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068 Environmental factors, training factors, race pace and distance, older age, and metabolic/endocrine disease are independent risk factors associated with adverse events in runners: a SAFER study in 76654 starters
  1. Martin Schwellnus1,2,3,
  2. Nicola Sewry1,
  3. Mats Borjesson4,5,6,
  4. Sonja Swanevelder7,
  5. Esme Jordaan7,8
  1. 1Sport, Exercise Medicine and Lifestyle Institute (SEMLI), Pretoria, South Africa
  2. 2IOC Research Centre, South Africa, Pretoria, South Africa
  3. 3Emeritus Professor of Sport and Exercise Medicine, Faculty of Health Sciences, University of Cape Town, South Africa, Cape Town, South Africa
  4. 4Institute of Neuroscience and Physiology, Sahlgrenska Academy, Göteborg University, Göteborg, Sweden
  5. 5Center for Health and Performance, Göteborg University, Göteborg, Sweden
  6. 6Sahlgrenska University Hospital/Östra, Göteborg, Göteborg, Sweden
  7. 7Biostatistics Unit, South African Medical Research Council, Cape Town, South Africa
  8. 8Statistics and Population Studies Department, University of the Western Cape, Cape Town, South Africa


Background Pre-race medical screening at endurance events has recently been suggested, but there are limited data on the use of pre-race questionnaire data to predict adverse events (defined as medical encounters or not finishing a race).

Objective To determine if risk factors, that are identified from a pre-race medical screening questionnaire, are associated with adverse events during a distance running event.

Design Prospective study, with cross-sectional analyses.

Setting 2012–2015 Two Oceans marathon races (21.1 km, 56 km), South Africa.

Patients (or Participants) 76654 race entrants (21.1 km and 56 km race).

Interventions (or Assessment of Risk Factors) Upon entering the race, all entrants completed a pre-race medical screening questionnaire. Based on the responses to the questionnaire, runners received a targeted educational intervention to reduce medical encounters (ME). All individual race day data was collected, and this included AE data as follows: runners that did-not-finish (DNF) the race (collected from the race organisers), and runners who had a medical encounter (ME) (collected by race day medical staff).

Main Outcome Measurements Using a multiple regression model, we report the prevalence ratio (PR: 95% CI) of risk factors associated with the adverse event rate (AE) (defined as DNF or ME), using race day data and individual pre-race medical screening data.

Results Independent risk factors associated with AE in the Two Oceans Races were: males >45years (1.2: 1.0–1.3; p=0.0210), females >55years (1.5: 1.1–2.1; p=0.0051), slower training pace (increase of 1min/km, 1.2: 1.1–1.2; p<0.0001), increased training frequency per week (increase of 2 times/week, 1.2: 1.1–1.3; p=0.0017), and a history of metabolic/endocrine disease (1.6: 1.2–2.1; p=0.0006).

Conclusions Environmental and training factors, older age, race pace and distance, and history of metabolic/endocrine disease were independent risk factors associated with adverse events in a mass-participation distance running event. These factors could be considered when developing and implementing pre-race education material that is disseminated to participants prior to the event.

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