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Approaches to Improve Causal Inference in Physical Activity Epidemiology
- Source :
- Journal of physical activityhealth. 17(1)
- Publication Year :
- 2019
-
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.
- Subjects :
- Confounding
biostatistics
030229 sport sciences
Epidemiological method
methods
law.invention
03 medical and health sciences
0302 clinical medicine
Randomized controlled trial
Bias
law
potential outcomes approach
Causal inference
Mendelian randomization
Propensity score matching
Humans
Orthopedics and Sports Medicine
Observational study
030212 general & internal medicine
causal inference
Biostatistics
Psychology
Exercise
Cognitive psychology
Subjects
Details
- ISSN :
- 15435474
- Volume :
- 17
- Issue :
- 1
- Database :
- OpenAIRE
- Journal :
- Journal of physical activityhealth
- Accession number :
- edsair.doi.dedup.....29cb828a1f31e8aa410c332e0a18a5c4