title: Obesity paradox in heart failure: statistical artifact, or impetus to rethink clinical practice?
abstract: The "obesity paradox" in heart failure (HF) is a phenomenon of more favorable prognosis, especially better survival, in obese versus normal-weight HF patients. Various explanations for the paradox have been offered; while different in their details, they typically share the premise that obesity per se is not actually the cause of reduced mortality in HF. Even so, there is a lingering question of whether clinicians should refrain from, or at least soft-pedal on, encouraging weight loss among their obese HF patients. Against the backdrop of recent epidemiological analysis by Banack and Kaufman, which speculates that collider stratification bias may generate the obesity paradox, we seek to address the aforementioned question. Following a literature review, which confirms that obese HF patients are demographically and clinically different from their normal-weight counterparts, we present four hypothetical data sets to illustrate a spectrum of possibilities regarding the obesity-mortality association. Importantly, these hypothetical data sets become indistinguishable from each other when a crucial variable is unmeasured or unreported. While thorough, the discussion of these data sets is intended to be accessible to a wide audience, especially including clinicians, without a prerequisite of familiarity with advanced epidemiology. We also furnish intuitive visual diagrams which depict a version of the obesity paradox. These illustrations, along with reflection on the distinction between weight and weight loss (and, furthermore, between voluntary and involuntary weight loss), lead to our recommendation for clinicians regarding the encouragement of weight loss. Finally, our conclusion explicitly addresses the questions posed in the title of this article.
authors: Departments of Statistics and Biostatistics, University of Kentucky, Lexington, KY, USA.
authors: Richard
authors: R
authors: Charnigo
authors: Gill Heart Institute, University of Kentucky, Lexington, KY, USA. mguglin@gmail.com.
authors: Maya
authors: M
authors: Guglin
mesh_terms: D016477:Artifacts; D015992:Body Mass Index; D015986:Confounding Factors, Epidemiologic; D014943:Global Health; D006333:Heart Failure / Q000150:complications* / Q000453:epidemiology; D006801:Humans; D009765:Obesity / Q000150:complications* / Q000453:epidemiology; D011379:Prognosis; D018570:Risk Assessment / Q000706:statistics & numerical data*; D012307:Risk Factors; D015996:Survival Rate / Q000639:trends
keywords: Anscombe quartet; Collider stratification bias; Confounding; Heart failure; Obesity; Obesity paradox; Reverse causality; Simpson’s paradox; Weight loss