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1
DermanW, etal. Br J Sports Med 2017;0:1. doi:10.1136/bjsports-2017-098039
High precompetition injury rate dominates the injury
profile at the Rio 2016 Summer Paralympic Games: a
prospective cohort study of 51 198 athletedays
Wayne Derman,1 Phoebe Runciman,1 Martin Schwellnus,2 Esme Jordaan,3
Cheri Blauwet,4 Nick Webborn,5 Jan Lexell,6,7,8 Peter van de Vliet,9
Yetsa Tuakli-Wosornu,10 James Kissick,11 Jaap Stomphorst12
Original article
To cite: DermanW,
RuncimanP,
SchwellnusM, etal.
Br J Sports Med Published
Online First: [please include
Day Month Year]. doi:10.1136/
bjsports-2017-098039
For numbered affiliations see
end of article.
Correspondence to
Professor Wayne Derman,
Institute of Sport and Exercise
Medicine, Department of
Surgical Sciences, Faculty of
Medicine and Health Sciences,
Stellenbosch University, South
Africa; ewderman@ iafrica. com
Accepted 12 September 2017
ABSTRACT
Objectives To describe the incidence of injury in the
precompetition and competition periods of the Rio 2016
Summer Paralympic Games.
Methods A total of 3657 athletes from 78 countries,
representing 83.4% of all athletes at the Games,
were monitored on the web-based injury and illness
surveillance system over 51 198 athlete days during
the Rio 2016 Summer Paralympic Games. Injury data
were obtained daily from teams with their own medical
support.
Results A total of 510 injuries were reported during
the 14-day Games period, with an injury incidence rate
(IR) of 10.0 injuries per 1000 athlete days (12.1% of
all athletes surveyed). The highest IRs were reported
for football 5-a-side (22.5), judo (15.5) and football
7-a-side (15.3) compared with other sports (p<0.05).
Precompetition injuries were significantly higher than in
the competition period (risk ratio: 1.40, p<0.05), and
acute traumatic injuries were the most common injuries
at the Games (IR of 5.5). The shoulder was the most
common anatomical area affected by injury (IR of 1.8).
Conclusion The data from this study indicate that (1)
IRs were lower than those reported for the London 2012
Summer Paralympic Games, (2) the sports of football
5-a-side, judo and football 7-a-side were independent
risk factors for injury, (3) precompetition injuries had a
higher IR than competition period injuries, (4) injuries
to the shoulder were the most common. These results
would allow for comparative data to be collected at
future editions of the Games and can be used to inform
injury prevention programmes.
INTRODUCTION
Paralympic sport continues to grow with increased
popularity among competitors and spectators alike.
Indeed, the Rio 2016 Summer Paralympic Games
saw the largest cohort of athletes participating at
this pinnacle event, namely 4378 athletes competing
in 22 sports.1 The protection of the health of the
athlete and efforts to reduce both injury and illness
in this population remain foremost on the agenda
of the International Paralympic Committee (IPC)2
and ongoing efforts to collect epidemiological data
to better inform injury prevention programmes has
remained a strong focus.3–8
It is important that before comprehensive
injury prevention programmes can be instituted,
adequate baseline data must be collected to allow
for the eventual determination of the success of
implemented prevention strategies.9 10 The first
large prospective study of injury epidemiology in
athletes with impairment, that expressed injury
rates and injury proportions per 1000 athlete days,
was reported following the London 2012 Summer
Paralympic Games.6 7 In that study, 633 injuries
were reported in 10.9% of the total number of
athletes monitored over the Games period. Further-
more, the injury incidence rate (IR) was 12.7 (95%
CI 11.7 to 13.7) injuries per 1000 athlete days.
The incidence of injury was highest in the sports
of football 5-a-side (IR of 22.4 (95% CI 14.1 to
33.8)),11 goalball (IR of 19.5 (95% CI 13.2 to
27.7)) and Para powerlifting (IR of 19.3 (95% CI
14.0 to 25.8)).12 Furthermore, the most commonly
affected anatomical area was the shoulder (IR of 2.1
(95% CI 1.7 to 2.6)), which is in accordance with
previous literature describing the epidemiology of
injury in both the Summer and Winter Paralympic
Games settings.5 13 14 Additionally, acute injuries
were the most commonly reported injury in terms
of onset (IR of 6.3 (95% CI 5.6 to 7.2)).
The aim of this study was to establish further
baseline data regarding the incidence of injury
in a Summer Paralympic Games setting.5 6 This
study described the profile of injuries, including
factors associated with injury risk, in a cohort of
3657 athletes whose attending physicians used the
web-based injury and illness surveillance system
(WEB-IISS) at the Rio 2016 Summer Paralympic
Games. Furthermore, the data presented in this
study, in combination with the data gathered from
the London 2012 Summer Paralympic Games, allow
for comparative data to be used when following
the efficacy of longitudinal injury prevention
programmes and specific prevention programmes
at future editions of the Summer Games.
METHODS
Setting
This study was conducted by members of the IPC
Medical Committee as part of the ongoing prospec-
tive study examining injury and illness epidemi-
ology in both the Summer and Winter Paralympic
Games settings and was conducted during the
3-day precompetition period and 11-day compe-
tition period of the Rio 2016 Summer Paralympic
Games.
2DermanW, etal. Br J Sports Med 2017;0:1. doi:10.1136/bjsports-2017-098039
Original article
Participants
Before research activities were initiated, approval was granted by
the University of Brighton (FREGS/ES/12/11) and Stellenbosch
University (N16/05/067) Research Ethics Committees. Informed
consent was obtained for the use of deidentified data from all
athletes during registration for the Games.
The present study used the WEB-IISS, which was successfully
implemented at both the London 2012 Summer Paralympic
Games and Sochi 2014 Winter Paralympic Games. The system
was designed for teams with their own medical support at the
Games. A more detailed description of the WEB-IISS can be
found in the previous literature.6
The organising committee medical facilities were used
predominantly by countries who did not have their own medical
support. However, given that the WEB-IISS was not used by
the Rio local organising committee, we were unable to obtain
reliable data regarding injuries in this athlete group. Therefore,
data regarding injury collected at the Rio organising committee
polyclinic and other medical facilities could not be included in
this study.
The study was promoted by providing introductory informa-
tion via email to all National Paralympic Committees (NPCs)
chefs de mission (n=160) and further communication was sent
to all attending Chief Medical Officers and team physicians of
the teams competing at the Games (n=81). Detailed informa-
tion about the study was provided to the team physicians of all
delegations at the medical briefing held during the precompe-
tition period of the Games and through individualised training
sessions at the polyclinic facility. Compliance from participating
team medical staff was facilitated by the provision of a tablet
computer (Samsung, Korea) for data entry. This was provided
to each participating country that had more than five athletes
competing at the Games. The remainder of the countries with
accompanying medical staff reported their data within the
Paralympic Village, via laptop computers and wireless internet
connection, through the same portal used on the tablets.
Data collection
Athlete information (age, sex and sport) was obtained from an
IPC database of competitors. Information gathered from the
team physicians with regard to the injury to be captured on the
WEB-IISS included the chronicity of the injury, mechanism of
acute and acute on chronic injuries, contributing factors to the
injury, stage of the Games in which the injury occurred, time
of occurrence of the injury (training or competition), protective
gear worn by the athlete, date of onset of symptoms, decision to
return to play, severity of the injury, special investigations used
in the assessment of the injury, primary anatomical area injured,
final diagnosis, anticipated time loss as a result of the injury and
the impairment type and class of the athlete.6 A new aspect of this
study was the inclusion of specific questions regarding concus-
sion, which were posed to the physician if they reported a head,
face or neck injury. All data were linked for statistical analyses
and subsequently delinked to provide a deidentified database.
Definition of injury
The general definition accepted for reporting an injury was
described as ‘any athlete experiencing an injury that required
medical attention, regardless of the consequences with respect
to absence from competition or training’.6 An injury was specif-
ically defined as ‘any newly acquired injury as well as exacerba-
tions of pre-existing injury that occurred during training and/
or competition of the Games period of the Rio 2016 Summer
Paralympic Games’. Acute traumatic, acute on chronic and
chronic injuries were reported. An acute traumatic injury was
defined as ‘an injury that was caused by an acute precipitating
traumatic event’. An acute on chronic injury was defined as ‘an
acute injury in an athlete with symptoms of a chronic injury
in the same anatomical area’. A chronic (overuse) injury was
defined as ‘an injury that developed over days, weeks or months
and was not associated with any acute precipitating event’.6
Calculation of athlete days
Team size was captured per day by each team’s physician at the
same time as registration of any injuries. However, an analysis
of these data showed very little variation from each country’s
team size as published in the IPC master list of athletes attending
the Games. These data were used as denominator data for the
calculation of IR per 1000 athlete days. Accurate denominator
data are essential to correct reporting and analysis of the epide-
miology of injuries in this setting, with multiple teams with
constantly changing team sizes.
Calculation of the injury incidence rate and injury proportion
Injury IR was calculated as injuries per 1000 athlete days. The
number of athlete days was reported separately by precompeti-
tion and competition periods, sport, age-group and sex. The IR
per 1000 athlete days was reported for all injury types, onset
of injury as well as injuries in different sports and anatomical
areas. The proportion of athletes with an injury refers to the
percentage of athletes reporting an injury and was calculated as
follows: number of athletes with an injury/the total number of
athletes competing in the relevant subgroup multiplied by 100.
Statistical analysis of the data
Standard descriptive statistical analyses were reported for each
injury outcome, including number of athletes participating, the
number of athlete days, number of injuries, number and propor-
tion of athletes with an injury. For the overall injury outcome,
descriptive statistics were reported by period, sport discipline,
age group (12–25 years, 26–34 years and 35–75 years) and sex
of the athlete (male or female).
As some athletes participated in more than one sport and/
or more than one event, the primary sport of the athlete was
used (track cycling and road cycling were combined due to small
numbers of participating athletes). Where athletes incurred
multiple injuries during the 14 days, each injury was reported as
a distinct injury encounter. Thus, the outcome was in the form
of counts, that is, the number of injuries each athlete reported.
A number of outcomes were considered in the analysis, namely
precompetition/competition injuries (period), acute traumatic/
acute on chronic/chronic injuries (onset) and various anatomical
areas of injury (lower limb, upper limb, head/neck/face, chest/
trunk/abdomen, spine and other areas of injury). Details of the
analysis of injuries by anatomical area were restricted to sport
related injuries (n=440) and excluded the non-sport-related
injuries (n=70).
Multiple regression analysis was performed to determine
whether the sports identified as having significantly higher
IRs were also independent risk factors for injury in this athlete
cohort. The model included four sport discipline categories: (1)
football-5-a-side and football-7-a-side, (2) judo, (3) wheelchair
basketball, wheelchair fencing and wheelchair rugby and (4) all
other sport disciplines. These sport groupings were determined
by the IRs in grouped sports, sex differences between the sports
3
DermanW, etal. Br J Sports Med 2017;0:1. doi:10.1136/bjsports-2017-098039
Original article
(footballs restricted to male athletes) and similarities in athlete
profile within sports (wheelchair sports).
Generalised linear Poisson’s regression modelling was used
to model the number of injuries for each injury outcome and
was corrected for overdispersion and included the indepen-
dent variables of interest (sport discipline, age category, sex).
Results were reported as injury IRs per 1000 athlete days
(IR with 95% CIs). Results for injury IRs were reported by
period, onset of injury, sex, age group and sport discipline. For
the comparison between the London and Rio injury IRs, the
correlation for athletes competing in both games could not be
built into the model since we did not have information linking
the athletes who competed at both Games. Results for impair-
ment data were reported via total number of injuries (%) only,
as the impairment data of all the athletes participating at the
Games were not available.
RESULTS
Participants
This study details the injuries reported by the team physicians
of countries who had their own medical support. Of these
countries, 78 countries chose to participate in the study and
three chose not to participate. During the total Games period,
3657 athletes were monitored for a period of 51 198 athlete
days. This athlete sample represented 48.8% of all countries
participating at the Games (160 teams) and yet represented
83.5% of the total number of all athletes at the Games (4378
athletes).
A description of the number of athletes per sport, sex of
the athletes and age group of the athletes is presented in
table 1. Most athletes were male (62%) and older than 25
years (73%). The sports with the highest number of athletes
competing were Para athletics (24%), Para swimming (13%)
and wheelchair basketball (6%). The sports of football
5-a-side and football 7-a-side were only participated in by
male athletes.
Overall incidence of injury and proportion of athletes injured
The total number of injuries incurred by 441 athletes was 510.
Therefore, the overall incidence of injury at the Rio 2016
Summer Paralympic Games was 10.0 injuries per 1000 athlete
days (95% CI 9.1 to 10.9). The proportion of the total number
of athletes being monitored on the WEB-IISS with an injury
was 12.1% (males=11.4%, females=13.2%) (table 2).
Table 1 Number of athletes participating in each sport at the Rio 2016 Summer Paralympic Games
Sport All athletes Females Males Age 12–25 Age 26–34 Age 35–75
All 3657 1389 2268 996 1320 1341
Archery 113 48 65 10 25 78
Boccia 99 30 69 23 34 42
Canoe 52 26 26 12 17 23
Cycling (track and road) 204 66 138 25 55 124
Equestrian 71 55 16 11 22 38
Football 5-a-side 70 0 70 23 36 11
Football 7-a-side 112 0 112 52 51 9
Goalball 102 54 48 34 46 22
Judo 115 41 74 26 60 29
Para athletics 894 354 540 294 354 246
Para powerlifting 141 62 79 13 50 78
Para swimming 492 217 275 287 141 64
Rowing 88 44 44 13 28 47
Sailing 76 15 61 3 16 57
Shooting Para sport 130 43 87 8 19 103
Sitting volleyball 127 70 57 22 46 59
Table tennis 223 78 145 43 68 112
Triathlon 58 29 29 10 20 28
Wheelchair basketball 228 96 132 49 107 72
Wheelchair fencing 72 30 42 12 34 26
Wheelchair rugby 96 2 94 8 52 36
Wheelchair tennis 94 29 65 18 39 37
Table 2 Incidence of injury by sex and age group for athletes competing at the Rio 2016 Summer Paralympic Games
Sex/age group
(years)
Total number of injuries
(percentage of total number
of injuries)
Number of athletes
with an injury
Total number of
athletes competing
Total number of
athlete days
Proportion of athletes
with an injury
Injury incidence rate:
number of injuries/1000
athlete days (95% CI)
All 510 (100%) 441 3657 51 198 12.1 10.0 (9.1 to 10.9)
Female 208 (40.8%) 183 1389 19 446 13.2 10.7 (9.3 to 12.3)
Male 302 (59.2%) 258 2268 31 752 11.4 9.5 (8.5 to 10.7)
Age 12–25 120 (23.5%) 104 996 13 944 10.4 8.6 (7.2 to 10.3)
Age 26–34 192 (37.6%) 168 1320 18 480 12.7 10.4 (9.0 to 12.0)
Age 35–75 198 (38.8%) 169 1341 18 774 12.6 10.6 (9.2 to 12.1)
4DermanW, etal. Br J Sports Med 2017;0:1. doi:10.1136/bjsports-2017-098039
Original article
Incidence of injury by sex and age group
The overall incidence of injury by sex (female, male) and age
group (12–25, 26–34, 35–75 years) is presented in table 2.
There were no significant differences between sex and age group
with regard to injury rate in the overall Games period.
Incidence of injury in the precompetition (3 days) and
competition period (11 days)
There were 141 injuries recorded in 134 athletes (IR of 12.9
(95% CI 10.9 to 15.2)) in the precompetition period, while 369
injuries were recorded in 325 athletes (IR of 9.2 (95% CI 8.3 to
10.2)) during the competition period of the Rio 2016 Summer
Paralympic Games (table 3). Thus, significantly higher rates of
injury were found in the precompetition period, compared with
the competition period (risk ratio: 1.40 (95% CI 1.51 to 1.71),
p=0.003).
Incidence of injury by sport
Table 4 presents the total number of injuries as well as injuries
per sport in 22 sports. There was a significantly higher rate of
injury in football 5-a-side (IR of 22.5 (95% CI 14.8 to 34.1),
p=0.001), judo (IR of 15.5 (95% CI 10.5 to 23.0), p=0.02) and
football 7-a-side (IR of 15.3 (95% CI 10.3 to 22.8), p=0.03)
compared with all other sports. Additionally, significantly lower
IR was reported for the sports of boccia (IR of 4.3 (95% CI 1.9
to 9.6), p=0.04) and Para swimming (IR of 7.1 (95% CI 5.4 to
9.4), p=0.03).
The multiple regression analysis found that, when adjusted
for age and sex, the three groupings of sports were independent
risk factors for injury, indicating that all three categories of sport
disciplines had a significantly higher IR compared with the cate-
gory ‘all other sport disciplines’ (table 4). The results were as
follows: (1) football-5-a-side and football-7-a-side (p=0.0001),
(2) judo (p=0.004) and (3) wheelchair basketball, wheelchair
fencing and wheelchair rugby (p=0.0002).
Incidence of sport and non-sport-related injury
There were 440 sport-related and 70 non-sport-related injuries
during the total Games period. The incidence of sport-related
injuries was 8.6 (95% CI 7.8 to 9.4) injuries per 1000 athlete
days, while the incidence of non-sport related injuries was 1.4
(95% CI 1.1 to 1.7).
Table 3 Incidence of injury in the precompetition and competition periods for athletes competing at the Rio 2016 Summer Paralympic Games
Period
Total number of injuries
(percentage of total
number of injuries)
Number of athletes
with an injury
Total number of
athletes competing
Total number of
athlete days
Proportion of athletes
with an injury
Injury incidence rate:
number of injuries/1000
athlete days (95% CI)
All 510 441 3657 51 198 12.1 10.0 (9.1 to 10.9)
Precompetition period 141 134 3657 10 971 3.7 12.9 (10.9 to 15.2)*
Competition period 369 325 3657 40 227 8.9 9.2 (8.3 to 10.2)
*Significantly higher than injuries in the competition period (p<0.01).
Table 4 Incidence of injury by sport for athletes competing at the Rio 2016 Summer Paralympic Games in descending order of injury incidence rate
Sport
Total number of injuries
(percentage of total
number of injuries)
Number of athletes
with an injury
Total number
of athletes
competing
Total number of
athlete days
Proportion of
athletes with an
injury
Injury incidence rate:
number of injuries/1000
athlete days (95% CI)
All 510 (100%) 441 3657 51 198 12.1 10.0 (9.1 to 10.9)
Football 5-a-side 22 (4.3%) 17 70 980 24.3 22.5 (14.8 to 34.1)*
Wheelchair fencing 16 (3.1%) 13 72 1008 18.1 15.9 (9.7 to 25.9)
Judo 25 (4.9%) 19 115 1610 16.5 15.5 (10.5 to 23.0)*
Football 7-a-side 24 (4.7%) 21 112 1568 18.8 15.3 (10.3 to 22.8)*
Wheelchair rugby 20 (3.9%) 16 96 1344 16.7 14.9 (9.6 to 23.1)
Wheelchair basketball 41 (8.0%) 32 228 3192 14.0 12.8 (9.5 to 17.4)
Sitting volleyball 21 (4.1%) 17 127 1778 13.4 11.8 (7.7 to 18.1)
Wheelchair tennis 15 (2.9%) 13 94 1316 13.8 11.4 (6.9 to 18.9)
Para powerlifting 22 (4.3%) 22 141 1974 15.6 11.1 (7.3 to 16.9)
Para athletics 126 (24.7%) 111 894 12 516 12.4 10.1 (8.5 to 12.0)
Archery 16 (3.1%) 14 113 1582 12.4 10.1 (6.2 to 16.5)
Triathlon 8 (1.6%) 7 58 812 12.1 9.9 (4.9 to 19.7)
Canoe 7 (1.4%) 6 52 728 11.5 9.6 (4.6 to 20.2)
Table tennis 27 (5.3%) 24 223 3122 10.8 8.6 (5.9 to 12.6)
Sailing 9 (1.8%) 8 76 1064 10.5 8.5 (4.4 to 16.3)
Rowing 9 (1.8%) 8 88 1232 9.1 7.3 (3.8 to 14.0)
Para swimming 49 (9.6%) 42 492 6888 8.5 7.1 (5.4 to 9.4)†
Cycling (track and road) 20 (3.9%) 20 204 2856 9.8 7.0 (4.5 to 10.9)
Equestrian 7 (1.4%) 7 71 994 9.9 7.0 (3.4 to 14.8)
Shooting Para sport 12 (2.4%) 11 130 1820 8.5 6.6 (3.7 to 11.6)
Goalball 8 (1.6%) 7 102 1428 6.9 5.6 (2.8 to 11.2)
Boccia 6 (1.2%) 6 99 1386 6.1 4.3 (1.9 to 9.6)†
*Significantly higher than all other sports (p<0.03).
†Significantly lower than all other sports (p<0.05).
5
DermanW, etal. Br J Sports Med 2017;0:1. doi:10.1136/bjsports-2017-098039
Original article
Incidence of sport-related injury by anatomical area
Sport-related injuries were recorded in 10.4% of athletes on the
WEB-IISS. The anatomical areas affected by sport-related injury
are presented in table 5. Injuries to the upper limb were most
prevalent with an IR of 3.4 (95% CI 3.0 to 4.0), followed by
the lower limb, which had an IR of 3.0 (95% CI 2.6 to 3.5). The
anatomical areas most affected by injury included the shoulder
(IR of 1.8 (95% CI 1.4 to 2.2)), wrist, hand and finger complex
(IR of 1.0 (95% CI 0.8 to 1.4)) followed by the ankle, foot and
toe complex (IR of 0.9 (95% CI 0.6 to 1.2)).
Incidence of injury by onset
Table 6 depicts the incidence of injury by onset, namely acute
traumatic injuries, acute on chronic injuries and chronic injuries.
The highest overall IR recorded was for acute injury (5.2 (95%
CI 4.6 to 5.8), compared with chronic injuries (p=0.0001),
followed by chronic overuse injuries (IR of 3.4 (95% CI 3.0 to
4.0)) and acute on chronic injuries (IR of 1.4 (95% CI 1.1 to
1.7)).
Proportion of injured athletes by impairment type
A description of the impairment types of the athletes who
sustained an injury is reported in table 7. Athletes with limb
deficiency constituted the group with the highest number of
injuries (154 injuries, 32.0% of all injured athletes), followed by
visual impairment (112 injuries, 20.0% of all injured athletes),
spinal cord injury (103 injuries, 18.4% of all injured athletes)
and central neurological impairment (82 injuries, 17.0% of all
injured athletes).
Estimated time loss as a result of injury
Of all injuries reported at the Rio 2016 Summer Paralympic
Games (510 injuries), 382 injuries (74.9%) did not result in the
athlete requiring time away from training or competition. Inju-
ries that required athletes to be excluded from training or compe-
tition for an estimated period of 1 day or more equalled 128
injuries (25.1%). Of these, there were 90 injuries that required
two or more days exclusion from training or competition. The
total days lost by the 160 athletes were 396 out of the overall
51 198 athlete days (7.7 days lost per 1000 athlete days). The
highest number of days lost was for football 5-a-side (32.7 days
lost per 1000 athlete days), football 7-a-side (26.1 days lost per
1000 athlete days) and judo (15.5 days lost per 1000 athlete
days). Athletes in the age group of 26–34 years (IR of 10.8) had
a significantly higher rate of time loss due to injury than athletes
in the age group of 35–75 years (IR of 5.3, p<0.05), however
not when compared with the age group of 12–25 years (IR of
6.9). There were no significant differences with regard to sex
of the athlete. Unfortunately, one athlete suffered a fatal head
injury during competition (cycling).
Table 5 Incidence of sport-related injury by each anatomical area for athletes competing at the Rio 2016 Summer Paralympic Games
Anatomical area
Total number of injuries (percentage
of total number of injuries)
Number of athletes
with an injury
Proportion of athletes with
an injury (%)
Injury incidence rate: number of
injuries/1000 athlete days (95% CI)
All 440 (100%) 382 10.4 8.6 (7.8 to 9.4)
Head and face 7 (1.6%) 7 0.2 0.1 (0.1 to 0.3)
Neck 37 (8.4%) 36 1.0 0.7 (0.5 to 1.0)
Shoulder 90 (20.5%) 84 2.3 1.8 (1.4 to 2.2)
Upper arm 5 (1.1%) 4 0.1 0.1 (0.0 to 0.2)
Elbow 20 (4.5%) 18 0.5 0.4 (0.3 to 0.6)
Forearm 8 (1.8%) 7 0.2 0.2 (0.1 to 0.3)
Wrist, hand and finger 53 (12.0%) 47 1.3 1.0 (0.8 to 1.4)
Chest wall 8 (1.8%) 8 0.2 0.2 (0.1 to 0.3)
Trunk and abdomen 5 (1.1%) 5 0.1 0.1 (0.0 to 0.2)
Thoracic spine 8 (1.8%) 8 0.2 0.2 (0.1 to 0.3)
Lumbar spine 29 (6.6%) 29 0.8 0.6 (0.4 to 0.8)
Pelvis/buttock 9 (2.0%) 9 0.2 0.2 (0.1 to 0.3)
Hip/groin 9 (2.0%) 9 0.2 0.2 (0.1 to 0.3)
Thigh 32 (7.3%) 28 0.8 0.6 (0.4 to 0.9)
Stump 1 (0.2%) 1 0.0 0.0
Knee 34 (7.7%) 33 0.9 0.7 (0.5 to 0.9)
Lower leg 25 (5.7%) 25 0.7 0.5 (0.3 to 0.7)
Ankle, foot and toe 44 (10.0%) 42 1.1 0.9 (0.6 to 1.2)
Other 16 (3.7%) 16 0.4 0.3 (0.2 to 0.5)
Table 6 Incidence of injury by onset for athletes competing in the precompetition and competition periods of the Rio 2016 Summer Paralympic
Games
Type of injury
Total number of injuries (percentage
of total number of injuries)
Number of athletes with
an injury
Proportion of athletes with
an injury (%)
Injury incidence rate: number of
injuries/1000 athlete days (95% CI)
All 510 (100%) 441 12.1 10.0 (9.1 to 10.9)
Acute traumatic injury 264 (51.8%) 241 6.6 5.2 (4.6 to 5.8)*
Acute on chronic injury 70 (13.7%) 64 1.8 1.4 (1.1 to 1.7)
Chronic overuse injury 176 (34.5%) 166 4.5 3.4 (3.0 o 4.0)
*Significantly higher than acute on chronic and chronic injuries (p<0.001).
6DermanW, etal. Br J Sports Med 2017;0:1. doi:10.1136/bjsports-2017-098039
Original article
DISCUSSION
The present study represents the largest sample of athletes
with impairment to be included in an epidemiological descrip-
tion of injuries sustained in the precompetition and competi-
tion periods of the Rio 2016 Summer Paralympic Games. This
study also represents the second consecutive Games dataset to
describe the incidence of injury in a Summer Games setting,
with the Rio 2016 Summer Paralympic Games total athlete
days comprising 1288 more athlete days than the London 2012
Summer Paralympic Games. These data provide important infor-
mation to team medical staff to allow for preparation for future
international multisport competitions as well as help to inform
future longitudinal data collection studies and injury prevention
programmes in this population.15 16
Lower overall incidence of reported injuries at the Rio Games
compared with the London Games
The first important finding of this study was that the overall
incidence of injury per 1000 athlete days in this study (IR of
10.0 (95% CI 9.1 to 10.9) was lower than that reported for
the London 2012 Summer Paralympic Games (IR of 12.7 (95%
CI 11.7 to 13.7), p<0.01).6 Furthermore, the proportion of
athletes with an injury at the Rio 2016 Summer Paralympic
Games (12.1%) was lower than the proportion of injured
athletes at the London 2012 Summer Paralympic Games
(15.0%). As no specific intervention strategies on behalf of the
IPC or (to the best of our knowledge) efforts by sporting feder-
ations to reduce rates of injury were employed in the Games
setting, the reason for this finding is not directly apparent but
might reflect a general increase in awareness of injury preven-
tion by team medical staff in the 4-year period between Games.
It must be kept in mind however that rates of injury may be
influenced by other variables, including environmental condi-
tions, facilities, selection criteria, scheduling of events and so
on. As polyclinic data for injury were not available for this study
due to challenges identified previously and the possibility that
athletes from smaller and perhaps under-resourced countries
might have a higher injury rate, it might be argued that injury
rates may have been higher if polyclinic data of the 247 athletes
from the smaller NPC delegations who were not recorded on
the WEB-IISS were included in the analysis. Although this is a
point of interest, it is unlikely that the influence of such a small
percentage (5.6%) of the total athlete cohort would signifi-
cantly alter the finding that the incidence of injury was lower at
Rio compared with London.
Higher incidence of precompetition injuries
Another important finding of this study was that there was
a significantly higher incidence of injury in the precompe-
tition period (IR of 12.9 (95% CI 10.9 to 15.2), p<0.003)
compared with the competition period (IR of 9.2 (95% CI
8.3 to 10.2)). A possible reason to explain these findings is
that there was a unique situation at the Rio Games whereby
the IPC redistributed the 267 athlete slots, following the deci-
sion of the IPC to suspend the Russian NPC from the Games.
As a result, 267 athletes from other countries were recruited
to the Rio Games between 23 August and 7 September 2016,
who may not have targeted participation at Rio after previ-
ously being informed that they had not been selected to
compete.17 Thus, this may reflect a larger group of athletes
who may have been predisposed to injury. It is also possible
that increased competition for a relatively lower total number
of Paralympic slots available to athletes (in comparison with
the London Games) might have led to an increased injury rate
in this period.18 A detailed in-depth analysis of the current
findings is planned by this group of researchers to identify
possible factors related to the difference between precompe-
tition and competition IRs.
Sports with an increased risk of injury
Findings of this study noted that the four highest risk sports
at the Games represented 10% of all the athletes on WEB-IISS
and include the sports football 5-a-side, judo and football
7-a-side and wheelchair fencing (combined IR of 16.8 (95%
CI 13.7 to 20.8), p<0.0001). Although there were sports that
had either a higher IR (wheelchair fencing (marginally signif-
icant, p=0.05)) or lower IR (goalball, shooting Para sport,
equestrian and cycling), significance was not reached, likely
due to the relatively lower number of athletes competing in
these sports and thus low statistical power. Although there
were some differences compared with the sports with the
highest incidence of injury at the London 2012 Summer
Paralympic Games (football 5-a-side, goalball, Para power-
lifting and wheelchair fencing), the sport of football 5-a-side
has repeatedly been identified as high risk for musculoskel-
etal injury.11 This finding indicates that these are the sports
where injury prevention programmes should be prepared for
as soon as possible with specific aims, methods and detailed
outcomes to determine if the rates of injury can be reduced by
as early as Tokyo 2020 Summer Paralympic Games. The addi-
tional sports identified as being high risk (judo and football
Table 7 Proportion of injured athletes by impairment type for all injuries for athletes competing at the Rio 2016 Summer Paralympic Games
Impairment type
Total number of injuries (percentage
of total number of injuries)
Number of athletes
with an injury
Proportion of injured athletes
in each impairment type (%)
All 510 (100%) 411 100
Limb deficiency (amputation, dysmelia, congenital deformity) 154 (30.2%) 141 32.0
Visual impairment 112 (22.0%) 88 20.0
Spinal cord injury 103 (20.2%) 81 18.4
Central neurological injury (cerebral palsy, traumatic brain injury, stroke,
other neurological impairment)
82 (16.1%) 75 17.0
Other 25 (4.9%) 24 5.4
Les autres (non-spinal polio myelitis, ankylosis, leg shortening, joint
movement restriction, nerve injury resulting in local paralysis)
17 (3.3%) 16 3.6
Intellectual impairment 8 (1.6%) 7 1.6
Unknown 5 (1.0%) 5 1.1
Short stature 4 (0.8%) 4 0.9
7
DermanW, etal. Br J Sports Med 2017;0:1. doi:10.1136/bjsports-2017-098039
Original article
7-a-side) should also be investigated further to identify
possible factors compounding the risk of injury to athletes
participating in these sports.
Upper limb injuries most common
A further finding of the present study was that the upper limb
(IR of 3.4 (95% CI 3.0 to 4.0)) showed a slightly higher IR than
that of the lower limb (IR of 3.0 (95% CI 2.6 to 3.5)), in accor-
dance with the data reported for the London Games. Further-
more, the most injured anatomical area was the shoulder (IR of
1.8 (95% CI 1.4 to 2.2), which is also in accordance with both
previous literature and our published IR of shoulder injuries at
the London Games.6 7 14 19 20
Concussions may be under-reported in this population
A new aspect of this study was the inclusion of specific ques-
tions regarding concussion, which were posed to the physician
if they reported a head, face or neck injury. Despite several
incidents where athletes were observed to suffer a blow to
the head followed by unsteady gait and survey reports of
more significant injuries to the head and face, no concussions
were reported. This indicates a need for clinician education
regarding concussion recognition, assessment and manage-
ment in this population.
Unfortunately, the Rio 2016 Summer Paralympic Games saw
the first death of an athlete in a Games setting, through head
injury during competition (cycling). This was clearly a cata-
strophic event and highlights the importance of ongoing efforts
toward planning for trauma and acute catastrophic events at
major international multisport competitions.
Impairments that may predispose athletes to injury
Finally, this study showed that athletes with the impairment
of limb deficiency (32.0%), visual impairment (20.0%) and
spinal cord injury (18.4%) had the highest proportion of
injury. The investigation of the specific factors contributing
to injury in these cohorts is important, as different impair-
ment types affect the risk for injury and the characteristics of
specific injuries.21–23 For example, whether the athletes with
limb deficiency who sustained injuries were prosthesis users
or not would allow us to determine whether the use of a pros-
thesis is associated with injury risk. This description requires
further in-depth analysis, which will be provided through the
combination of Games datasets as baseline data in the future.
Strengths and limitations of the study
This study constituted the largest study of its kind to investigate
incidence of injury at a major international Paralympic competi-
tion. There was high compliance from team physicians involved
in the study as well as a large proportion of team physicians who
have worked with the WEB-IISS on more than one occasion in
previous editions of the Games, which helped to enhance data
collection. Compliance was further encouraged by the provision
of a tablet computer to every team physician monitoring a team
of five athletes or more as well as the awarding of daily prizes
for completing data entry on the previous day. Another strength
of this study was that the WEB-IISS allowed for online regis-
tration of injuries over a wireless connection at the team’s base
or at venues during the Games. Additionally, enhancements to
the WEB-IISS system were carried out prior to the Games, in
order to provide a better platform for data entry. An important
enhancement was the collection of impairment data from every
athlete who was injured during the Games at the time of injury.
This is the first system to capture impairment data, which is
crucial for the implementation and tailoring of prevention
programmes in the future. This study w also the first to docu-
ment the incidence of injury in the new Paralympic sports of
triathlon (IR of 9.9 (95% CI 4.9 to 19.7)) and canoe (IR of 9.6
(95% CI 4.6 to 20.2)).
A limitation of the present study was that data from the poly-
clinic and venue medical stations were not available for analysis.
Therefore, the data regarding injury from the 247 athletes who
did not have their own medical support and the 474 athletes
from the three countries who chose not to participate have not
been captured. A further consideration is that it is possible that
athletes might have reported an injury to the polyclinic which
was not reported to their own doctor. However, we believe
that this might have occurred in a negligible number of cases,
as we verified significant injuries against imaging records of the
polyclinic. Furthermore, further analysis comparing the London
and Rio Games in only the group of athletes monitored on the
WEB-IISS, with additional statistical modelling, is planned for
the future by this group of researchers. A further limitation of
the study was that doctors were asked to anticipate the number
of days lost due to injury and were unable to validate their esti-
mate once the athlete had recovered. Updates to the WEB-IISS
are planned in the future to allow the doctors to amend their
records with regard to time loss data. Furthermore, the total
number of participating athletes in each impairment types was
not available for analysis in this study. Finally, a detailed analysis
is required to assess the factors related to the lower overall IR
of injury at the Rio Games compared with the London Games.
CONCLUSION
This study completed at the Rio 2016 Summer Paralympic
Games was the largest study of its kind to successfully document
the incidence of injury per 1000 athlete days in athletes with
impairment. A lower incidence of injury was found at Rio 2016,
as compared with the London 2012 Summer Paralympic Games.
The sports with the highest incidence of injury included football
5-a-side, judo and football 7-a-side. Injuries in the precompeti-
tion period had a significantly higher IR than injuries sustained
in the competition period. It was found that the upper limb had
more injuries compared with the lower limb, with the shoulder
joint representing the single most injured area. Acute injuries
were the most common type of injury with regard to onset. This
study stands to represent baseline data for the development and
implementation of injury prevention programmes for athletes
with impairment at future competitions.
What are the new findings?
►This is the second significant dataset to document the
incidence of injury in a Summer Paralympic Games setting.
►Precompetition injury rates were significantly higher than
competition injury rates.
►The sports of football 5-a-side, judo and football 7-a-side
had a significantly higher incidence of injury, compared
with all other sports, while boccia and Para swimming had a
significantly lower injury rate.
►The shoulder joint was the most commonly injured
anatomical area.
►Acute injuries constituted the highest injury rate at the
Games.
8DermanW, etal. Br J Sports Med 2017;0:1. doi:10.1136/bjsports-2017-098039
Original article
Author affiliations
1Institute of Sport and Exercise Medicine, Department of Surgical Sciences, Faculty of
Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
2Sport, Exercise Medicine and Lifestyle Institute (SEMLI) and Section Sports Medicine,
Faculty of Health Sciences, University of Pretoria, Pretoria, South Africa
3Biostatistics Unit, Medical Research Council, Parow, South Africa
4Department of Physical Medicine and Rehabilitation, Spaulding Rehabilitation
Hospital and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, USA
5Centre for Sport and Exercise Science and Medicine (SESAME), University of
Brighton, Eastbourne, UK
6Department of Health Sciences, Lund University, Lund, Sweden
7Department of Neurology and Rehabilitation Medicine, Skåne University Hospital,
Lund, Sweden
8Department of Health Science, Luleå University of Technology, Luleå, Sweden
9Medical and Scientific Department, International Paralympic Committee, Bonn,
Germany
10Yale School of Public Health, Department of Chronic Disease and Epidemiology,
Department of Orthopaedics and Rehabilitation, Yale University, Connecticut, United
States of America
11Carleton University Sport Medicine Clinic, Department of Family Medicine, Ottawa,
Canada
12Department of Sport Medicine, Isala Klinieken, Zwolle, Netherlands
Twitter Follow Wayne Derman at @ISEM_SU
Acknowledgements The authors wish to extend their sincerest thanks to
all National Paralympic Committee medical personnel who participated in data
collection as well as to the International Paralympic Committee for their support,
in particular Anne Sargent, Katharina Grimm and Guzel Idrisova. They also wish to
thank Samsung for the provision of tablet computers used as both tools for data
collection as well as study incentives. Thanks are also extended to the Rio Organizing
Committee for their support throughout the period of the Rio 2016 Summer
Paralympic Games, particularly Joao Grangeiro and Emma Painter.
Funding This study was approved and supported by the International Paralympic
Committee. Funding for the study was provided by the International Olympic
Committee (IOC) Research Centre (South Africa) Grant.
Competing interests None.
Ethics approval Brighton University (FREGS/ES/12/11), Stellenbosch University
(N16/05/067)
Provenance and peer review Not commissioned; externally peer reviewed.
© Article author(s) (or their employer(s) unless otherwise stated in the text of the
article) 2017. All rights reserved. No commercial use is permitted unless otherwise
expressly granted.
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How might it impact on clinical practice in the future?
►The data presented in this study allow for the further
establishment of a baseline injury dataset in Paralympic
athletes, to be used as a comparison for data gathered at
future Paralympic Games and to inform practice for clinicians
providing medical support at the Games.
►These data, in conjunction with the data from the London
2012 Summer Paralympic Games, provide the basis for
evidence-based injury prevention programmes to be
implemented in the future.
►These future prevention programmes should be prepared for
athletes from high-risk sports. Further studies are needed
to determine the cause of higher rates of injury during the
precompetition period.
