An evolved interpretation of Austin Bradford Hill’s causal viewpoints and their influence on epidemiologic methods

In 1965, Sir Austin Bradford Hill articulated nine viewpoints for evaluating whether a body of evidence about the relationship between an exposure and outcome should be interpreted causally. In this commentary, we highlight a selection of the ways in which these viewpoints have had an impact on the field of epidemiology in terms of methods development, study design, and interpretation of results. Additionally, we opine on how the viewpoints relate to our understanding of basic epidemiologic concepts-for example, our choice of absolute or relative measures of effect, our evolving understanding of the role of context in the generalizability of study results, and modern epistemologies for causal inference (ie, the potential outcomes framework and graphical causal models). Hill cautioned his audience that evidence should be weighed according to the policy choice it would inform and the context in which that policy would be implemented. We root our remarks in considerations of the public health impact of our conclusions about the causal nature of an observed relationship.

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Publication Details

Journal
American Journal of Epidemiology
Published
2024-09-17
DOI
https://doi.org/10.1093/aje/kwae367
Citations
5
Primary Topic
Advanced Causal Inference Techniques
Type
article
Field-Weighted Citation Impact
3.55

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article

An evolved interpretation of Austin Bradford Hill’s causal viewpoints and their influence on epidemiologic methods

Catherine R. Lesko, Matthew P. Fox
5 citations
American Journal of Epidemiology
Advanced Causal Inference Techniques
3.55
article

An evolved interpretation of Austin Bradford Hill’s causal viewpoints and their influence on epidemiologic methods

Catherine R. Lesko, Matthew P. Fox
article en
5 citations

Abstract

In 1965, Sir Austin Bradford Hill articulated nine viewpoints for evaluating whether a body of evidence about the relationship between an exposure and outcome should be interpreted causally. In this commentary, we highlight a selection of the ways in which these viewpoints have had an impact on the field of epidemiology in terms of methods development, study design, and interpretation of results. Additionally, we opine on how the viewpoints relate to our understanding of basic epidemiologic concepts-for example, our choice of absolute or relative measures of effect, our evolving understanding of the role of context in the generalizability of study results, and modern epistemologies for causal inference (ie, the potential outcomes framework and graphical causal models). Hill cautioned his audience that evidence should be weighed according to the policy choice it would inform and the context in which that policy would be implemented. We root our remarks in considerations of the public health impact of our conclusions about the causal nature of an observed relationship.

American Journal of EpidemiologyVol. 194(6)
Boston University (US), Johns Hopkins University (US), Johns Hopkins Medicine (US)
National Institutes of Health
Good health and well-being
Openalex Percentile: Top 7%
Advanced Causal Inference Techniques
3.55
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