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.

Original languageEnglish
Pages (from-to)403-406
Number of pages4
JournalHealth Psychology
Issue number4
StatePublished - 1 Apr 2016


  • Cardiovascular
  • Causal inference
  • Context
  • Health disparities
  • Race/ethnicity


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