Accuracy of BMI for Diagnosing Obesity

Body mass index (BMI) is currently widely recommended and used as the best measure of obesity both in population and clinical studies. It dates back to the Belgian statistician Adolphe Quételet, who between 1830 and 1850 described this index as a way to characterize the level of adiposity in sedentary adults.

But how accurate is this index really to identify individuals with excess body fat?

This question was recently addressed by Abel Romero-Corral and colleagues from the Mayo Clinic, MN, USA, who analysed the relationship between BMI and body fat percent (BF%) as measured by bioelectrical impedence in 13,601 subjects (age 20-79.9 years; 49% men) from the Third National Health and Nutrition Examination Survey (Int J Obesity).

In this study, the authors defined obesity based on the World Health Organization (WHO) reference standard for obesity of BF%>25% in men and >35% in women.

BMI-defined obesity (>=30) was present in 19% of men and 25% of women, while BF%-defined obesity was present in 44% of men and 52% of women.

A BMI>=30 had a high specificity (men=95%, women=99%), but a poor sensitivity (men=36%, women=49%) to detect BF%-defined obesity. This means that while the BMI definition does identify the vast majority of men and women who have increased body fat, it also misses a significant number of individuals who have high percent body fat and would be considered obese by the BF% definition.

The diagnostic performance of BMI diminished as age increased and in the intermediate range of BMI (25-29.9), BMI failed to discriminate between BF% and lean mass in both sexes.

The authors conclude that accuracy of BMI in diagnosing obesity is limited, particularly for individuals in the intermediate BMI ranges, in men and in the elderly. Thus, the currently recommended BMI cutoff of >=30 kg for obesity has good specificity but misses more than half the people with excess fat.

The scary part of these results of course is in the fact that based on actual BF% the prevalence of obesity in this population doubled! On the other hand, we know that %body fat or body composition alone is not a particularly reliable measure of health.

I prefer to continue using my operational clinical definition of obesity: the presence of excess body fat that threatens or affects your health.

Given the wide variation in the inter-individual susceptibility to develop adiposity-related health problems, the diagnosis of obesity and the question of whether or not reducing the proportion of body fat will indeed benefit your health will always remain a matter of clinical judgement.

AMS
Duschesnay, Quebec

What is Obesity?

Don't worry - I am not going to take off on a discussion about whether obesity is a disease or "simply" a risk factor. I am also not going to discuss again obesity definitions - anthropometric or otherwise.

Today's post is simply about an analogy that may help sharpen our clinical thinking around excess weight.

Think of someone who has an elevated plasma creatinine level (a marker of kidney failure) - the elevated creatine definitely tells us that there is something "wrong" with the kidneys, but that's about it. From the creatine level alone we can certainly tell that the kidneys are failing in their excretory function, but we cannot tell what is causing the kidneys to fail - is it a pre-renal, intra-renal or post-renal problem? We can probably list a 100 reasons why kidneys could fail and obviously the treatment (apart from some very general principles) will very much depend on the cause, i.e. the actual diagnosis.

In many ways, one can look at excess body fat simply as a sign or symptom of the fact that there is a something "wrong" with energy homeostasis. The excess body fat tells us nothing about what the problem is - sure, it's either excessive food intake or reduced energy expenditure - but that is like saying that the creatinine levels are elevated because the kidney is not excreting properly. I can think of a long list of reasons or factors that would contribute to excessive caloric intake or reduced energy expenditure: sociocultural factors, psychological factors, biomedical factors - figuring out what exactly is causing the energy imbalance is the real problem.

Only when we find what is causing the excessive intake will we have made a diagnosis of what is causing the problem - a few specific examples could include: poor meal planning, peer pressure, hedonic overeating, depression, obesogenic medications, binge eating disorder, defective satiety signaling, etc. The point is that till we know what is causing the overeating, we can't fix it, which means we will have little success in treating the weight problem and will be limited to a "symptomatic" approach - just eat less!

Similarly, when the problem appears to be lack of activity, again the question is what exactly is causing the problem. Obviously if the problem is lack of time our approach will hopefully be very different than if the problem is back pain or lack of motivation (a possible symptom of sleep apnea, exhaustion or depression). A "symptomatic" but useless approach would be to simply recommend 10,000 steps. No better than offering an ice-pack to someone with a fever.

Just as the term "kidney failure" only tells us that there is something "wrong" with the kidneys the term "obesity" only tells us that there is something "wrong" with energy homeostasis.

In itself, neither the term "kidney failure" nor "obesity" is a real diagnosis - they are only helpful if they prompt further investigation into what might have or is still causing the problem. Only when we find the cause will we be on our way to solving the problem.

AMS
Edmonton, Alberta

What's the Ideal Weight for a Japanese?

Regular readers of my blog know about my issues with a weight-based definition of obesity. As I have repeatedly pointed out, good health is possible over a wide range of body weights and weight alone is a rather poor measure of overall health.

Not surprisingly the same appears true for the Japanese. At least according to a paper just out in OBESITY, in which Atsushi Hozawa and colleagues from the Shiga University of Medical Science, Otsu, Japan, examined the relationship between BMI and all-cause mortality in 8,924 Japanese men and women without stroke or heart disease.

During 19 years of follow-up, 1,718 deaths were observed. As in other populations, the relationship between BMI and fatal events was U-shaped. Risk of total mortality was highest in participants with BMI <18.5 and lowest in participants with BMI 23.0-24.9. These findings persisted even after excluding the first 5 years of follow-up with a focus on healthy participants. For both the full sample and healthy participants, all-cause mortality risk did not differ between BMI ranges 21.0-22.9 and 23.0-24.9.

These data are particularly of interest because recent recommendation from the WHO and others suggest that a BMI > 23.0 should be considered overweight in Asian populations.

This would obviously make little sense if mortality is in fact lowest in individuals with BMI between 23.0-24.9.

Once again, this study illustrates the problem with BMI-based definitions of obesity which fail to take into account the huge inter-individual variability in the impact that excess body fat can have on health.

While there is no doubt that some Japanese with a BMI as low as 23 may have a full blown "metabolic syndrome", others (perhaps the majority) at the same BMI may be perfectly healthy.

Clearly it is time for a health-based rather than a solely anthropometric classification of obesity.

AMS
Edmonton, Alberta

ICD-10 Classification of Obesity: Can Someone Please Explain?

The International Statistical Classification of Diseases and Related Health Problems 10th Revision (ICD-10) is a widely-used coding of diseases and signs, symptoms, abnormal findings, complaints, social circumstances and external causes of injury or diseases, as classified by the World Health Organization (WHO).

Classification for obesity can be found in Chapter IV (Endocrine, nutritional and metabolic diseases) under the subsection Obesity and Other Hyperalimentation (Codes E66.0 to E66.9).

These are defined as follows:

E66.0 Obesity due to excess calories

E66.1 Drug-induced obesity

E66.2 Extreme obesity with alveolar hypoventilation (Pickwickian syndrome)

E66.8 Other obesity (Morbid obesity)

E66.9 Obesity, unspecified (Simple obesity NOS)

Here is why I do not understand this classification:

Well firstly, as far as I know, every form of weight gain requires an imbalance between energy intake and output. This means that all forms of obesity result from “excess” calories – i.e, if you define “excess” as exceeding caloric expenditure. Code E66.0 would therefore apply to all patients with obesity.

Weight gain in E66.1, which refers to drug-induced obesity, is of course also related to caloric “excess” – whether this results from hyperphagia (e.g. clozapine) or reduced metabolic rate (e.g. beta-blockers). When do you decide that someone is gaining weight solely because of a medication? More often than not there are other predisposing factors (e.g. sedentariness, depression, etc.).

Why the “coders” decided to make a special case for the rather rare alveolar hypoventilation (E66.2) but ignored all other major complications of severe obesity (e.g. heart failure, sleep apnea, osteoarthrits, etc.), at least to me, makes no sense.

But things get even more confusing!

E66.8 refers to “other obesity” – does this mean obesity not caused by caloric excess? Then none of my patients would ever qualify for this code. Or does E66.8 apply only to “morbid obesity” – which is not a WHO definition, unless they actually mean Class III obesity – then what about Class II obesity in case of a patient who is “morbid” because he has type 2 diabetes? Would this person qualify?

To fully add to the confusion, you can also choose code E66.9, i.e. “unspecified” or “simple” obesity – again, do they mean not resulting from caloric excess? Or do they perhaps mean patients with no complications? Or does ”simple” refer to cases where the cause is not “complicated” (as in, "this fellow “simply” eats too much")?

Overall, to me this classification makes no sense whatsoever. It is neither consistently based on etiology nor is it clinically meaningful in any sense of the word.

Take for example the case of someone with a BMI of 42 due to “simple” overeating who gains another 40 lbs after starting on clozapine resulting in numerous complications including alveolar hypoventilation. Would this patient’s obesity have to be classified as E66.0, E66.1; E66.2 or E66.8? Or, would this “simply” be E66.9. Or perhaps all of the above?

None of this makes any sense to me!

If there is anyone out there who can help me interpret these codes and show me how to use them to classify my patients in a way that would be clinically relevant, I’d be more than grateful.

In the meantime, I will continue using my own classification of obesity (which we now internally refer to as the “Edmonton Obesity Classification”). Although this system is not meant to provide insights into etiology, at least it allows me to clinically grade the amount of weight and to stage the extent of disease in every patient.

AMS
Edmonton, Alberta

Obesity Classification: Time to Move Beyond BMI?

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