The obesity paradox: Understanding the effect of obesity on mortality among individuals with cardiovascular disease

Highlights

• The obesity paradox may be attributed to collider stratification bias.

• Physiological and methodological explanations for the paradox are discussed.

• Demonstrates the magnitude of bias induced by studying a highly selected group

Abstract

Objective

To discuss possible explanations for the obesity paradox and explore whether the paradox can be attributed to a form of selection bias known as collider stratification bias.

Method

The paper is divided into three parts. First, possible explanations for the obesity paradox are reviewed. Second, a simulated example is provided to describe collider stratification bias and how it could generate the obesity paradox. Finally, an example is provided using data from 17,636 participants in the US National and Nutrition Examination Survey (NHANES III). Generalized linear models were fit to assess the effect of obesity on mortality both in the general population and among individuals with diagnosed cardiovascular disease (CVD). Additionally, results from a bias analysis are presented.

Results

In the general population, the adjusted risk ratio relating obesity and all-cause mortality was 1.24 (95% CI 1.11, 1.39). Adjusted risk ratios comparing obese and non-obese among individuals with and without CVD were 0.79 (95% CI 0.68, 0.91) and 1.30 (95% CI = 1.12, 1.50), indicating that obesity has a protective association among individuals with CVD.

Conclusion

Results demonstrate that collider stratification bias is one plausible explanation for the obesity paradox. After conditioning on CVD status in the design or analysis, obesity can appear protective among individuals with CVD.

Introduction

Over the past three decades, the prevalence of obesity has increased substantially in North America (Flegal et al., 2010). A recent study by Flegal and colleagues highlighted that over one third of American adults (36%) are obese and more than two thirds (69%) are overweight (Flegal et al., 2012). In the general population, obesity is associated with an increased risk of death (Adams et al., 2006, Calle et al., 2003, Flegal et al., 2013). An analysis of data from nineteen pooled studies reported all-cause mortality hazard ratios of 1.44 (95% CI 1.38, 1.50) for grade I obesity (BMI 30 to 34.9 kg/m²), 1.88 (95% CI 1.77, 2.00) for grade II obesity (BMI 35 to 39.9 kg/m²), and 2.51 (95% CI 2.30, 2.73) for grade III obesity (BMI ≥ 40 kg/m²) relative to normal weight individuals (Berrington de Gonzalez et al., 2010).

Despite the known association between obesity and mortality in the general population, there have been conflicting reports about the relationship between obesity and mortality among individuals with cardiovascular disease (CVD). Numerous authors have reported that obesity confers a survival advantage in patients with CVD, a phenomenon known as the “obesity paradox” (McAuley and Blair, 2011, Romero-Corral et al., 2006). Among individuals with CVD, studies have reported that obese patients have improved short- and long-term survival, measured by all-cause mortality, relative to normal weight counterparts. Evidence of the obesity paradox has been found among patients with many types of cardiovascular disease, including coronary heart disease, myocardial infarction, hypertension, atrial fibrillation, and heart failure (Angerås et al., 2013, Badheka et al., 2010, Bucholz et al., 2012, Curtis et al., 2005, Lavie et al., 2009a, Lavie et al., 2009b, Nigam et al., 2006, Oreopoulos et al., 2008a, Oreopoulos et al., 2008b, Uretsky et al., 2007). As well, the obesity paradox has been documented among cardiac surgery patients, such as those who have undergone percutaneous coronary intervention, heart valve surgery, and coronary artery bypass surgery (Gruberg et al., 2002, Oreopoulos et al., 2008a, Oreopoulos et al., 2008b, Sarno et al., 2011, Vaduganathan et al., 2012, van der Boon et al., 2013). The obesity paradox has also been reported in patients with other types of chronic disease, including diabetes, cancer, renal disease, and chronic obstructive pulmonary disease (McAuley and Blair, 2011). Several hypotheses have been suggested to explain this phenomenon (Chrysant and Chrysant, 2013, Dixon and Lambert, 2013).