practice (and research).

More often than not in clinical medicine - simple is simply wrong!

AMS
Edmonton, Alberta

As a nephrologist, I come from a field in which many key decisions are based on the outcome of a biopsy specimen. There are indeed many areas of medicine in which tissue biopsies are routinely used to establish a diagnosis or to guide treatment. Could the same hold true for obesity?

We have long known that obesity is by no means a homogeneous condition and that the clinical manifestation of obesity related comorbidities covers a wide and unpredictable spectrum of disorders. It is thus only likely that different forms of obesity are heterogeneous at the tissue level and in their response to treatment.

A first indication of just how adipose tissue biopsies may be used in clinical practice now comes from a study published in this month’s issue of the International Journal of Obesity. In this paper, Wang and colleagues from the Pennington Biomedical Research Center, Baton Rouge, LA, USA, use microarray gene expression technology to group 72 otherwise healthy obese men and women into two distinct clusters (denoted red and green). Interestingly, the red cluster contained no men, had “red” patients had less visceral fat and smaller fat cells. More importantly, it appeared that the patients in the green cluster appeared to respond with slightly greater weight loss to adrenergic treatment with ephedra and caffeine (not exactly my choice of antiobesity drugs) in an 8 week intervention.

Although the authors may be a tad overenthusiastic in terms of proclaiming that this paper now “brings us into an era of personalized treatment in the obesity clinic”, there is certainly some hope that fat biopsies may someday prove to provide a clinically useful predictor for response to specific treatments.

Obviously much needs to happen before anyone would seriously consider routine fat biopsies in clinical practice. For one, we would need prospective studies on sensitivity and specificity to detect clinically significant differences in response. Obviously, cost-effectiveness analyses would also need to establish the cost/benefit ratio for what is still a very expensive technology.

For now, nonetheless, the study confirms what I have maintained all along - obesity is a heterogeneous disorder and there is no reason to assume that any one treatment will work for all.

AMS
Edmonton, Alberta

Since its launch almost a decade ago, the notion that the use of the satiogenic serotonin-norepineprhine-reuptake-inhibitor (SNRI) sibutramine commonly results in an increase in blood pressure, has been a major barrier to its use in high-risk cardiovascular patients, particularly those with high blood pressure.

Nevertheless, over the past years, several lines of evidence have emerged suggesting that while sibutramine may increase blood pressure in a small group of susceptible individuals (particularly in those with normal blood pressure), its overall effect on blood pressure is the opposite, i.e. the vast majority of patients on sibutramine actually experience a fall in blood pressure with treatment. This appears particularly true for patients with moderately elevated blood pressure levels.

So what happens to blood pressure, when sibutramine is used in high-risk patients with poorly controlled blood pressure?

This question was analysed in the 6-week run-in phase of the SCOUT study (an ongoing, double-blind, randomized, placebo-controlled outcome trial in overweight/obese patients at high risk of a cardiovascular event), published in last month’s issue of Diabetes, Obesity & Metabolism.

During the 6-week single-blind lead-in period, 10,742 patients received sibutramine and weight management. Vital sign changes were assessed post hoc by initial blood pressure (mmHg) categorized as normal, high-normal or hypertensive.

To assess the impact of sibutramine on blood pressure and pulse rate, only patients (N = 10,025) who reported no change in the class of antihypertensive medication used and who did not report an increase in antihypertensive medication use were analysed.

At entry, approximately 50% of patients were hypertensive and 26% were high-normal. In hypertensive patients, blood pressure changes decreased by median of -6.5 mmHg systolic and -2.0 mmHg diastolic (P<0.001).

Interestingly, even hypertensive patients with no weight loss or with weight gain had median decreases of -3.5 mmHg systolic and -1.5 mmHg diastolic (p < 0.001).

In contrast, normotensive patients had median increases of 1.5 mmHg systolic and 1.0 mmHg diastolic (p < 0.001), which was attenuated with increasing weight loss in that blood pressure was significantly decreased in normotensive patients, who lost >5% of their initial weight.

Approximately 43% of patients initially categorized as hypertensive had a lower blood pressure category after 6-weeks on sibutramine.

In contrast to the differential effect on blood pressure, pulse rates were uniformly elevated by 1-4 bpm across blood pressure and weight change categories.

Obviously, these results have to be interpreted with caution as there is no control group and there is some potential for regression to the mean. Nevertheless, the results do support the notion that even in high risk patients, the predominant effect of sibutramine administered together with a weight-loss program is a blood pressure decrease - especially in patients with pre-existent hypertension.

It will be of great interest to see what the net effect of sibutramine treatment on cardiovascular outcomes and safety will be, when the final results of SCOUT are revealed on completion of this major obesity outcome study.

AMS
Edmonton, Alberta

Disclaimer: I am on the Executive Steering Committee of the SCOUT study and have received consulting and speaker honoraria as well as research support from Abbott Laboratories, the makers of sibutramine.

In response to yesterday’s post on ADHD and obesity, I was made aware of two recent studies, both relevant to this topic.

In the first, A psycho-genetic study by Caroline Davis and colleagues from York University, Toronto, Ontario, Canada, published in the Journal of Psychiatric Research, the researchers examined whether ADHD symptoms were more pronounced in adults with symptoms of binge eating disorder (BE) than in their non-binging obese counterparts, and whether the links were stronger with inattentive vs impulsive/hyperactive symptoms. They also assessed the role of the dopamine D3 receptor in ADHD symptoms since the DRD3 gene has been associated with impulsivity and drug addiction - both relevant features of ADHD.

In the study that involved 60 cases and 120 controls (60 obese and 60 normal weight), childhood and adults ADHD symptoms were assessed and genotying was performed.

While all of the four ADHD symptom scales were significantly elevated in the BE and obese groups compared to the normal weight group, bearers of three DRD3 genotypes had significantly elevated scores on the hyperactive/impulsive symptom scale.

These results suggest that symptoms of ADHD are more common in obese individuals (irrespective of BED status) and that the D3 receptor may play a role in the manifestation of the hyperactive/impulsive symptoms of ADHD.

In another study, published in this month’s issue of OBESITY by Lance Levy and colleagues from the Nutritional Disorders Clinic, also in Toronto, Ontario, Canada, they describe their success in treating refractory obesity in severely obese adults following the management of newly diagnosed attention deficit hyperactivity disorder.

78 subjects out of 242 consecutively referred severely obese, weight loss refractory individuals were diagnosed as having ADHD, of which 65 received ADHD treatment and 13 remained as controls.

After an average of 466 days of continuous ADHD pharmacotherapy, weight change in treated subjects was -12% of initial weight versus a 3% weight gain in controls.

This study not only confirms that ADHD is a highly prevalent condition in severely obese patients, but that the treatment of ADHD is associated with significant long-term weight loss in individuals with a lengthy history of weight loss failure.

Levy suggests, as I did in earlier postings on this topic, that ADHD should be considered as a primary cause of weight loss failure in obese patients.

As he points out, this finding may also be important for patients seeking obesity surgery, as surgical patients with unmanaged ADHD may display poor compliance with diet and supplement requirements.

AMS
Edmonton, Alberta

p.s. Caroline Davis will be presenting at the upcoming 1st National Obesity Summit, Kananaskis, Alberta, May 7-10, hosted by the Canadian Obesity Network