Injury Risk in New Zealand Rugby Union: A Nationwide Study of Injury Insurance Claims from 2005 to 2017.

OBJECTIVES: The Accident Compensation Corporation is a compulsory, 24-h, no-fault personal injury insurance scheme in New Zealand. The purpose of this large-scale retrospective cohort study was to use Accident Compensation Corporation records to provide information about rugby injury epidemiology in New Zealand, with a focus on describing differences in risk by age and gender.
METHODS: A total of 635,657 rugby injury claims were made to the Accident Compensation Corporation for players aged 5-40 years over the period 2005-2017. Information about player numbers and estimates of player exposure was obtained from New Zealand Rugby, the administrative organisation for rugby in New Zealand.
RESULTS: Over three quarters of claims (76%) were for soft-tissue injuries, with 11% resulting from fractures or dislocations, 6.7% from lacerations, 3.1% from concussions and 2.0% from dental injuries. Body regions injured included shoulder (14%), knee (14%), wrist/hand (13%), neck/spine (13%), head/face (12%), leg (11%) and ankle (10%). The probability of a player making at least one injury claim in a season (expressed as a percentage) was calculated under the assumption that the incidence of claims follows a Poisson distribution. Players aged 5-6 years had a probability of making at least one claim per season of 1.0%, compared to 8.3% for players aged 7-12 years, 35% for age 13-17 years, 53% for age 18-20 years, 57% for age 21-30 years and 47% for age 31-40 years. The overall probability of making at least one claim per season across all age groups was 29%. The relative claim rate for adults (players aged 18 years and over) was 3.92 (90% confidence interval 3.90-3.94) times that of children. Ten percent of players were female, and they sustained 6% of the injuries. Overall, the relative claim rate for female players was 0.57 times that of male players (90% confidence interval 0.56-0.58). The relative claim rate of female to male players tended to increase with age. There were very few female players aged over 30 years; however, those who did play had higher claim rates than male players of the same age group (1.49; 90% confidence interval 1.45-1.53).
CONCLUSIONS: Injuries resulting from rugby are distributed across the body, and most of the claims are for soft-tissue injuries. Rates of injury increase rapidly through the teenage years until the early 20 s; for male players they then decrease until the mid-30 s. For female players, the injury rate does not decrease as players move into their 30 s. Combining Accident Compensation Corporation injury claim data with national player registration data provides useful information about the risks faced by New Zealand's community rugby players, and the insights derived are used in the development of rugby injury prevention programme content.

Key Points

Introduction

Rugby union (rugby) is a field-based team sport characterised in part by the degree of physical contact players are permitted to use in contesting possession of the ball. According to World Rugby, which is the governing body of rugby union internationally, rugby union is played in 120 countries, with 8.5 million players participating in the sport [1].

Injury surveillance is fundamental to quantifying, and thus managing the risk of injury associated with a given activity [2-4]. The absence of information regarding injury risks means that participants cannot make informed decisions about whether to take part in the activity, and administrative or regulatory bodies cannot make evidence-supported decisions regarding risk mitigation strategies.

While there have been multiple studies of the epidemiology of rugby injuries from throughout the world, the preponderance of these have dealt with players at the elite level of the sport, who represent a small fraction of the overall playing population [5]. The injury epidemiology of players at the community level of the sport, and especially of female players, has been investigated in relatively few research studies [6-11]. Some researchers and safety advocates have suggested that injury surveillance in youth rugby is not as comprehensive as it ought to be, and the relative lack of research on the risks of injury for community-level players, especially for children, has led to competing claims about whether rugby is an acceptably safe sport [11-17].

With a few exceptions, most rugby-related injury surveillance projects published to date have involved the collection of injury information from researchers and/or medical personnel associated with teams. Another method of obtaining injury information across a defined population is via the analysis of injury insurance claims, as we describe below, and as King and colleagues have done for rugby league in New Zealand [18-20].

New Zealand, a country of approximately 4.8 million people in 2017 has had, since 1974, a 24-h no-fault levy- and taxpayer-funded injury insurance and rehabilitation scheme. The scheme was enacted by statute and is administered by the Accident Compensation Corporation (ACC). The ACC collects and stores information about all injuries in New Zealand that result in claims against the scheme, thus it provides a nationwide, all activity injury surveillance system. The ACC does not, however, monitor exposure to activities. New Zealand Rugby (NZR), which administers rugby union in New Zealand, records player numbers on an annual basis. The purpose of this paper is to use combined data from the ACC and NZR to describe the injury epidemiology and level of risk associated with participation in rugby across age groups and by gender in an entire country’s playing population.

Methods

Injuries and Player Numbers

The ACC obtains information about all rugby injuries that result in claims for medical assessment or treatment in New Zealand. The nationwide scope of the scheme means that, regardless of whether a player sustained an injury in school, club, amateur or professional rugby, the details of the injury are logged by the ACC. There are approximately 30,000 ACC-registered medical providers in New Zealand.

Because variations in injury definitions can lead to difficulties in comparing injury rates across studies, ‘consensus’ definitions for a number of sports, including rugby, have been developed [21]. Fuller and colleagues recommended that case definitions based on either ‘medical attention’ or ‘time-loss’ injuries should be used in studies of rugby injury epidemiology [21]. For the most part, ACC claims in New Zealand are synonymous with medical treatment for injuries (see www.acc.co.nz for details of the ACC system). Although it is technically possible for a rugby player in New Zealand to sustain an injury, obtain medical attention for it at the field of play and the medical treatment provider not to submit a claim to the ACC, in most cases, medical treatment injuries become ACC claims for all but very minor injuries.

Information was obtained from the ACC about 635,657 rugby injury claims for players aged 5–40 years that occurred from the 1 January, 2005 until the 31 December, 2017. Self-reported age and gender (recorded as male or female) are recorded for all ACC claims. Numbers of rugby players were obtained from the NZR player register, which also collects self-reported age and gender (again, as male or female).

While we also conducted analyses for each individual age, players were assigned to the following age groups: 5–6 years, 7–12 years, 13–17 years, 18–20 years, 21–30 years and 31–40 years for reporting purposes. In New Zealand, players aged 5 and 6 years play non-contact ‘tag’ rugby. Players aged 7–12 years (primary school age) play modified forms of rugby, with the contact elements of the sport introduced progressively over several years. Tackling usually begins for players at age 7 years. A description of the ‘rugby development model’ and the variations played by children of different ages is available online [22]. Players aged 13–17 years are of secondary school age. Players aged 18–20 years have normally left school; most play in age-graded competitions (e.g. Under 21 years). Players aged younger than 5 years (1.6% of all players), and older than 40 years (2% of all players) were excluded from the analyses.

We chose to report claim rates in two main ways; first, as the actual rate of claims per 1000 players by year, and second as the estimated rate of claims per 1000 player-hours of exposure to training and match play. The first was used because we were able to derive them directly from the ACC and NZR data. The second was used to facilitate comparisons with existing work because reporting injuries per 1000 player-hours has been the most commonly used convention in publications of rugby injury epidemiology [5, 11, 21].

Injury Type and Body Region Definitions

Claims were classified into the following injury types:

soft tissue (contusion, muscle strain, ligament strain);

fracture or dislocation;

cut/laceration;

concussion/brain injury;

dental injury; and

‘other’ (includes injuries to internal organs).

Body regions were grouped as follows, with the label for reporting in parentheses where it differs:

head/face/ear/eye/nose (head/face);

neck/spine;

shoulder;

arm/elbow (arm);

wrist/hand/finger/thumb (wrist/hand);

chest/abdomen/thorax (trunk);

leg—excluding knee and ankle (leg);

knee;

ankle;

foot/toe; and

other—includes injuries to internal organs.

We excluded ‘multiple locations/unobtainable’ from the body region by injury type breakdown, as these accounted for less than 1% of all claims.

Statistical Methods

The probability of a player making at least one injury claim in a season (expressed as a percentage) was calculated based on the method outlined by Parekh et al., under the assumption that the incidence of claims follows a Poisson distribution [23]. The probability of making at least one claim per year for any given player was:where P(0), the probability of making zero claims, equals e(−1*Injuries per player per year).

Note that ‘overall’ probabilities in the tables below are not linear sums of the component probabilities because of the non-linear transformation used to calculate Poisson probabilities.

Ninety percent confidence limits on rates and probabilities were calculated using Wilson’s method [24]. In the results below, where confidence intervals on rates are not presented, it is because the uncertainty in the estimate was negligible—the confidence limits range from the point estimate multiplied or divided (×/÷) by a factor of 1.01 through to ×/÷ 1.06. Comparisons of rates by gender, age group and injury site were calculated using the Genmod procedure in SAS (Version 9.4; SAS Institute, Cary, NC, USA).

This large-scale study provides significant new information about the injury epidemiology of community rugby players, and highlights differences in injury rates between genders and age groups.

Rates of rugby injury increase rapidly with age from childhood to adulthood; rates for adults (18 years of age and over) are about four times higher than rates for children (17 years of age and younger).

Injuries are distributed throughout the body; soft-tissue injuries comprise three quarters of injury claims.

In general, female players have lower rates of injury than male players.

Table 1

Accident Compensation Corporation claim and player numbers per year by gender and age group: 2005–17

Gender	Age group, years
	5–6		7–12		13–17		18–20		21–30		31–40		Overall
	Claims	Players	Claims	Players	Claims	Players	Claims	Players	Claims	Players	Claims	Players	Claims	Players
Female	7 ± 3	1267 ± 455a	364 ± 94	8103 ± 3086	1306 ± 409	3861 ± 638	384 ± 144	687 ± 178	801 ± 251	906 ± 200	275 ± 48	296 ± 52	3138 ± 925	15,120 ± 4370
Male	112 ± 22	10,148 ± 1519	4574 ± 661	49,233 ± 2555	14,186 ± 1597	31,676 ± 1855	7513 ± 762	9810 ± 585	15,012 ± 1130	18,039 ± 721	4362 ± 359	6995 ± 296	45,759 ± 4346	125,902 ± 4164
Total	119 ± 26	11,415 ± 1952	4938 ± 744	57,336 ± 5290	15,492 ± 1922	35,538 ± 1523	7899 ± 857	10,497 ± 502	15,813 ± 1282	18,945 ± 769	4637 ± 366	7291 ± 272	47,817 ± 5095	141,022 ± 7074
Percent of all claims for age group	0.2		10		32		16		20		9.5		100
Percent of all players in age group		8		41		25		7		8		5		100

aStatistics are means per year ± one standard deviation

Table 2

Injury claim rates and claim probabilities by age group and gender

		Age group, years
		5–6	7–12	13–17	18–20	21–30	31–40	Overall
Injury claims per 1000 players per year	Female	5.3a	45	338	559	884	930	169
	Male	10.8	93	448	766	832	623	276
	Both genders	10.4	86	436	752	835	636	265
Percent probability of making at least one claim per season	Female	0.53	4.4	29	43	59	61	19
	Male	1.1	8.9	36	54	57	46	31
	Both genders	0.95	8.3	35	53	57	47	29
Average number of seasons played per claim for players of that age group	Female	188	23	3.5	2.3	1.7	1.7	5.3
	Male	91	11	2.8	1.9	1.8	2.2	3.3
	Both genders	105	12	2.9	1.9	1.8	2.1	3.4

a90% confidence intervals for claim rates and claim probabilities are ≤ ×/÷ factors of 1.01

Table 3

Claim rates per 1000 players per year by gender, age group and injury type

Gender	Age group, years	Injury type
		Soft tissue	Fracture/dislocation	Laceration	Concussion/brain injury	Dental	Other	Total
Female	5–6	3 (2.4–3.8)a	0.97 (0.64–1.5)	0.55 (0.32–0.95)	0.18 (0.07–0.47)	0.42 (0.23–0.79)	0.18 (0.07–0.47)	5.3 (4.5–6.4)
	7–12	32 (31–33)	8.5 (8.1–9)	1.8 (1.6–2)	1.0 (0.87–1.2)	0.86 (0.73–1)	0.85 (0.72–1.0)	44.9 (43.9–46.1)
	13–17	271 (267–275)	31 (30–33)	11 (9.8–11)	15 (14–16)	3.7 (3.3–4.2)	6.6 (6.1–7.3)	338 (334–343)
	18–20	464 (452–476)	45 (42–49)	16 (14-18)	18 (16–21)	7.4 (6–9)	8.2 (6.7–9.9)	559 (546–572)
	21–30	755 (742–768)	63 (59–67)	27 (25–30)	19 (17–21)	8.7 (7.4–10)	12 (11–14)	884 (870–898)
	31–40	796 (773–820)	69 (62–76)	24 (20–28)	9.6 (7.3–13)	13 (10–16)	18 (14–22)	930 (904–955)
	Mean	168 (167–170)	20 (19–20)	6.5 (6.2–6.8)	6.5 (6.2–6.8)	2.6 (2.4–2.8)	3.6 (3.4–3.9)	208 (206–209)
Male	5–6	5.7 (5.4–6.0)	1.8 (1.7–2.0)	2.0 (1.8–2.2)	0.24 (0.18–0.32)	0.84 (0.72–0.98)	0.42 (0.34–0.53)	11 (10.5–11.5)
	7–12	62 (62–63)	14 (14–14)	6.8 (6.6–6.9)	4.0 (3.9–4.1)	3.7 (3.6–3.9)	2.4 (2.3–2.5)	93 (92–94)
	13–17	327 (326–328)	53 (53–54)	27 (27–28)	21 (20–21)	10 (9.9–10)	9.6 (9.3–9.8)	448 (446–450)
	18–20	599 (596–603)	68 (67–69)	49 (48–50)	23 (22–24)	13 (13–14)	14 (13–14)	766 (762–770)
	21–30	662 (659–665)	71 (70–72)	55 (55–56)	17 (16–17)	11 (11–12)	15 (15–16)	832 (829–835)
	31–40	495 (491–499)	57 (56–59)	41 (40–42)	7 (6.6–7.5)	9.5 (9–10)	14 (14–15)	623 (619–628)
	Mean	276 (275–277)	38 (37–38)	24 (23–24)	11 (11–11)	7.3 (7.2–7.4)	7.4 (7.3–7.6)	363 (363–364)
Overall mean		264 (264–265)	36 (36–36)	22 (22–22)	10.8 (10.7–10.9)	6.8 (6.7–6.9)	7.0 (6.9–7.1)	347 (347–347)
Overall relative rate (male/female)		1.21 (1.16–2.26)	1.40 (1.30–1.51)	2.69 (2.43–2.99)	1.35 (1.13–1.61)	1.85 (1.63–2.10)	1.58 (1.33–1.89)	1.75 (1.74–1.77)

aFigures in parentheses are 90% confidence limits

Table 4

Claim rates per 1000 players per year by gender, age group and body region

Gender	Age group, years	Body region
		Head/face	Neck/spine	Shoulder	Arm	Wrist/hand	Trunk	Leg	Knee	Ankle	Foot/toe	Other
Female	5–6	1.3 (0.94–1.9)a	0.44 (0.19–0.99)	0.18 (0.07–0.47)	0.42 (0.23–0.79)	0.79 (0.5–1.2)	0.11 (0.02–0.56)	0.3 (0.15–0.63)	0.36 (0.19–0.71)	0.79 (0.5–1.2)	0.61 (0.36–1)	0.44 (0.19–0.99)
	7–12	4.5 (4.2–4.9)	2.8 (2.5–3)	2.9 (2.6–3.2)	3.6 (3.3–3.9)	13 (13–14)	0.87 (0.74–1)	2.2 (2–2.4)	4.5 (4.1–4.8)	5.5 (5.1–5.8)	3.9 (3.6–4.2)	0.97 (0.82–1.1)
	13–17	38 (37–39)	37 (36–39)	40 (39–42)	16 (15–17)	48 (47–50)	9 (8.4–9.7)	27 (26–29)	62 (60–64)	44 (42–45)	9 (8.3–9.7)	7.4 (6.8–8.1)
	18–20	57 (53–62)	71 (67–76)	73 (69–78)	20 (18–22)	60 (56–65)	16 (14–18)	56 (52–60)	107 (101–112)	76 (72–81)	13 (11–15)	9.5 (8–11)
	21–30	68 (64–72)	126 (121–132)	114 (109–120)	24 (22–27)	92 (88–97)	34 (32–37)	114 (109–119)	166 (160–172)	108 (103–113)	23 (20–25)	14 (12–16)
	31–40	55 (49–61)	159 (148–170)	105 (97–114)	34 (29–39)	94 (87–103)	41 (36–47)	128 (119–138)	159 (148–170)	112 (103–121)	24 (20–28)	20 (16–24)
	Mean	20 (19–21)	25 (24–26)	24 (23–25)	9.0 (8.7–9.4)	30 (29–31)	6.6 (6.3–6.9)	20 (19–21)	36 (35–37)	26 (25–27)	6.8 (6.5–7.1)	4.1 (3.8–4.3)
Male	5–6	2.9 (2.6–3.1)	0.77 (0.65–0.9)	0.78 (0.66–0.92)	1 (0.87–1.2)	1.4 (1.2–1.6)	0.25 (0.19–0.33)	0.79 (0.67–0.93)	1.1 (0.99–1.3)	0.7 (0.59–0.84)	0.81 (0.69–0.95)	0.5 (0.41–0.61)
	7–12	16 (16–16)	8.7 (8.5–8.8)	6.6 (6.4–6.7)	6.1 (6–6.3)	18 (18–19)	2.8 (2.7–2.9)	6.1 (6–6.3)	11 (11–11)	8.7 (8.5–8.9)	6.2 (6–6.4)	2.7 (2.6–2.8)
	13–17	66 (65–66)	57 (56–58)	66 (66–67)	23 (23–24)	65 (64–66)	14 (14–15)	41 (40–41)	56 (55–57)	37 (37–38)	12 (11–12)	10 (10–11)
	18–20	90 (88–91)	85 (84–87)	136 (134–138)	30 (29–31)	82 (81–83)	25 (25–26)	90 (88–91)	109 (107–110)	90 (89–91)	14 (13–15)	15 (14–15)
	21–30	86 (85–87)	110 (109-111)	128 (127–129)	34 (33–35)	82 (81–83)	38 (37–39)	114 (113–116)	119 (118–120)	89 (88–90)	16 (16–17)	16 (15–16)
	31–40	58 (57–59)	97 (95–98)	77 (76–79)	26 (25–27)	57 (56–58)	42 (41–43)	95 (94–97)	88 (86–90)	57 (55–58)	12 (12–13)	14 (14–15)
	Mean	45.5 (45.3–45.8)	45.5 (45.3–45.8)	52.5 (52.2–52.8)	17 (16.9–17.2)	45 (44.7–45.3)	14.5 (14.3–14.6)	41.4 (41.2–41.7)	48.8 (48.6–49.1)	35.7 (35.4–35.9)	9.5 (9.4–9.7)	7.9 (7.8–8)
Overall mean		42.8 (42.5–43.0)	43.3 (43.1–43.6)	49.5 (49.2–49.8)	16.2 (16.0–16.3)	43.4 (43.1–43.6)	13.6 (13.5–13.7)	39.1 (38.9–39.4)	47.5 (47.2–47.7)	34.7 (34.3–34.9)	9.3 (9.1–9.4)	7.5 (7.4–7.6)
Overall relative rate (male/female)		2.28 (2.22–2.34)	1.83 (1.79–1.87)	2.18 (2.12–2.23)	1.88 (1.81–1.96)	1.52 (1.48–1.55)	2.27 (2.17–2.39)	2.07 (2.01–2.12)	1.35 (1.32–1.38)	1.36 (1.32–1.39)	1.40 (1.34–1.47)	1.94 (1.82–2.06)

aFigures in parentheses are 90% confidence limits