Approaches to improve causal inference in physical activity epidemiology

Article


Lynch, Brigid M., Dixon-Suen, Suzanne C., Ramirez Varela, Andrea, Yang, Yi, English, Dallas R., Ding, Ding, Gardiner, Paul A. and Boyle, Terry. 2020. "Approaches to improve causal inference in physical activity epidemiology." Journal of Physical Activity and Health. 17 (1), pp. 80-84. https://doi.org/10.1123/jpah.2019-0515
Article Title

Approaches to improve causal inference in physical activity epidemiology

ERA Journal ID9773
Article CategoryArticle
AuthorsLynch, Brigid M. (Author), Dixon-Suen, Suzanne C. (Author), Ramirez Varela, Andrea, Yang, Yi (Author), English, Dallas R. (Author), Ding, Ding (Author), Gardiner, Paul A. (Author) and Boyle, Terry (Author)
Journal TitleJournal of Physical Activity and Health
Journal Citation17 (1), pp. 80-84
Number of Pages5
Year2020
PublisherHuman Kinetics Publishers
Place of PublicationChampaign, IL, United States
ISSN1543-3080
1543-5474
Digital Object Identifier (DOI)https://doi.org/10.1123/jpah.2019-0515
Web Address (URL)https://journals.humankinetics.com/view/journals/jpah/17/1/article-p80.xml
Abstract

Background: It is not always clear whether physical activity is causally related to health outcomes, or whether the associations are induced through confounding or other biases. Randomized controlled trials of physical activity are not feasible when outcomes of interest are rare or develop over many years. Thus, we need methods to improve causal inference in observational physical activity studies. Methods:We outline a range of approaches that can improve causal inference in observational physical activity research, and also discuss the impact of measurement error on results and methods to minimize this. Results: Key concepts and methods described include directed acyclic graphs, quantitative bias analysis, Mendelian randomization, and potential outcomes approaches which include propensity scores, g methods, and causal mediation. Conclusions: We provide a brief overview of some contemporary epidemiological methods that are beginning to be used in physical activity research. Adoption of these methods will help build a stronger body of evidence for the health benefits of physical activity. © 2020 Human Kinetics, Inc.

Keywordsbiostatistics; causal inference; methods; potential outcomes approach
ANZSRC Field of Research 2020420204. Epidemiological methods
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Byline AffiliationsCancer Council Australia, Australia
Federal University of Pelotas, Brazil
University of Sydney
University of Queensland
University of South Australia
Institution of OriginUniversity of Southern Queensland
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