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Methods matter: population attributable fraction (PAF) in sport and exercise medicine
  1. Ahmad Khosravi1,2,
  2. Rasmus Oestergaard Nielsen3,4,
  3. Mohammad Ali Mansournia5,6
  1. 1 Department of Epidemiology, Shahroud University of Medical Sciences, Shahroud, Iran
  2. 2 Ophthalmic Epidemiology Research Center, Shahroud University of Medical Sciences, Shahroud, Iran
  3. 3 Department of Public Health, Section for Sports Science, Aarhus University, Aarhus, Denmark
  4. 4 Research Unit for General Practice, Aarhus, Denmark
  5. 5 Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
  6. 6 Sports Medicine Research Center, Neuroscience Institute, Tehran University of Medical Sciences, Tehran, Iran
  1. Correspondence to Professor Mohammad Ali Mansournia, Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran; mansournia_ma{at}yahoo.com

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Background

Physical inactivity kills as many people as smoking—a newspaper heading reads1 following a Lancet publication2 suggesting that more than 5 million deaths would be avoided annually if all inactive people exercised. The statistic that provided this data point (5 million deaths) is called the population attributable fraction (PAF) .3 PAF is an estimate of the health impact of an exposure (eg, physical inactivity, high-carbohydrate diet) on a health outcome (eg, death, heart attack, onset of type 2 diabetes mellitus).4 Although PAF is widely used in public health research, it is not yet well known in the sport and exercise medicine and physiotherapy settings. A search of the Pubmed database in December 2019 using the strings ‘PAF AND sports medicine’ or ‘PAF AND sports injury’ identified 12 hits and one hit, respectively. We believe that PAF will be of interest to those members of the BJSM community who work in physical activity/prevention research.

In the sports injury context, PAF may be used to identify the proportion of a certain injury attributed to a certain exposure. For instance, scientists may be interested to know the attributable fraction of bicycle-related head injuries in the population due to non-helmet use.5 Other examples include the sport medicine researcher interested in estimating the PAF of knee injuries as risk factor for knee osteoarthritis or knee replacement in footballers.6 In this case, they can calculate the proportion of knee osteoarthritis or knee replacement cases as long consequence of knee injury that will be prevented in footballers if they receive ‘the 11+’ prevention programme.7 8 In another example in this context, the coaches interested knowing how many injuries will be prevented in volleyball players with additional training sessions.9 Finally, policy makers may be interested in estimating the PAF using artificial turf …

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Footnotes

  • Twitter @RUNSAFE_Rasmus

  • Contributors AK wrote the paper, and MAM and RON revised the paper. All authors approved the final version of the paper.

  • Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

  • Competing interests None declared.

  • Patient consent for publication Not required.

  • Provenance and peer review Not commissioned; externally peer reviewed.

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