title: Translating context to causality in cardiovascular disparities research.
abstract: Moving from a descriptive focus to a comprehensive analysis grounded in causal inference can be particularly daunting for disparities researchers. However, even a simple model supported by the theoretical underpinnings of causality gives researchers a better chance to make correct inferences about possible interventions that can benefit our most vulnerable populations. This commentary provides a brief description of how race/ethnicity and context relate to questions of causality, and uses a hypothetical scenario to explore how different researchers might analyze the data to estimate causal effects of interest. Perhaps although not entirely removed of bias, these causal estimates will move us a step closer to understanding how to intervene. (PsycINFO Database Record
authors.affiliation: Center for Biostatistics and Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai.
authors.forename: Emma K T
authors.initials: EK
authors.lastname: Benn
authors.affiliation: Department of Population Health, New York University School of Medicine.
authors.forename: Keith S
authors.initials: KS
authors.lastname: Goldfeld
mesh_terms: D002318:Cardiovascular Diseases / Q000453:epidemiology* / Q000209:etiology*; D004522:Educational Status; D054625:Healthcare Disparities; D006801:Humans; D015233:Models, Statistical; D063505:Racism / Q000523:psychology; D012959:Socioeconomic Factors; D013315:Stress, Psychological / Q000150:complications / Q000453:epidemiology