Monthly Archives: September 2020

1.5. Putting the Social Back in Social Epidemiology with Dr. Whitney Robinson



Is all epidemiology social epidemiology? If I am someone who studies cancer, or obesity, or infectious disease, or any other branch of epidemiology, should I be considering topics related to social epidemiology in my own work? In this episode of SERious Epidemiology, Dr. Whitney Robinson joins us to explain key concepts in social epidemiology.

After listening to this podcast, if you are interested in learning more about social epidemiology or some of the resources mentioned are included below:

  1. Kaufman, J.S. & Oakes, M. Methods in Social Epidemiology, 2nd edition.

https://www.amazon.com/Methods-Social-Epidemiology-Public-Biostatistics/dp/111850559X

  1. Link, Bruce G., and Jo Phelan. “Social Conditions As Fundamental Causes of Disease.” Journal of Health and Social Behavior, 1995, pp. 80–94. JSTOR, www.jstor.org/stable/2626958.
  2. Chandra Ford’s work on critical race praxis:

Ford, Chandra L, and Collins O Airhihenbuwa. “Critical Race Theory, race equity, and public health: toward antiracism praxis.” American journal of public health vol. 100 Suppl 1,Suppl 1 (2010): S30-5. doi:10.2105/AJPH.2009.171058

Ford CL, Airhihenbuwa CO. The public health critical race methodology: Praxis for antiracism research. Social Science & Medicine. 2010;71:1390-1398.

  1. VanderWeele TJ, Robinson WR. On the causal interpretation of race in regressions adjusting for confounding and mediating variables. Epidemiology. 2014;25(4):473-484. doi:10.1097/EDE.0000000000000105
  2. VanderWeele TJ, Robinson WR. Rejoinder: how to reduce racial disparities?: Upon what to intervene?. Epidemiology. 2014;25(4):491-493. doi:10.1097/EDE.0000000000000124
  3. Whitney R Robinson, Zinzi D Bailey, Invited Commentary: What Social Epidemiology Brings to the Table—Reconciling Social Epidemiology and Causal Inference, American Journal of Epidemiology, Volume 189, Issue 3, March 2020, Pages 171–174, https://doi.org/10.1093/aje/kwz197

1.4. Statisticalize your intervention soup: A journal club episode discussing Hernan and Taubman’s “Does obesity shorten life?”



In this journal club episode, we discuss one of our top 10 favourite epidemiology papers: “Does obesity shorten life? The importance of well-defined interventions to answer causal questions” by Miguel Hernán and Sarah Taubman. We talk about the consistency assumption in causal inference, why we think measurement error needs to be added to the list of assumptions for causal inference, and invent a new word (“statisticalize”) to dismiss the notion that fancy methods can always solve our problems.

 

References:

Hernán MA, Taubman SL. Does obesity shorten life? The importance of well-defined interventions to answer causal questions. Int J Obes. 2008;32:s8-s14.

Cole S, Frangakis C. The consistency statement in causal inference: a definition or an assumption? Epidemiology. 2009; 20:3-5.