Study: "Obesity Paradox" in Cardiovascular Disease Does Not Exist

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The "obesity paradox" suggests that patients with excess weight are associated with better survival among individuals with cardiovascular disease -a mysterious and confounding phenomenon that has been demonstrated in many clinical studies.

The “obesity paradox” suggests that patients with excess weight are associated with better survival among individuals with cardiovascular disease (CVD)—a mysterious and confounding phenomenon that has been demonstrated in many clinical studies.

This paradox seems to go against everything we’d expect in terms of cardiovascular mortality. Why would those patients at greater risk for developing CVD also have a greater chance of surviving it?

A new study in Obesity suggests that the paradox is an “artifact of reverse causation and confounding by smoking rather than a real biological phenomenon as previous studies have argued.” The findings are in direct dispute of a recent European Journal of Epidemiology meta-analysis and many others.

The researchers investigated the association between weight status and mortality in the US population ages 35 and above with CVD. Data were obtained from the National Health and Nutrition Examination Survey, 1988-2010, linked to mortality records through 2011. To minimize biases resulting from illness-induced weight loss, a reference category consisting of individuals who have always maintained normal weight was used. Age-standardized mortality rates and Cox models were estimated, comparing overweight/obesity (body mass index (BMI) ≥25.0 kg m−2) to normal weight (BMI 18.5-24.9 kg m−2).

The researchers found that the paradox was present among those with overweight/obesity at the time of survey (hazard ratio (HR) = 0.89; 95% confidence interval (CI) 0.78-1.01). However, when the reference category was limited to the always-normal-weight, the paradox disappeared (HR = 1.16; 95% CI 0.95-1.41). When analysis was additionally confined to never-smokers, mortality risks were significantly higher in the overweight/obesity group (HR = 1.51; 95% CI 1.07-2.15; P = 0.021).

“Our results show that simultaneously addressing both confounding by smoking and reverse causality leads to a striking reversal of the obesity paradox,” wrote the study authors. “Having overweight/obesity was associated with a non-significant 11% reduction in mortality relative to normal weight in a conventional model that used BMI at survey to assess weight status. However, when the reference category was defined to include only those who have always been of normal weight and the sample was restricted to never-smokers, overweight/obesity was associated with a statistically significant 51% increase in mortality.”

How could the paradox have persisted for so long?

For one, according to the study authors, studies of the mortality consequences of obesity are subject to two major biases: reverse causation and confounding by smoking. These biases are typically enhanced when attention is confined to individuals who have entered a disease state. Reverse causation refers to instances in which weight is a consequence rather than a cause of illness. Low weight is often a result of disease, which can cause loss of appetite or increase metabolic demands, and is associated with higher mortality. Because the incidence of weight loss is typically higher among individuals suffering from an illness and because mortality is also higher, reverse causation is a greater threat to unbiased estimation of the mortality risks of obesity when analysis is confined to such individuals.

Also, individuals with overweight/obesity are less likely to smoke than normal-weight individuals, a negative relationship that becomes stronger when individuals are selected into a disease state for which both smoking and obesity are risk factors. “The stronger negative correlation between smoking and obesity in the disease state, in turn, enhances the risk of residual confounding, producing a downward bias in the estimated mortality risk associated with obesity,” the researchers observe.

“Without identifying the key role of smoking, several other authors have hypothesized the operation of an unobserved risk factor that, having collided with obesity in the disease state, raises the relative mortality of the non-obese in that state. Confounding by smoking and reverse causality are major sources of bias in estimating the association between weight status and mortality. We have shown that these biases are enhanced in the population with CVD, in which both the prevalence of illness is higher and the negative correlation between BMI and smoking is stronger than in the source population.”

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