Understanding causal inference: the future direction in sports injury prevention.
Although physical activity reduces mortality and morbidity, injuries associated with activity may increase both short- and long-term musculoskeletal disability. On the basis of basic science and injury epidemiology studies, authors have made conclusions about cause and effect (causal inferences) and have suggested various interventions to decrease the rate of injuries. However, recent advances in epidemiology suggest that the regression/stratification approach to adjustment for confounding does not provide an appropriate foundation for causal inference; therefore, hypotheses based on traditional analyses may be misleading. The purpose of this article is to provide an overview of the basic concepts of injury epidemiology related to causes, risk factors, and confounding, and to conceptually explain the more recent advances that allow for appropriate interpretations of cause and effect.
Shrier
Ian
I
Centre for Clinical Epidemiology and Community Studies, Lady Davis Institute for Medical Research, Department of Family Medicine, SMBD-Jewish General Hospital, Montréal, Canada. ian.shrier@mcgill.ca
D001265:Athletic Injuries / Q000517:prevention & control*; D015982:Bias; D015984:Causality; D015986:Confounding Factors, Epidemiologic; D006801:Humans