Absurd, but True?

Have you heard about the “obesity paradox?” Like all paradoxes, the obesity paradox suggests that something absurd might be true such as obese adults might have a greater chance of surviving some diseases than normal weight adults. According to a 2011 review by Paul McAuley and Steven Blair, a 1982 study by a research team lead by Patrice Degoulet was one of the earliest studies to discover the association between obesity and greater survival in their research on dialysis patients. McAuley and Blair go onto suggest that Luis Gruberg and his research team created the term “obesity paradox” in 2002. Gruberg and his team were investigating short-term and long-term outcomes after percutaneous coronary intervention in patients with coronary artery disease. The researchers discovered, to their surprise, that obese patients had a reduced risk of complications, cardiac death, and one-year mortality. Furthermore, according to a 2014 review by a group of researchers lead by Carl Lavie on obesity and cardiovascular (CV) diseases, a couple of long-term studies suggest that weight loss increases mortality in overweight and obese individuals. Therefore, weight loss may be more of a detriment than a benefit in obese patients with CV diseases. Lavie and his team point to a recent meta-analysis of 97 studies, consisting of approximately 2.9 million participants. The authors of the meta-analysis found that overweight patients with a body mass index (BMI) of 25 to 30 kg/m2 had six percent lower mortality than patients with a normal BMI (18.5 to 25 kg/m2). They also found that when all levels of obesity are taken into consideration, patients with a BMI of ≥ 30 kg/m2 had a significant increase in mortality risk when compared with normal BMI patients. Additionally, Lavie and his team cite research suggesting that higher BMI in younger patients increased their risk of mortality, whereas higher BMI in older patients decreased their risk.

What? This is counter to what we have been told in the media and from health and fitness “experts” about the dangers of being overweight or obese. Could it be that, as I have previously written about in It’s Simple, but it’s Not, obesity is complex? It’s not only complex at the cultural level, but also at the physiological level. Lavie and his team point out that recent research into obesity, fitness, and weight loss is beginning to provide some insight into the obesity paradox.

According to Lavie and his team, there are several potential causes for the obesity paradox in patients with CV diseases, such as undesired weight loss, a lower prevalence of smoking, age, and the BMI (a measure of body fat using height and weight). Lavie and his team point to research demonstrating that the BMI “has a poor diagnostic performance to identify obesity in the general population and also in cohorts with CHD [coronary heart disease].” The authors suggest that this poor performance may account for some of the obesity paradoxes they discuss in their review.

The BMI has become a big problem for some researchers. In 2011, Richard Bergman and his research team set out to develop a more accurate and efficient measure of percent body fat than the BMI. The authors argue that BMI does not accurately measure body fat in individuals with a high level of lean body mass (body weight minus the fat) and some ethnic groups. Furthermore, the BMI can be difficult to calculate in field settings when body weight cannot be accurately measured. Bergman and his team used two large studies to develop and test a new measure of adiposity: the BetaGen study that looked at gestational diabetes mellitus in 1,733 Mexican American participants and the Triglyceride and Cardiovascular Risk in African-Americans (TARA) study with 223 participants. The authors used dual-energy X-ray absorption (DXA), one of the most accurate measures of body fat, to measure the relationship between subject characteristics and adiposity in the groups. The authors found that in the BetaGen group “hip size divided by height to the power of 1.5 [-18], yielded the strongest correlation with DXA-derived %fat estimates.” The team then took their newly developed measure, the body adiposity index or BAI, and applied it to the TARA group and validated their results using DXA analysis. They found that the BAI had similar diagnostic accuracy in the TARA group as in the BetaGen group. Therefore, it accounted for ethnic differences. Bergman and his team also discovered that the relationship between BAI and percent adiposity was the same for men and women, so separate cutoffs were not needed. Furthermore, percent adiposity could be accurately estimated in the field without the use of costly and cumbersome measures of body weight. All that is needed is a simple tape measure. The authors warn that more research is needed to determine if the BAI is a more useful measure than the BMI, and other measures, in predicting health outcomes.

Lavie and his team also looked at research that used other methods of measuring obesity such as waist circumference and body fat to better understand the obesity paradox. In a 2012 study, Lavie and his team were able to show that CHD patients with both low body fat and low lean mass had the poorest survival outcomes, whereas patients with both high lean mass and body fat had the best. Due to these and other studies, the authors suggest that there may be an “overweight paradox,” rather than an obesity paradox.

Another potential source of confounding (an unaccounted for variable that can influence research results) identified by Lavie and his team was fitness. The authors found that body fatness and fitness could reliably predict CV disease risk factors including CV morbidity and mortality. Health related physical fitness, as defined in ACSM’s Guidelines for Exercise Testing and Prescription, is “a set of attributes or characteristics that people have or achieve that relates to the ability to perform physical activity.” These characteristics are separated into health- or skill-related components. Lavie and his team focused on the health-related components: cardiovascular endurance, body composition, muscular strength, muscular endurance, and flexibility. Although the authors acknowledge that the associations between fitness, fatness, and health remain controversial, they provide research examples that suggest that fitness is not only extremely predictive of CV disease, it “largely negates the adverse effects of body fatness, as well as other traditional CV risk factors, including overweight/obesity, metabolic syndrome/type II diabetes mellitus, and hypertension.” Lavie and his team conclude that fitness may be more important than preventing weight gain when considering long-term health outcomes.

As stated at the beginning of this blog post, weight loss may be more of a detriment than a benefit in obese patients with CV diseases. According to Lavie and his team, using weight loss to improve health outcomes in obese patients is controversial. The controversy is marked by conflicting research. For example, Lavie and his team cite three studies that show that diet, exercise training, and limited weight loss reduce the prevalence of metabolic syndrome and type II diabetes mellitus. However, the authors also cite a recent large study that did not show survival benefits for minimal weight loss in diabetic patients. Additionally, Lavie and his team looked at data from 12 studies that showed purposeful weight reduction improved outcomes or prognosis in obese patients with CV diseases, especially severely obese patients. The authors do recognize that more large-scale weight loss studies are needed to accurately assess the benefits of weight reduction in obese patients. Furthermore, Lavie and his team emphasize that the obesity paradox is usually not associated with morbidly obese (BMI ≥40 kg/m2) patients, which is a major risk factor for the development of CV diseases and is associated with poor prognosis if a patient develops CV diseases.

How the mighty have fallen: the BMI is an unreliable measure of body fat, being overweight with high lean body mass might be more healthy than normal weight with low mean body mass, and being overweight and fit might provide a person with the best health outcomes. How the health and fitness world will shudder to its core.

Rodney Steadman 15 July 2014

Works Cited

American College of Sports Medicine. (2013). ACSM’s guidelines for exercise testing and prescription. Lippincott Williams & Wilkins.
Bergman R, Stefanovski D, Buchanan T, Sumner A, Reynolds J, Sebring N, Xiang A, & Watanabe R (2011). A Better Index of Body Adiposity Obesity, 19 (5), 1083-1089 DOI: 10.1038/oby.2011.38

Degoulet P, Legrain M, Réach I, Aimé F, Devriés C, Rojas P, & Jacobs C (1982). Mortality risk factors in patients treated by chronic hemodialysis. Report of the Diaphane collaborative study. Nephron, 31 (2), 103-10 PMID: 7121651

Gruberg L, Weissman N, Waksman R, Fuchs S, Deible R, Pinnow E, Ahmed L, Kent K, Pichard A, Suddath W, Satler L, & Lindsay J (2002). The impact of obesity on the short-term andlong-term outcomes after percutaneous coronary intervention: the obesity paradox? Journal of the American College of Cardiology, 39 (4), 578-584 DOI: 10.1016/S0735-1097(01)01802-2

Lavie C, McAuley P, Church T, Milani R, & Blair S (2014). Obesity and Cardiovascular Diseases Journal of the American College of Cardiology, 63 (14), 1345-1354 DOI: 10.1016/j.jacc.2014.01.022

Lavie C, De Schutter A, Patel D, Romero-Corral A, Artham S, & Milani R (2012). Body Composition and Survival in Stable Coronary Heart Disease Journal of the American College of Cardiology, 60 (15), 1374-1380 DOI: 10.1016/j.jacc.2012.05.037

McAuley P, & Blair S (2011). Obesity paradoxes Journal of Sports Sciences, 29 (8), 773-782 DOI: 10.1080/02640414.2011.553965


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