Objective To describe the incidence rate (IR) and illness burden (IB) at the Pyeongchang 2018 Paralympic Winter Games.
Methods A total of 567 athletes from 49 countries were monitored for 12 days over the Pyeongchang 2018 Games (6804 athlete days). Illness data were obtained daily from teams with (41 teams, 557 athletes) and teams without (8 teams, 10 athletes) their own medical support, through electronic data capturing systems.
Results There were 87 illnesses reported, with an illness IR of 12.8 illnesses per 1000 athlete days (95% CI 10.2 to 16.0) and IB of 6.8 days lost per 1000 athlete days (95% CI 3.4 to 13.5). The highest IR was reported for Para snowboard (IR of 19.7 [95% CI 12.0 to 32.2]). Illnesses in the respiratory system (IR of 4.1 [95% CI 2.9 to 5.9]; IB of 1.4 [95% CI 0.6 to 3.0]), skin and subcutaneous system (IR of 2.5 [95% CI 1.5 to 4.1]; IB of 0.6 [95% CI 0.1 to 2.9]), and eye and ocular adnexa (IR of 1.6 [95% CI 0.9 to 3.1]; IB of 0.5 [95% CI 0.1 to 3.3]) were the most common.
Conclusion This is the first study to report both the IR and IB in this setting. There was a high IR of illness in the new sport of Para snowboard. The respiratory system had both the highest IR and IB.
Statistics from Altmetric.com
What are the findings?
This was the first study to document both the incidence rate and burden of illness per 1000 athlete days at a Winter Paralympic Games.
The sport with the highest incidence rate of illness was Para snowboard, and illnesses were most commonly reported in the skin and subcutaneous system in this sport.
Illnesses were most common in the respiratory system, skin and subcutaneous system, and eye and ocular adnexa.
The burden of illness was highest in the respiratory system.
How might it impact on clinical practice in the future?
The data presented in the current study illustrate the physiological systems and sports most at risk for illness, and can be used to inform coaches and organisations in their measures to avoid illness in their teams at Paralympic Winter Games.
These data also provide the basis for organised illness prevention programmes in sports and organisations.
In recent years, there has been an increase in the number of studies, development of systems and improved data collection methods regarding the surveillance of illness in athletes with impairment at major international multisport competitions. The International Paralympic Committee (IPC) has prioritised epidemiological research regarding the protection of the health of the Para athlete and has committed to ongoing research in this area.1–5
The first robust epidemiological investigation of illness in athletes with impairment in a Paralympic Games setting was conducted at the London 2012 Paralympic Games.2 5 The London 2012 and subsequent Rio 2016 Summer Games studies documented an incidence rate (IR) of illness of 12.8 (95% CI 12.1 to 14.2)1 and 10.0 (95% CI 9.2 to 10.9)4 illnesses per 1000 athlete days, respectively. The first such investigation in a Winter Games setting was conducted at the Sochi 2014 Paralympic Winter Games. The IR of illness was 18.7 (95% CI 15.1 to 23.2), indicating a higher risk of illness in the Winter Games setting.6 At Sochi 2014, the sport with the highest IR of illness was wheelchair curling (IR of 20.0 [95% CI 10.1 to 39.6]), and there were more illnesses reported in athletes aged 35–63 years (IR of 22.6 [95% CI 16.0 to 31.9]). The physiological systems most affected by illness were the respiratory system (IR of 5.6 [95% CI 3.8 to 8.0]), eye and ocular adnexa (IR of 2.7 [95% CI 1.7 to 4.4]), and digestive system (IR of 2.4 [95% CI 1.4 to 4.2]).6
Longitudinal illness surveillance is important via repeated measures at multiple Games, or out of the Games setting, to indicate which areas of the health of the Para athlete require attention, intervention and further monitoring.7 This is one in a series of studies required to further elucidate the patterns of illness in the Paralympic Games setting.
We aimed to document the IR and burden of illness at the Pyeongchang 2018 Paralympic Winter Games. This study aimed to report overall illness IR, illness IR per sport, type of illness and physiological systems affected by the illness in the 3-day precompetition and 9-day competition period of the Games.
The present study was a component of a larger ongoing epidemiological study of both the Summer and Winter Paralympic Games, which commenced with the London 2012 Paralympic Games. This study involved prospective monitoring of the epidemiology of illness during the 3-day precompetition period and 9-day competition period of the Pyeongchang 2018 Paralympic Winter Games. Athletes participated in five categories of sports, namely Para alpine skiing, Para snowboard, Para Nordic skiing (combining Para cross-country skiing and Para biathlon), Para ice hockey and wheelchair curling.
The current study was conducted by members of the IPC’s Medical Committee.
Teams who had their own medical support at the Games used the web-based injury and illness surveillance system (WEB-IISS) in order to record illnesses (online supplementary table 1), which has been successfully used at the London 2012, Sochi 2014 and Rio 2016 Paralympic Games.1 4 6 A more detailed description of the WEB-IISS can be found in the previous literature.6 Introductory information about the study was provided prior to the Games via email to all National Paralympic Committees chefs de mission (n=49), and further communication was sent to all team physicians of the teams competing at the Games (n=41). During the precompetition period of the Games, a medical briefing was held where team physicians were provided with both detailed information about the study, as well as individualised training sessions on how to use the WEB-IISS. Daily data entry compliance was incentivised by the provision of a basic tablet computer (Samsung, Seoul, Korea) to each participating country that had medical support at the Games, which could be used for data entry. Countries with accompanying medical staff who had less than five athletes in their team reported their data through the same portal used on the tablets, via laptop computers and wireless internet connections within the Paralympic Village.
For teams who did not have accompanying medical staff, illness data were captured via the Pyeongchang Organizing Committee for the 2018 Olympic & Paralympic Winter Games (POCOG) customised surveillance system in the local organising committee’s venue and polyclinic facilities. This system was also used to capture all admissions to peripheral hospitals, radiology services, medical and pharmacy encounters, and specialist services at both the polyclinic and venues. It additionally captured visits from athletes with their own medical support services who chose to report their illnesses to the polyclinic. After the closing of the Games, these data were de-linked and processed to remove duplicate entries and data from non-athletes. Furthermore, physiotherapy, non-ophthalmological routine eye examinations (optometry) or orthopaedic bracing visits to the polyclinic during this time were excluded. These data were then integrated into the WEB-IISS illness master spreadsheet for analysis. Thus, the present study constitutes all illnesses presented to team physicians and local polyclinic staff during the Games period of the Pyeongchang 2018 Paralympic Winter Games.
Definition of illness
An illness that should be reported to the team physician was defined as ‘any athlete requiring medical attention for an illness regardless of the consequences with regard to absences from training or competition’, and more specifically defined as ‘any newly acquired illness as well as exacerbations of pre-existing illness that occurred during training and/or competition in the pre-competition or competition periods of the Pyeongchang 2018 Paralympic Winter Games’.6
Calculation of athlete days
Team size was calculated from the masterlist of athletes attending the Games, which was published by the IPC prior to the Games, as all team sizes (both WEB-IISS and polyclinic-monitored athletes) came from the same source and were seen to be reliable in comparison with physician-reported team size. Athlete days were calculated by multiplying the total term days (3-day precompetition and 9-day competition period) multiplied by the team size as published by the IPC. These data constituted denominator data for the calculation of illness IR. The provision of accurate denominator data is critical to correct analysis and reporting of the epidemiology of illness in this international multisport setting, with multiple teams.
Calculation of illness IR
The illness IR was reported as illnesses per 1000 athlete days (95% CI). Athlete days were reported separately by sex, age group, sport and Games periods. Total illnesses as well as illnesses in different sports and physiological systems were reported. The percentage of athletes with an illness was calculated by dividing the total number of athletes with an illness by the total number of athletes competing in the relevant subgroup. This was then multiplied by 100.
Calculation of time loss and illness burden
Time loss as a result of illness was estimated by the team physician at the time of reporting the illness. The doctors were then able to log into the system at a later stage and modify the entry to represent the actual days lost by the athlete.
The illness burden (IB) was determined by calculating the number of days lost per illness, per 1000 athlete days, thus accounting for both frequency (IR) and severity (time loss) of illness. The IB was expressed as days lost per 1000 athlete days (95% CI).8 9
Time loss data (and subsequent IB calculations) were only available for illnesses logged on the WEB-IISS. Thus, the time loss and IB denominator data represented 557 athletes (83.6%) who had their own medical support (6684 athlete days).
Statistical analysis of the data
All data (WEB-IISS and polyclinic data sets) were in the form of counts (ie, the number of illnesses each athlete reported). A description of the impairment categories of athletes with an illness was presented as the percentage of the total ill athlete cohort (%) only. This is because the impairment data of the total athlete cohort participating at the Games were not available and the IRs could not be reported for impairment categories. Some athletes participated in more than one sport and/or more than one event; the primary sport of the athlete (determined from the IPC masterlist of athletes attending the Games) was used in the analysis. Where some athletes incurred multiple illnesses during the total Games period, each of these was reported as distinct illnesses. Descriptive statistical analyses were reported, including the number of athletes participating in five categories of sport (Para alpine skiing, Para snowboard, Para Nordic skiing [combining Para cross-country skiing and Para biathlon], Para ice hockey and wheelchair curling), the number of athletes competing by age (12–25 years, 26–35 years and 35–67 years) and sex (male or female), the number of reported illnesses, and the number and percentage of athletes with an illness. Generalised linear Poisson regression modelling (multiple independent models developed with one independent variable each; SAS V.9.4) was used to model the number of reported illnesses overall, as well as the number of illnesses for physiological systems affected by an illness, and were corrected for overdispersion and including the independent variables of interest. All results reported were from univariate Poisson models, and included a scale parameter, due to some modest overdispersion in the Poisson models. No inclusion of covariables in the models was made. Illness IR and IB were reported per 1000 athlete days (including 95% CI). The IR of illness was reported by sex, age group, type of sport and physiological system affected by illness, and the IB for physiological system affected.
The present study details all illnesses presented to team physicians and local polyclinic staff during the precompetition and competition periods of the Pyeongchang 2018 Paralympic Winter Games. The total number of countries attending the Games was 49, representing 567 athletes constituting 6804 athlete days. The complete cohort of athletes at the Games was monitored in this study. There were 41 teams (83.6% of all teams) representing 557 athletes (6684 athlete days) who had their own medical support, while 8 countries (16.4% of all teams) representing 10 athletes (120 athlete days) used only the local polyclinic medical facilities. If an athlete monitored on the WEB-IISS also used polyclinic services and the illnesses recorded were the same, only the WEB-IISS encounter was included.
There were 433 male and 134 female athletes monitored in the study. The mean (±SD) age of all athletes in this study was 32.1±10.3 years. The total number of athletes and the sex and age distribution in five categories of sports, namely Para alpine skiing, Para snowboard, Para Nordic skiing (combining Para cross-country skiing and Para biathlon), Para ice hockey and wheelchair curling, are presented in table 1.
IR of illness by sport
Table 2 presents the total number of illnesses, as well as the illnesses reported in five categories of sports. The total number of illnesses recorded in all sports was 87 (65 WEB-IISS, 22 polyclinic) in 77 athletes (13.6% of all athletes at the Games), with an IR of 12.8 per 1000 athlete days (95% CI 10.2 to 16.0). There was a higher IR of new illnesses (IR of 11.3 [95% CI 8.9 to 14.4]) compared with recurrent illnesses (IR of 1.5 [95% CI 0.7 to 2.9]). The highest total number of illnesses was recorded in the sports of Para Nordic skiing (23 illnesses in 20 athletes) and Para ice hockey (23 illnesses in 21 athletes), although the sport of Para snowboard had the highest IR of 19.7 illnesses per 1000 athlete days (95% CI 12.0 to 32.2). The lowest IR was recorded for wheelchair curling, where five illnesses were reported in five athletes (IR of 6.9 [95% CI 2.8 to 17.3]). There were no significant differences in IR between the sports.
IR of illness by sex and age group
The IR of illness by sex and age group is presented in table 3. There were no significant differences in IR between male and female athletes, and between age groups.
IR of illness in the precompetition (3 days) and competition period (9 days)
There were 28 illnesses recorded in 25 athletes (IR of 16.5 [95% CI 10.9 to 24.9]) during the precompetition period and 59 illnesses recorded in 54 athletes (IR of 11.6 [95% CI 8.8 to 15.1]) during the competition period of the Pyeongchang 2018 Paralympic Winter Games (table 4). There was no significant difference of IR of illness between these two Games periods.
IR of illness for each physiological system
The physiological systems affected by illness are presented in table 5. The respiratory system had the highest number of illnesses reported, with 28 illnesses reported in 28 athletes (IR of 4.1 [95% CI 2.9 to 5.9]). The second most commonly affected system was the skin and subcutaneous system with 17 illnesses reported in 16 athletes (IR of 2.5 [95% CI 1.5 to 4.1]). The eye and ocular adnexa (surrounding tissues) had an IR of 1.6 (95% CI 0.9 to 3.1), with 10 athletes reporting 11 illnesses.
Illness by impairment
Table 6 depicts the impairment profiles of 59 athletes with illnesses, whose data were captured on the WEB-IISS. Illnesses provided by the polyclinic did not provide impairment details of the ill athletes. Among the 59 athletes, there were 26 athletes with limb deficiency (44%), followed by 16 with spinal cord injury (27.1%).
Time loss and burden of illness
Of the illnesses reported using the WEB-IISS during the Games period (6684 athlete days), 27.7% of the illnesses required one or more days of exclusion from training or competition, while 72.3% of illness on the WEB-IISS required no time loss from training or competition.
There were 18 illnesses that required one or more days of absence from training/competition. The total days lost were 44, with an IB of 6.8 days lost per 1000 athlete days (95% CI 3.4 to 13.5). The physiological system with the highest IB was the respiratory system (9 days lost; IB of 1.4 [95% CI 0.6 to 3.0]), followed by the skin and subcutaneous system (IB of 0.6 [95% CI 0.1 to 2.9]). The eye and ocular adnexa had an IB of 0.5 (95% CI 0.1 to 3.3), and the digestive system had a time loss burden of 0.3 days lost per 1000 athlete days (95% CI 0.0 to 2.0).
The present epidemiological study is the first to document both the IR and IB per 1000 athlete days in athletes with impairment at a major multisport Winter competition and constitutes a significant addition to the data set of illnesses in this setting.
Para snowboard, a risk for all illnesses and specifically skin illnesses
The first important finding of this study was that the relatively new sport of Para snowboard was identified as a high risk for all illnesses, and specifically illnesses in the skin and subcutaneous system.
The skin and subcutaneous system was affected by a high rate of illness (IR of 2.5 [95% CI 1.5 to 4.1]) for all athletes at these Games. The conditions reported included stump/prosthesis interface pathology, stump/skin subcutaneous pain, skin rash, skin breakdown and abscesses. Specifically, athletes in the sport of Para snowboard reported more skin and subcutaneous illnesses (35% of all illnesses in Para snowboard athletes; IR of 6.9 [95% CI 3.1 to 15.6]) as opposed to skin injuries, lacerations and abrasions, which are reported as injuries on the WEB-IISS and will be described in a subsequent paper. The finding that stump/prosthesis interface pathology constituted a large component of these reported illnesses indicates the need for specific tailored interventions to target skin care in the groups of athletes with impairment competing in Para snowboard, predominantly athletes with limb deficiency, who constituted the largest number of ill athletes at these Games (44%).5
Respiratory system still the highest at risk for illness
The respiratory system was once again the system at the highest risk for illness at these Games (IR of 4.1 [95% CI 2.9 to 5.9]). This finding has been shown in previous studies and has been implicated in both Para and able-bodied athletes in both Summer and Winter Games settings.2 4–6 10–12
The burden of illness in the Para athlete population
A novel contribution of this study was the addition of IB calculations. In recent years, epidemiological injury and illness research has moved away from solely reporting IR of illness, and towards a more complete understanding of the consequences of the reported condition. This has resulted in the description of both the number and subsequent burden of illnesses in studied populations, reported as time lost (severity) per illness.8 The overall IB at the Pyeongchang 2018 Games was 6.8 days lost per 1000 athlete days (95% CI 3.4 to 13.5), and the system with the highest IB was the respiratory system (IB of 1.4 [95% CI 0.6 to 3.0]). It is interesting to note that the respiratory system had both a high IR as well as high severity of illnesses, resulting in the highest burden. This is in accordance with previous studies which indicated respiratory illnesses pose a high risk to athletes during sporting activities.2 4–6 11–13
Previous research in the sporting realm has shown injury and IB in athletes; however, most of these studies have been conducted in team sports and use the ‘athletes at risk’ method, which estimates exposure time as ‘the number of players on the field multiplied by the number of game-hours that the team has played’, and reports illnesses per 1000 player hours.8 13–20 This study has been conducted according to the ‘athlete participation’ method, which assumes that ‘one athlete is participating in one practice or game’ and reports illnesses per 1000 player days.9 As a result, comparison with these studies in sports which report illnesses in very high-risk team sports with different denominator statistics is not possible. This study constitutes the first study to report IB in this population using this method.
The eye and ocular adnexa are at risk for illness in a Winter setting
A novel finding at the Sochi Games was the high IR of illness in the eye and ocular adnexa (surrounding tissues, IR of 2.7 [95% CI 1.7 to 4.4]).6 This finding has been confirmed in the current study (IR of 1.6 [95% CI 0.9 to 3.1], IB of 0.5 [95% CI 0.1 to 3.3]). The ocular pathologies reported by the team physicians and the POCOG (polyclinic) ophthalmologists for this system included allergic conjunctivitis, corneal erosion, degenerative myopia, dry eye and ocular hypertension, indicating a more diverse group of eye conditions in this setting, which in turn indicates factors other than sunburn and snow glare should be considered. These findings warrant further detailed and longitudinal (continuous) investigation within a Winter sport athlete cohort; however, it may be important to note that some of the athletes who may have reported these conditions were visually impaired, and thus a pre-existing condition may be present.
Lower rate of illness at Pyeongchang 2018 compared with Sochi 2014
It is interesting to note that the overall IR of illness was lower at the Pyeongchang 2018 Games compared with the Sochi 2014 Games (IR of 18.7 [95% CI 15.1 to 23.2]).6 Although a full analysis of this difference was not possible in the current study, a detailed analysis is planned to investigate this decrease in reported illnesses in a Winter setting and determine factors relating to the observed difference.
Strengths and limitations of the study
A strength of the current study was that the data collection system was upgraded prior to these Games, so that medical officers could alter the days lost after the initial logging of the illness or injury. This facility was kept open for alterations to the time loss data to be made by the team physicians for a period of 2 weeks following the conclusion of the Games.
A limitation of the present study was that two electronic sources were used for data collection (WEB-IISS and polyclinic entries). The polyclinic data collection did not collect as much detailed data as the WEB-IISS. It is suggested that all athletes be covered on the WEB-IISS at future editions of the Games, or that the local organising committee system be expanded to include the same variables as the WEB-IISS. There was a relatively small total number of illnesses and ill athletes in the present study, which does not allow for complex multivariate statistical analysis. Furthermore, although this study captured impairment data from athletes who reported an illness, we did not know the entire cohort’s impairment details, limiting the conclusions drawn about impairment in the present study.
Summary and conclusion
In summary, the present study was the second large data set to present illnesses per 1000 athlete days at a Paralympic Games. We report a high IR of illness in the new sport of Para snowboard, specifically illnesses in the skin and subcutaneous system. A novel finding of this study was the addition of IB calculations, which showed that the respiratory system has both a high IR and IB. Using these baseline data, further studies will investigate the difference in illness profile of the Sochi 2014 and Pyeongchang 2018 Games, and the factors related to this difference.
This study was approved and supported by the IPC. The authors would like to thank the POCOG staff, as well as the NPC medical staff, whose input was pivotal to the success of this study.
Twitter The burden of #athlete #illness at the #PyeongChang2018 @Paralympics
Contributors All authors have contributed to the development, application and write-up of the current study.
Funding Funding for this study was provided by the IOC Research Centre South Africa grant and International Paralympic Committee research support.
Competing interests All authors have declared competing interests.
Patient consent Not required.
Ethics approval Research ethical approval was granted by the University of Brighton (FREGS/ES/12/11) and Stellenbosch University (N16/05/067) research ethics committees before research activities were conducted. During the registration process, consent was obtained from all athletes for the use of de-identified medical data gathered during the Games.
Provenance and peer review Not commissioned; externally peer reviewed.
If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.