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Novel Factors Associated With Analgesic and Anti-inflammatory Medication Use in Distance Runners: Pre-race Screening Among 76 654 Race Entrants—SAFER Study VI

Rotunno, Adrian, MBBCh, MSc*; Schwellnus, Martin P., MBBCh, MSc, MD*,†,‡; Swanevelder, Sonja, MSc§; Jordaan, Esme, MSc§,¶; Janse Van Rensburg, Dina C., MBBCh, MMed, MD*; Derman, Wayne, MBBCh, PhD†,║

Clinical Journal of Sport Medicine: September 2018 - Volume 28 - Issue 5 - p 427–434
doi: 10.1097/JSM.0000000000000619
Original Research

Objective: Analgesic/anti-inflammatory medication (AAIM) increases the risk of medical complications during endurance races. We determined how many runners use AAIM before or during races, AAIM types, and factors associated with AAIM use.

Design: Cross-sectional study.

Setting: 21.1-km and 56-km races.

Participants: Seventy-six thousand six hundred fifty-four race entrants.

Methods: Participants completed pre-race medical screening questions on AAIM use, running injury or exercise-associated muscle cramping (EAMC) history, and general medical history.

Main Outcome Measures: Analgesic/anti-inflammatory medication use, types of AAIM (% runners; 95% confidence interval), and factors associated with AAIM use (sex, age, race distance, history of running injury or EAMC, and history of chronic diseases) [prevalence ratio (PR)].

Results: Overall, 12.2% (12.0-12.5) runners used AAIM 1 week before and/or during races (56 km = 18.6%; 18.0-19.1, 21.1 km = 8.3%; 8.1-8.6) (P < 0.0001). During races, nonsteroidal anti-inflammatory drugs (NSAIDs) (5.3%; 5.1-5.5) and paracetamol (2.6%; 2.4-2.7) were used mostly. Independent factors (adjusted PR for sex, age, and race distance; P < 0.0001) associated with AAIM use were running injury (2.7; 2.6-2.9), EAMC (2.0; 1.9-2.1), cardiovascular disease (CVD) symptoms (2.1; 1.8-2.4), known CVD (1.7; 1.5-1.9), CVD risk factors (1.6; 1.5-1.6), allergies (1.6; 1.5-1.7), cancer (1.3; 1.1-1.5), and respiratory (1.7; 1.6-1.8), gastrointestinal (2.0; 1.9-2.2), nervous system (1.9; 1.7-2.1), kidney/bladder (1.8; 1.6-2.0), endocrine (1.5; 1.4-1.7), and hematological/immune (1.5; 1.2-1.8) diseases.

Conclusions: 12.2% runners use AAIM before and/or during races, mostly NSAIDs. Factors (independent of sex, age, and race distance) associated with AAIM use were history of injuries, EAMC, and numerous chronic diseases. We suggest a pre-race screening and educational program to reduce AAIM use in endurance athletes to promote safer races.

*Sport, Exercise Medicine and Lifestyle Institute (SEMLI) and Section Sports Medicine, Faculty of Health Sciences, University of Pretoria, Pretoria, South Africa;

International Olympic Committee (IOC) Research Centre, Pretoria, South Africa;

Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa;

§Biostatistics Unit, South African Medical Research Council, Parow, South Africa;

Statistics and Population Studies Department, University of the Western Cape, Cape Town, South Africa; and

Institute for Sport and Exercise Medicine, Faculty of Medicine & Health Sciences, University of Stellenbosch, Parow, South Africa.

Corresponding Author: Martin P. Schwellnus, Sport, Exercise Medicine and Lifestyle Institute (SEMLI) and Section Sports Medicine, Faculty of Health Sciences, University of Pretoria, Sports Campus, Burnett St, Hatfield, Pretoria 0020, South Africa (mschwell@iafrica.com).

The study was partially funded by a research grant from the International Olympic Committee (IOC) Research Centre (South Africa) at the University of Pretoria. The South African Medical Research Council (SAMRC) provided partial funding for the statistical analysis.

The authors report no conflicts of interest.

Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal's Web site (www.cjsportmed.com).

A. Rotunno: data collection, data interpretation, manuscript (first draft), and manuscript editing. M. Schwellnus: principle investigator, responsible for the overall content as guarantor, study concept, study planning, data collection, data interpretation, manuscript (first draft), manuscript editing, and facilitating funding. S. Swanevelder: study planning, data analysis including statistical analysis, data interpretation, and manuscript editing. E. Jordaan: study planning, data analysis including statistical analysis, data interpretation, and manuscript editing. D. C. Janse Van Rensburg: data interpretation, manuscript (first draft), and manuscript editing. W. Derman: study concept, study planning, data collection, data interpretation, and manuscript editing.

Received February 13, 2018

Accepted May 01, 2018

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INTRODUCTION

Health benefits of regular exercise are well established, and >150 minutes per week of moderate- to high-intensity exercise1–3 is universally recommended as an important component of a healthy lifestyle to prevent and treat noncommunicable disease.1,4–7 Not surprisingly, in the past 2 to 3 decades, participation in mass community-based endurance sports events (running, cycling, swimming, and triathlons) has seen a steady growth worldwide8 with notable increases in older participants.9 Recreational distance running remains one of the most popular forms of endurance exercise, and since 1976, there is a reported increase of >12-fold in overall participation numbers in distance races such as the marathon.

However, there is also equally strong evidence that moderate- to high-intensity exercise can acutely, and transiently, increase the risk of a range of acute medical complications during races.10,11 These complications include serious cardiac incidents12–16 and noncardiac complications typically related to severe fluid and electrolyte abnormalities (mainly hyponatremia),17–19 acute kidney injury and renal failure,20–23 exertional heat stroke,24–28 and gastrointestinal (GIT) bleeding.29 Risk factors associated with acute medical complications (cardiac and noncardiac) were recently reviewed,9 and one of the risk factors is the use of medication, immediately before or during races.9

The most common type of medication used by athletes is prescription and over-the-counter (OTC) analgesic and/or anti-inflammatory medication (AAIM).30 Analgesic/anti-inflammatory medication use during training, competition, and recovery is common practice in many athletes including Olympic athletes,31,32 Paralympic athletes,33 elite track and field athletes,34 football (soccer) players,35–38 athletes participating in multicoded sports events,39 college athletes,40 athletes participating in triathlon,41,42 and endurance cycling.43,44 Furthermore, the types of AAIM typically used in athlete populations are nonsteroidal anti-inflammatory drugs [(NSAIDs) oral, topical, and injectable forms], analgesics (paracetamol, opioids, and other nonopioids), anesthetics (injectable and transdermal), and other OTC medication.30

In distance runners, the prevalence of AAIM use immediately before or during races has only been reported in a few studies notably in ultra-marathon (>42.2-km race distances) runners,45–47 marathon (42.2 km) runners,29,45,46 half-marathon (21.1 km) runners,45 and amateur female runners.48 These studies consistently show a high prevalence of AAIM use immediately before or during a race that is the highest in ultra-marathon runners (60%-70%)45–47 compared with marathon and half-marathon runners (26%-49%)29,45,46 or female amateur runners (35%).48

This high prevalence of AAIM use in distance runners is of concern because there are well-documented serious adverse events (AEs) that are associated with AAIM use during endurance events. The AEs during exercise include increased risk of GIT injury,29,45,49,50 renal injury,29,51–55 cardiovascular side effects,29,50,53 and possible detrimental effects on the healing processes to damaged muscle, tendons, and bone.41,56 In 1 study among 3913 marathon runners, the overall incidence of self-reported AEs was 5 times higher (overall risk difference of 13%) in AAIM users, and this incidence increased significantly with increasing medication dose.29

The main limitations of studies that reported the prevalence of AAIM use in runners are selection bias (samples selected for the studies are not necessarily representative of the target populations), response rates that are either not reported45 or very low (11.3%)46 to moderate (56%),29 and with the exception in the 1 study among 3913 marathon runners,29 relatively small sample sizes.45,46,48 Furthermore, as far as we are aware, the factors associated with AAIM use in runners, immediately before or during races, are not well documented. In only a few studies, the reasons for AAIM use by athletes are reported and include pain relief from injury and related painful conditions such as exercise-associated muscle cramping (EAMC), injury prophylaxis, peer pressure, faster recovery, and the belief that AAIM use will result in earlier return to play or improve athletic performance.40–42,48

The purpose of this study is to determine the prevalence of AAIM use in half-marathon and ultra-marathon runners, the types of medication used, and to identify independent factors (runner demographics, race distance, running injury, EAMC history, and a history of underlying chronic medical conditions) that may be associated with AAIM use in these runners.

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METHODS

This study formed part of a series of ongoing Strategies to reduce Adverse medical events For the ExerciseR (SAFER) studies.57 We previously documented a high rate of acute medical complications in runners participating in the 2008 to 2011 Old Mutual Two Oceans Marathon races, including sudden death,11,58 and this precipitated the design and implementation of an online pre-race medical screening program for all race entrants from 2012 to 2015. In this postintervention period, all race entrants (n = 106 743) completed a pre-race medical screening questionnaire as part of the online registration process. Of these, 76 654 (71.8% of all race entrants) gave informed consent that their personalized medical data could be used for research purposes, and these runners were designated as participants for this study [male = 44 042 (57.5%) and female = 32 612 (42.5%)] (Table 1).

TABLE 1

TABLE 1

In the study group, compared with all entrants, there were equal proportions of runners by sex and age groups (Table 1). However, the proportion of study participants in the 21.1-km race category was significantly higher compared with all the race entrants (study participants = 61.4% and all race entrants = 60.7%) (0.7% higher; P = 0.0011) (Table 1).

Before the onset of the study, we obtained permission from the research ethics committees of the University of Cape Town (REC 009/2011) (REC 030/2013) and permission to complete the data collection, and the subsequent analysis of the results was obtained from the research ethics committee of the University of Pretoria (REC 433/2015).

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Online Pre-race Medical Screening Questionnaire

An online pre-race medical screening questionnaire or “self-assessment of risk” was developed, based on the European Society of Cardiology (ESC) and the European Association of Cardiovascular Prevention and Rehabilitation (EACPR) guidelines.59,60 The questionnaire was administered to race entrants from 2012 to 2015 and included the following categories of medical history: symptoms of cardiovascular disease (CVD), risk factors for CVD, and history of diagnosed chronic disease (CVD, respiratory, metabolic or hormonal, GIT, nervous system, renal or bladder, hematological or immune system, cancer, and allergies), general prescription medication use, medication use during racing, and a past history of collapse during racing. These factors are all associated with a possible increased risk of acute medical complications in moderate- to high-intensity exercise such as distance running.9

In the medical screening tool, runners were specifically asked to answer the following question related to AAIM use for injuries: “Have you ever in your running career used medicines to treat injuries in the week before or during a race—including anti-inflammatory drugs, cortisone (pills or injection), or pain killers?” In response to a “yes” answer to this question, runners were grouped as nonusers or users of AAIM (AAIM users = 10 140, 21.1 km = 4048, 56 km = 6092). Runners who responded with a “yes” answer were then asked to complete 2 additional questions related to (1) use of AAIM in the week before a race, or use of AAIM during races, and (2) the type of AAIM used (see Appendix A, Supplemental Digital Content 1, http://links.lww.com/JSM/A181). In the overall user group, we included runners who reported AAIM use (1) only in the week before races, (2) only during races, or (3) both in the week before and during races.

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Main Outcome Variables

Prevalence of AAIM use in race entrants: overall use, different types of AAIM use, and use 1 week before races or during races.

We describe the overall prevalence of AAIM use in race entrants (as a % of all race entrants in the study) and the prevalence of use of different types of AAIM (AIM such as NSAIDs and cortisone, and analgesic medication) by runners in 2 periods—the week before a race and during a race.

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Factors Associated With Analgesic/Anti-inflammatory Medication Use in Runners

In this study, we specifically wanted to investigate the factors associated with AAIM use in race entrants in the following 3 main categories of factors: (1) runner demographics (age, sex, and race distance), (2) a history of running injuries or EAMC, and (3) a history of risk factors for CVD, symptoms of CVD, and existing chronic disease [CVD, respiratory disease, endocrine disease, GIT disease, nervous system or psychiatric disease, kidney or bladder disease, hematological system disease, immune system disease, cancer, and allergies].

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Statistical Analysis

All data from the 2012 to 2015 runner and medical screening database were entered into an Excel spread sheet (Microsoft 2010) and then analyzed using the SAS 9.4 statistical program (SAS Institute Inc, Cary, North Carolina). The binary-scaled response variable was the response to the questions on medication use to treat injuries before or during a race (including anti-inflammatory drugs, cortisone, or pain killers). Because of the cross-sectional nature of the study, we used log-binomial regression to directly estimate risk ratios (RRs) for the main category risk factors. However, convergence problems may arise with binomial regression models; in this case, they may fail to provide an estimate of the RR. To avoid this, we approximated the relative risk by using the Poisson regression model with a robust error variance. The correlated structure of the data (a runner could run multiple years and have more than 1 injury in a year) was accounted for by using an unstructured correlation matrix. Risk ratios [95% confidence intervals (CIs)], also indicated as prevalence risk (PRs), were reported for all the results. The statistical significance level was 5%, unless specified otherwise.

Univariate regression models on all main categories of factors associated with AAIM use obtained the crude unadjusted RR (PRs and 95% CIs) of AAIM use for each factor separately. The multiple regression models, by main categories of injuries, symptoms, and chronic disease, adjusted the univariate PRs for sex, age category, and race type. Final multiple regression models included all significant main category risk factors, adjusted for sex, age category, and race distance. Crude numbers, prevalence, and 95% CIs are reported throughout.

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RESULTS

Overall Prevalence of Analgesic/Anti-inflammatory Medication Use (in the Week Before and/or During Races)

The overall prevalence of use of AAIM, in the week before and/or during races, in this population was 12.2% (95% CI, 12.0-12.5), and this was significantly higher in 56 km (18.6%, 95% CI, 18.0-19.1) compared with 21.1 km (8.3%, 95% CI, 8.1-8.6) race entrants (P < 0.0001).

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Prevalence of Different Types of Analgesic/Anti-inflammatory Medication Used in the Week Before a Race or During a Race

The prevalence of use of different types of AAIM used in the week before a race or during a race for all race entrants, 21.1-km race entrants, and 56-km race entrants is depicted in Table 2.

TABLE 2

TABLE 2

The main observation from these tables is that NSAIDs are the most frequent AAIM used (%, 95% CIs) by all race entrants, 21.1-km, and 56-km race entrants, both in the week before a race (all = 8.6%, 8.4-8.9; 21.1 km = 6.3%, 6.0-6.5; and 56 km = 12.8%, 12.4-13.3) and during races (all = 5.3%, 5.1-5.5; 21.1 km = 3.1%, 2.9-3.2; and 56 km = 9.2, 8.8-9.5). This is followed by analgesic use (mainly paracetamol) and less commonly, corticosteroid use (Table 2). The 56-km race entrants also consistently reported higher prevalence of use of all specific AAIM, compared with 21.1-km race entrants (Table 2).

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Factors Associated With Analgesic/Anti-inflammatory Medication Use in Race Entrants

Factors associated with AAIM use in race entrants were explored for 3 main categories of factors: (1) runner demographics, (2) a history of running injuries or EAMC, and (3) a history of chronic disease (risk factors for CVD, symptoms of CVD, and previously diagnosed chronic disease). Univariate regression models on all main categories of factors associated with AAIM use obtained the crude unadjusted prevalence risk (PR) for AAIM use in these 3 categories, and these data are provided in Supplemental Digital Content 2 (see Tables S1–S3, http://links.lww.com/JSM/A180). The unadjusted PR of AAIM use was significantly higher in female versus male runners (P = 0.0365), 56-km versus 21.1-km runners (P < 0.0001), and older age groups (41-50 years and >50 years) versus younger age groups (31-40 years and ≤30 years) (P < 0.0001) (see Table S1, Supplemental Digital Content 2, http://links.lww.com/JSM/A180) (unadjusted data).

Subsequently, factors independent of sex, race type, and age group were explored in a multiple regression model. The adjusted (by sex, age, and race type) PRs (with 95% CIs) and % of race entrants using AAIM by factors in our second (history of injuries and EAMC) and third categories (CVD symptoms, CVD risk factors, and chronic disease) of risk factors in the multiple regression model are depicted in Table 3.

TABLE 3

TABLE 3

A history of a running injury was associated with the highest prevalence risk (PR = 2.7; 95% CI, 2.6-2.9) (P < 0.0001) of AAIM use in race entrants. For more specific groups of running injuries, the prevalence risk of AAIM use varied between 2.0 to 2.4 (P < 0.0001) for race entrants reporting a history of muscle injuries, tendon injuries, and EAMC. There was also a significantly higher PR of AAIM use in race entrants who reported CVD symptoms, CVD risk factors, and chronic disease. A PR >2.0 was associated with a history of CVD symptoms and GIT disease (P < 0.0001), and a PR that varied between 1.5 and 1.9 was associated with a history of nervous system/psychiatric disease, kidney/bladder disease, CVD, respiratory disease, risk factors for CVD, allergies, endocrine disease, and hematological/immune disease (P < 0.0001). The PR of AAIM use was also significantly higher in entrants with a history of cancer (PR = 1.3) (P = 0.0003).

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DISCUSSION

The main findings of this study were: (1) in runners, the prevalence of AAIM use, either in the week before a race or during a race, was 12.2% (about 1 in 8 runners), and this was significantly higher in 56 km (18.6%; about 1 in 5 runners) compared with 21.1 km (8.3%; about 1 in 12 runners), (2) the most frequent type of medication used, both in the week before a race and during a race, was NSAIDs, followed by analgesics (mainly paracetamol), (3) independent factors (adjusted for sex, age group, and race distance) with the highest prevalence risk (PR) of AAIM use in race entrants were a history of running injuries (2.2-2.7 higher risk) or EAMC (2.0 times higher risk), and (4) novel independent factors associated with AAIM use in runners were symptoms of CVD, CVD risk factors, and a number of underlying chronic diseases (PR varied between 1.3-2.0 times higher risk).

The overall prevalence of AAIM use in our 56- and 21-km running population is considerably lower than previously reported use in ultra-marathon runners (60%-70%)45–47 and marathon or half-marathon runners (26%-49%).29,45,46 The precise reasons for this are not apparent but may be related to a number of factors including timing of the questionnaire administration, details of the questionnaire methodology used, selection bias in most previous studies, low-response rates in some previous studies, and considerable differences in the populations who were studied (ranging from multistage ultra-marathon runners to amateur female recreational runners). Therefore, we cannot, with confidence, compare our reported prevalence of AAIM use data with those reported in previous studies. However, we do acknowledge that our reported prevalence of AAIM use in 56-km runners is considerably lower compared with prevalence of AAIM use (%) in runners participating in multistaged ultra-marathon races over a number of days (70%45 and 60.5%47) and also in races that are considerably longer in duration than our 56-km race (67 km = 49.2% and 112 km = 60.3%).46 Longer race duration is a consistent factor associated with increasing AAIM use,45,46 and this also confirmed by data from our study showing a significantly higher prevalence of use in 56-km versus 21.1-km runners. However, AAIM use in our 56-km and 21.2-km running populations is still lower than the 49% reported for 42.2-km runners29 and 26% for 21.1-km runners,45 respectively. The precise reasons for higher prevalence of AAIM use in different populations of runners participating in races of the same duration require further study, and that includes the development of a consensus tool to measure and determine AAIM use in athletic populations. Although we report a lower prevalence of AAIM use in our population of runners, the dangers of AAIM use, which have been documented in a prospective study in runners,29 still warrant the same concern and attention to protect athlete health.

We found that NSAIDs were the most commonly used type of AAIM used before (8.6%) and during (5.3%) events, followed by paracetamol (before = 2.8%; during = 2.6%). A similar trend was observed in the 56-km versus 21.1-km races. This finding is consistent with all previously published data on the types of AAIM used by runners immediately before and during races,29,45–48 or by athletes participating in different sports.31–42

The main novel findings in our study are related to factors associated with AAIM use. The unadjusted PR of AAIM use in our population showed that female runners, older runners, 56-km versus 21.1-km runners, runners with a history of musculoskeletal injuries or EAMC, and runners with symptoms of CVD, risk factors for CVD, and those with a variety of underlying chronic diseases have a significantly higher risk of AAIM use. In the adjusted (for sex, age, and race distance) analysis, independent factors associated with AAIMs use were a history of musculoskeletal injuries or EAMC, and runners with symptoms of CVD, risk factors for CVD, and those with a variety of previously diagnosed chronic diseases. Notably, from our study, the highest PR for AAIM use was a history of running injuries. Previous studies have reported the possible reasons for AAIM use in athletes with injury and these include: pain relief, injury prophylaxis, peer pressure to participate, completing the race, faster recovery, and the belief that AAIM use will result in earlier return to play or improve athletic performance.40–42,48

Our finding that there is an increased risk of AAIM use in runners with a history of EAMC is novel. Although the etiology of EAMC is still under investigation, numerous factors are associated with EAMC and include increased exercise intensity (running speed) resulting in premature muscle fatigue,61,62 a history of a running injury,61 a history of pre-race muscle damage62 or injury,63 a history of muscle cramping,61,62 and possible genetic factors.64 The final common pathway of these factors is that they are all associated with increased motor neuron hyperexcitability.65 Exercise-associated muscle cramping presents as a painful involuntary muscle contraction, and it is therefore not surprising that AAIM use will be higher in these runners to prevent or treat EAMC during races. However, the precise relationship between AAIM use and EAMC requires further study.

Finally, we also identified that runners with a history of CVD symptoms, CVD risk factors, and a number of underlying chronic diseases have a significantly higher risk of AAIM use immediately before or during races. We are not aware of any previous data reporting this finding. A possible explanation is that the underlying chronic diseases may be associated with more musculoskeletal complaints, either from the underlying condition or from chronic medication that is prescribed in the treatment of chronic disease. For example, in patients with CVD and hypercholesterolemia, well-documented side effects of commonly prescribed medications such as statins are generalized muscle aches, tenderness, and weakness (broadly myalgia). This pain itself may encourage runners to take AAIM and predispose them to an increased likelihood of AAIM use during running. Another possible explanation is habitual pill-taking behavior. Chronic diseases frequently require daily doses of multiple tablets, and if a runner is in the habit of regularly taking tablets, there may be a lower threshold for AAIM consumption when pain is experienced. However, the precise reasons for the association between increased risk of AAIM use and CVD symptoms, CVD risk factors, and underlying chronic disease require further study.

We believe that our data are particularly important for race organizers and medical teams that are responsible for mass community-based running events. They need to be aware of the prevalence of AAIM use, types of medication consumed, and the profile of runners who use AAIM immediately before and during races because this will influence the likelihood of serious cardiovascular events,29,50,53 renal injury,29,51–55 or serious GIT injury29,45,49,50 during an event. Race organizers and medical teams could consider targeted educational interventions to reduce AAIM use and the subsequent risk of medical complications. Furthermore, as the profile of recreational endurance athletes participating in mass community-based events reflects an increasing older population, there may be an additional higher risk of AEs in those athletes who use AAIM and have underlying chronic disease.

The main strength of this study is that it is the largest study to examine the prevalence of use of AAIM use in recreational endurance runners. Furthermore, in contrast to previous studies in runners, selection bias is minimal, as we showed that the data set is representative of the athlete population studied and reflects the age and sex of all the race entrants in our population. The notable exception is a small but significant overrepresentation of 21.1-km runners in our population. A further strength of the study is that we used a multiple regression analysis to identify independent factors associated with AAIM use in an athlete's running career. As with all previous studies, the main limitation of this study is that the data are self-reported, and that the survey wording can affect the interpretation of the data, as in previous studies. We also acknowledge that not all potential variables associated with AAIM use could be included in our model, and that we cannot infer any causal relationships between AAIM use and the risk factors we identified because of the cross-sectional study design. Finally, in this study, we do not report on the relationship between AAIM use and adverse medical events over the 4-year study period, but this will be explored in future SAFER studies.

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SUMMARY AND CONCLUSIONS

In summary, the data from this study highlight the importance that race medical directors and their teams must be aware of the prevalence of AAIM use of runners during races, the types of AAIM used, associated factors, and the potential risk of AEs in runners participating in their events. We support initiatives to introduce a pre-race medical screening and educational program to create awareness of the dangers of AAIM use during endurance sports to reduce the prevalence of use and subsequent risk of AEs to ensure a safer race for the participants and responsible medical teams alike. An area for future research is to measure the effectiveness of such an intervention. Finally, it is the role of every health care professional to counsel athletes on the potential dangers and side effects of AAIM use, in particular NSAIDs, when competing in endurance sports events.

The Declaration of Helsinki: Permission to analyze the medical histories of the study participants was obtained from the research ethics committee of the University of Cape Town (REC 009/2011) (REC 030/2013) and the research ethics committee of the University of Pretoria (REC 433/2015). This study complied with the Declaration of Helsinki's ethical principles for conducting medical research involving human participants.

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Keywords:

medication use; analgesics; anti-inflammatory medication; running; chronic disease; risk factors

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