Citation

Blanchard T. Synthese 2022; 200(6): e482.

Copyright

(Copyright © 2022, Holtzbrinck Springer Nature Publishing Group)

DOI

10.1007/s11229-022-03944-z

PMID

unavailable

Abstract

The epidemiologist Bradford Hill famously argued that in epidemiology, specificity of association (roughly, the fact that an environmental or behavioral risk factor is associated with just one or at most a few medical outcomes) is strong evidence of causation. Prominent epidemiologists have dismissed Hill's claim on the ground that it relies on a dubious 'one-cause one effect' model of disease causation. The paper examines this methodological controversy, and argues that specificity considerations do have a useful role to play in causal inference in epidemiology. More precisely, I argue that specificity considerations help solve a pervasive inferential problem in contemporary epidemiology: the problem of determining whether an exposure-outcome correlation might be due to confounding by a social factor. This examination of specificity has interesting consequences for our understanding of the methodology of epidemiology. It highlights how the methodology of epidemiology relies on local tools designed to address specific inference problems peculiar to the discipline, and shows that observational causal inference in epidemiology can proceed with little prior knowledge of the causal structure of the phenomenon investigated. I also argue that specificity of association cannot (despite claims to the contrary) be entirely explained in terms of Woodward's well-known concept of "one-to-one" causal specificity. This is because specificity as understood by epidemiologists depends on whether an exposure (or outcome) is associated with a 'heterogeneous' set of variables. This dimension of heterogeneity is not captured in Woodward's notion, but is crucial for understanding the evidential import of specificity of association.

Language: en

Keywords

Causal inference; Causal specificity; Epidemiology; Specificity of association