ABSTRACT
We aimed to assess the in‐season weekly average prevalence proportion, the incidence rate, and burden (the product of incidence rate and duration of injury in weeks) of health problems among Danish youth handball community players aged 11–17. In this 30‐week prospective cohort study, players self‐reported health problems, including all injuries and illnesses, regardless of time loss or medical attention, and handball exposure using weekly web‐based surveys (OSTRC‐H2). Sex differences were estimated using Poisson regression (incidence rates) and binomial regression (weekly average prevalence proportions) with clustered robust standard errors. We included 945 players (age: 14.5 ± 1.5 years; 55% female) from 20 clubs across Denmark. The response proportion to the weekly questionnaires was 63% (range: 42%–79%). The average prevalence proportion of health problems was 23% (95% CI 21%–25%), with 17% (95% CI 15%–19%) attributable to injuries and 6% (95% CI 5%–7%) to illnesses. The overall incidence rate was 14.9 (95% CI 13.9–15.9)/1000 h. Female players aged 13–15 showed a higher incidence rate (15.9 [95% CI 14.2–17.8]/1000 h) compared to age‐matched males (13.2 [95% CI 11.5–15.1]/1000 h), with an incidence rate ratio of 1.21 [95% CI 1.0–1.4], and had a higher weekly average prevalence proportion (23% [95% CI 19%–27%]) than age‐matched males (12% [95% CI 10%–15%]), corresponding to a difference of 10% points [95% CI 6%–15% points]. COVID‐19 infection accounted for 36% of reported illnesses. Our findings highlight the need for injury prevention initiatives to address both sudden‐onset and gradual‐onset injuries in youth handball players. Sex differences in injury measures and the potential link between illness and injury risk warrant further investigation.
Keywords: athletic injuries, epidemiology, youth sports
1. Introduction
Youth sports participation offers significant health benefits [1], but also carries risks for health problems, including illnesses and musculoskeletal injuries [2, 3, 4], which may hinder athlete development and contribute to early dropout from sports [2, 5]. Injuries sustained during adolescence are further associated with an increased risk of early‐onset osteoarthritis [6]. Thus, while sports are intended to promote physical activity and associated benefits, injury‐related consequences may paradoxically contribute to inactivity, obesity, and mental health challenges [7].
To promote healthy sports participation during adolescence, reliable and up‐to‐date surveillance data are crucial for understanding the prevalence and nature of health problems in this population [8]. The Oslo Sports Trauma Research Centre Questionnaire on Health Problems (OSTRC‐H2) has been developed to measure both injury and illness symptoms, proving particularly valuable in sports settings where gradual‐onset injuries and illnesses pose a significant burden on health and performance [9]. In recent years, the questionnaire has been applied to children and adolescents across various sporting contexts [10].
Handball, one of the most popular sports in Europe [11], has a high incidence of injuries among young handball players [12, 13], but research on illnesses in this population is scarce [12, 14]. To date, no studies have provided comprehensive epidemiological data on all health problems, including both injuries and illnesses faced by youth handball players, particularly those below 13 years of age. Investigating health problems in this population below 13 years is important as our previous study in youth handball players involving players between 14 and 18 years of age indicated that almost half of the players in the youngest age group had experienced a previous injury 1 year prior to study start [12].
The objectives with the present study were to investigate the weekly average prevalence proportion, incidence rates, burden of health problems, and player availability in Danish youth handball players aged 11–17 years.
2. Methods
2.1. Study Design and Participants
This prospective cohort study used data from The Health And Performance Promotion in Youth (HAPPY) hybrid effectiveness‐implementation cluster‐randomized trial, investigating the effectiveness of two different implementation strategies of an injury preventive exercise program [15].
Participants aged between 11 and 17 years were eligible and were followed for one handball season over 30 weeks between October 2021 and May 2022. The COVID‐19 pandemic and its restriction caused the cancellation of handball activities in the last two weeks of 2021. A detailed description of the recruitment procedure has been published elsewhere [15]. All players in the study were introduced to an injury prevention exercise program via their coaches; however, adherence to the program was low to moderate, with no differences in adherence or injury rates between the two randomization groups [15].
The study was approved by The Regional Committees on Health Research Ethics for Southern Denmark (20212000–76) and The Danish Protection Agency, University of Southern Denmark (case number: 10.925). Parents provided informed consent via the secure web application REDCap (Research Electronic Data Capture), while players consented via the mobile app used for injury and handball exposure reports.
2.2. Definition of Health Problems, Burden, and Player Availability
A health problem was defined as any condition reducing an athlete's normal state of full health, irrespective of its impact on the athlete's participation, performance, or need for medical attention [9]. Health problems were categorized into injury and illness. An injury was defined as tissue damage or deviation from normal physical function, while illness referred to any noninjury‐related complaint or disorder. Injury mechanisms were classified into sudden‐onset, resulting from a specific, identifiable event, and gradual‐onset, which lack a clear precipitating event. Subsequent injuries to the same location as the index injury were defined and categorized as recurrences if reported again after the players had reported to be fully available for training and competition for at least 1 week. Recurrences were further classified as “early recurrence” if they occurred within 8 weeks after a player return to full participation, and as “late recurrence” if it occurred between week eight and week 30 [16]. Injury burden was defined as the product of incidence rate expressed as injuries sustained/1000 player‐hours, and severity [17], expressed as the mean severity of injury in three different ways: (1) The mean number of weeks an injury was reported, (2) the mean number of weeks an injury with time‐loss was reported, and (3) the mean cumulative OSTRC‐H2 severity score [18] calculated as described below. Player availability was measured on a four‐point Likert scale from “no participation” to “full participation” based on the first question from the OSTRC‐H2 questionnaire. Total weekly handball exposure was calculated by summing total hours of training and total hours of matches [19]. Handball exposure did not include exposure to strength training or other activities outside the handball field.
2.3. Data Collection
Player demographics (e.g., sex, age, height, team, position, handball, and other sports experience including years of practice and current practice) were collected at baseline via the AthleteMonitoring.com mobile application (FITSTATS Technologies Inc., Moncton, Canada). Players reported weekly on any health problems experienced in the preceding 7 days using the updated OSTRC‐H2 questionnaire [20], translated into Danish and adapted for adolescents. The questionnaire was administered every Sunday evening via the AthleteMonitoring app and includes four questions on: (1) if the players had experienced any health problems the preceding 7 days and if so (2) how the health problem had affected their training or competition, (3) performance, and (4) to what extent they had experienced symptoms. Responses were based on a four‐point Likert Scale ranging from “no symptoms/health problems” (response option 1) to “a great extent” (response option 4). Based on the answers from these four questions, we calculated the OSTRC‐H2 severity score between 0 and 100 for each health problem [18]. Further, we classified health problems into “any health problem” (response > 1 in Q1) or “substantial health problem” (responses ≥ 3 in Q2 and Q3). Time‐loss injury was noted when players indicated they could not participate due to injury, illness, or other health problems.
Upon completing the OSTRC‐H2, all players provided their total weekly handball match and training exposure as part of the weekly online questionnaire. Specifically, they answered two additional questions regarding the total number of minutes played in handball matches and the total number of hours spent in handball training during the preceding 7 days.
2.4. Pilot Testing of the OSTRC‐H2 in Adolescents Using Cognitive Interviews
As the OSTRC‐H2 was originally intended for senior athletes and lacks validation for adolescents, we pilot tested it with our target group to assess their understanding of health problems, injuries, illnesses, and the specific questions and response options. We conducted two focus groups, one with three male and one with three female handball players in a comfortable home setting. An experienced researcher (author LKS) facilitated the sessions, starting with a text message containing the Danish translation of health‐related problems, injuries, and illnesses. Participants reviewed the definition, identified challenging terms, and discussed their meanings. Two researchers (MM and LKS) transcribed and analyzed the interviews, focusing on (1) difficult words in the original definition, (2) their explanations of health‐related problems, (3) connotations linked to health problems, and (4) the use of personal experiences to understand the definition better. The findings revealed that all participants struggled to understand the definitions and required assistance from the interviewer or peers. Based on their explanations, we developed adapted definitions of a health problem, injury and illness, while preserving the original wording of the specific questions to maintain the OSTRC‐H2's integrity. The adapted definitions were accepted by the focus group participants and reviewed by the questionnaire's developers and are available in Supporting Information S1.
2.5. Statistics
All statistical analyses were performed using Stata/BE 18.0 software (StataCorp, College Station, TX, USA). Demographic variables were summarized as means ± standard deviations (SD) for continuous variables, and as frequency and percentage distributions for categorical variables. The weekly prevalence proportion was calculated as the number of players reporting minimum one health problem divided by the total number of players responding to the questionnaire. Incidence rates were reported as injuries per 1000 h of handball exposure, while differences in sex, injury, and exposure types were estimated using Poisson regression with clustered robust standard errors (SEs). Sex differences in the average weekly prevalence proportions were estimated using binomial regression with clustered robust SEs. All three burden estimates were estimated using linear regression with clustered robust SEs and illustrated in risk matrices with incidence and mean severity. Only health problems that occurred after players' inclusion and during the surveillance period were considered in the analysis of incidence rates. Players who chose to withdraw from the study were excluded, but their data were included up to the point of withdrawal.
Missing health data were not imputed and duplicate OSTRC‐H2 reports were excluded. Overall, we did not impute handball exposure data; however, if players reported an injury and in the same week had a missing value in handball exposure, we imputed the handball exposure to 1 s to avoid these injuries being excluded from the analyses.
3. Results
3.1. Participants and Baseline Injury Status
A total of 945 youth handball players from 20 clubs representing all geographical regions of Denmark completed the baseline questionnaire and engaged in weekly reporting of health problems and exposure time. Participants' ages ranged from 11 to 17 years, with a mean (SD) age of 14.5 (1.5), and 55% were female (Table 1).
TABLE 1.
Baseline player characteristics for 945 players.
| Female | Male | |||||
|---|---|---|---|---|---|---|
| Alla (n = 522) | Low (n = 101) | Moderate (n = 421) | All (n = 422) | Low (n = 88) | Moderate n = 334 | |
| Age group | ||||||
| U13 | 151 (29%) | 25 (25%) | 126 (30%) | 136 (32%) | 25 (28%) | 111 (33%) |
| U15 | 286 (55%) | 58 (57%) | 228 (54%) | 235 (56%) | 53 (60%) | 182 (54%) |
| U17 | 85 (16%) | 18 (18%) | 67 (16%) | 51 (12%) | 10 (11%) | 41 (12%) |
| Age (years) | 14.5 (1.5)b | 14.4 (1.5)c | ||||
| Height (cm) | 167.1 (10.8)d | 174.9 (10.9)e | ||||
| Weight (kg) | 57.3 (10.9)f | 62.8 (14.1)g | ||||
| BMI (kg/m2) | 21.2 (10.9)h | 20.3 (3.0)i | ||||
| Player position | ||||||
| Goalkeeper | 57 (11%) | 50 (12%) | ||||
| Wing | 124 (24%) | 110 (26%) | ||||
| Back players | 143 (27%) | 108 (26%) | ||||
| Line players | 73 (14%) | 51 (12%) | ||||
| Playmaker | 75 (14%) | 57 (14%) | ||||
| No permanent position | 50 (10%) | 45 (11%) | ||||
| Handball experience (years) | 6.8 (2.8)j | 6.3 (2.9) | ||||
| Participation on other handball teams | ||||||
| Talent training | 73 (14%) | 81 (19%) | ||||
| National teams | 4 (1%) | 3 (1%) | ||||
| Senior teams | 2 (0%) | 0 (0%) | ||||
| Older teams | 30 (6%) | 22 (5%) | ||||
| Younger teams | 17 (3%) | 9 (2%) | ||||
| Participation in other sports | 122 (23%) | 122 (29%)j | ||||
| Previous injury | a | |||||
| Yes | 321 (61%) | 71 (70%) | 250 (59%) | 274 (65%) | 61 (69%) | 213 (64%) |
| No | 201 (39%) | 30 (30%) | 171 (41%) | 148 (35%) | 27 (31%) | 121 (36%) |
| Current injury | a | |||||
| Yes | 297 (57%) | 64 (63%) | 233 (55%) | 222 (53%) | 44 (50%) | 178 (53%) |
| No | 225 (43%) | 37 (37%) | 188 (45%) | 200 (47%) | 44 (50%) | 156 (47%) |
Note: Low = Proportion of handball players providing < 10 weeks of responses. Moderate = Proportion of handball players providing > = 10 weeks of responses. Estimates are presented as frequencies (%) or mean (SD). Percentage estimates are rounded to the nearest whole number for visual representation. Missings: amissing, n = 1; bmissing, n = 15; cmissing, n = 14; dmissing, n = 8; emissing, n = 17; fmissing, n = 93; gmissing, n = 26; hmissing, n = 95; Imissing, n = 29; jmissing, n = 2.
At baseline, 595 of the 945 players (63% [95% CI 60%–66%]) reported a past‐year previous injury, while 519 of the 945 players (55% [95% CI 52%–58%]) reported a current injury. Previous and current injuries at baseline, stratified by sex, age groups, and selected body regions, are detailed in Supporting Information S2.
A total of 123 players out of the 945 players were excluded during the season due to dropout: 78 players chose to withdraw because they no longer wished to participate, 39 players stopped playing handball, and 6 players changed clubs during the study period.
The mean weekly response proportion during the study period was 63% in all age groups (range: 42% to 79%). Low responders (< 10 weeks response to the weekly questionnaire) had a higher proportion of previous injuries than moderate responders in injury characteristics at baseline (Table 1).
3.2. Health Problem Prevalence Proportion and Player Availability
During the 30‐week surveillance period, 664/945 players (70%) reported at least one health problem. The average weekly prevalence proportion of health problems for the total sample was 23% (95% CI 21% to 25%), with 17% (95% CI 15% to 19%) attributable to injuries and 6% (95% CI 5% to 7%) to illnesses. Detailed mean weekly health problem data stratified by sex, age groups, and health problem type (injury/illness) are provided in Table 2. Girls had a significantly higher weekly average prevalence proportion in the U15 age group (prevalence proportion difference 10%‐points; 95% CI 6%–15% points) but a significantly lower weekly average prevalence proportion in the U17 age group (prevalence proportion difference −13% points; 95% CI −25% to 2% points).
TABLE 2.
Mean weekly health problem prevalence proportion.
| U13 female (n = 151) | U13 male (n = 136) | |||
|---|---|---|---|---|
| Mean | (95% CI) | Mean | (95% CI) | |
| All health problems | 19% | (15% to 24%) | 15% | (11% to 19%) |
| Injuries | 14% | (10% to 20%) | 9% | (6% to 13%) |
| Sudden‐onset injuries | 6% | (4% to 9%) | 5% | (3% to 8%) |
| Gradual‐onset injuries | 8% | (5% to 13%) | 5% | (3% to 7%) |
| Illness | 4% | (3% to 7%) | 5% | (4% to 7%) |
| Substantial health problems | 9% | (7% to 13%) | 8% | (7% to 10%) |
| Injuries | 7% | (4% to 10%) | 4% | (2% to 6%) |
| Sudden‐onset injuries | 3% | (2% to 6%) | 2% | (1% to 4%) |
| Gradual‐onset injuries | 4% | (2% to 7%) | 1% | (1% to 2%) |
| Illness | 3% | (2% to 4%) | 4% | (3% to 6%) |
| Time‐loss health problems | 11% | (8% to 15%) | 9% | (7% to 12%) |
| Injuries | 8% | (5% to 11%) | 5% | (3% to 6%) |
| Sudden‐onset injuries | 4% | (2% to 7%) | 2% | (1% to 4%) |
| Gradual‐onset injuries | 4% | (2% to 6%) | 2% | (1% to 3%) |
| Illness | 3% | (2% to 4%) | 5% | (4% to 7%) |
| U15 female (n = 286) | U15 male (n = 235) | |||
| Mean | (95% CI) | Mean | (95% CI) | |
| All health problems | 30% | (27% to 35%) | 18% | (15% to 22%) |
| Injuries | 23% | (19% to 27%) | 12% | (10% to 15%) |
| Sudden‐onset injuries | 9% | (7% to 11%) | 4% | (3% to 6%) |
| Gradual‐onset injuries | 14% | (11% to 18%) | 8% | (6% to 11%) |
| Illness | 8% | (6% to 9%) | 6% | (5% to 7%) |
| Substantial health problems | 17% | (14% to 20%) | 10% | (8% to 13%) |
| Injuries | 11% | (9% to 14%) | 6% | (5% to 8%) |
| Sudden‐onset injuries | 6% | (4% to 8%) | 3% | (2% to 4%) |
| Gradual‐onset injuries | 5% | (4% to 7%) | 4% | (2% to 6%) |
| Illness | 5% | (4% to 7%) | 4% | (3% to 5%) |
| Time‐loss health problems | 20% | (18% to 23%) | 13% | (11% to 15%) |
| Injuries | 14% | (11% to 17%) | 7% | (6% to 10%) |
| Sudden‐onset injuries | 6% | (5% to 8%) | 3% | (2% to 4%) |
| Gradual‐onset injuries | 8% | (6% to 10%) | 4% | (3% to 6%) |
| Illness | 7% | (5% to 8%) | 5% | (4% to 7%) |
| U17 female (n = 85) | U17 male (n = 51) | |||
| Mean | (95% CI) | Mean | (95% CI) | |
| All health problems | 27% | (21% to 35%) | 36% | (27% to 48%) |
| Injuries | 19% | (13% to 26%) | 32% | (24% to 44%) |
| Sudden‐onset injuries | 11% | (7% to 17%) | 13% | (8% to 21%) |
| Gradual‐onset injuries | 8% | (5% to 13%) | 19% | (12% to 32%) |
| Illness | 9% | (7% to 13%) | 4% | (3% to 6%) |
| Substantial health problems | 14% | (10% to 19%) | 21% | (13% to 33%) |
| Injuries | 8% | (5% to 13%) | 18% | (11% to 30%) |
| Sudden‐onset injuries | 5% | (3% to 9%) | 9% | (5% to 16%) |
| Gradual‐onset injuries | 3% | (2% to 7%) | 9% | (4% to 22%) |
| Illness | 7% | (5% to 8%) | 5% | (4% to 8%) |
| Time‐loss health problems | 16% | (12% to 21%) | 27% | (19% to 39%) |
| Injuries | 10% | (7% to 15%) | 24% | (16% to 35%) |
| Sudden‐onset injuries | 6% | (3% to 9%) | 9% | (6% to 16%) |
| Gradual‐onset injuries | 5% | (2% to 8%) | 14% | (7% to 27%) |
| Illness | 6% | (4% to 8%) | 4% | (2% to 6%) |
Abbreviations: n, numbers; 95% CI, 95% confidence interval.
The mean weekly proportion of players who were unable to participate in any handball activities was 7% (95% CI 6% to 8%), but this varied throughout the season (Figure 1A,B).
FIGURE 1.
(A) Player availability (%) over 30 weeks due to injuries. Numbers on the x‐axis refer to calendar week. (B) Player availability (%) over 30 weeks due to illnesses. Numbers on the x‐axis refer to calendar week.
3.3. Injuries and Burden
Players reported 881 new (n = 737) and recurrent injuries (n = 144) during 59 171 handball exposure hours, resulting in an overall injury incidence rate of 14.9 (95% CI 13.9 to 15.9) per 1000 h. In the age groups below 15 years, the incidence rates of gradual‐onset injuries exceeded those of sudden‐onset injuries, whereas in the 15–17 age group, the incidence rates of sudden‐onset injuries were higher than those of gradual‐onset injuries. Of the 144 recurrent injuries reported, 104 were early recurrences. Among these, females reported 105 recurrent injuries, while males reported 39 recurrent injuries. Table 3 displays the injury incidences, incidence rates, incidence rate ratios, and burden estimates stratified by sex, age group, and injury mechanism (gradual‐onset/sudden‐onset). Supporting Information S3 and S4 provide detailed injury data by body region and sex, showing that female players had a higher incidence rate of sudden‐onset knee injuries compared to males (IRR 2.3, 95% CI: 1.2–4.5).
TABLE 3.
Injury incidence, incidence rates, and burden by age group and sex.
| Incidence | Exposure | Incidence rate | Incidence rate ratio | Incidence rate ratio | Burden | ||
|---|---|---|---|---|---|---|---|
| n | Hour | Injuries per 1000 h (95% CI) | IRR (95% CI) (Sex) | IRR (95% CI) (Injury type and exposure) | Mean number of weeks affected by injury (95% CI) | ||
| U13 | |||||||
| Female (n = 151) | Total | 137 | 9052 | 15.1 (12.8 to 17.9) | Reference | 2.3 (1.7–2.9) | |
| Gradual‐onset | 74 | 9052 | 8.2 (6.5 to 10.3) | Reference | Reference | 2.2 (1.4–2.9) | |
| Sudden‐onset | 63 | 9052 | 7.0 (5.3 to 8.9) | Reference | 0.9 (0.6 to 1.2) | 2.3 (1.4–3.2) | |
| Training* | 24 | 6822 | 3.5 (2.3 to 5.2) | Reference | Reference | ||
| Match* | 24 | 2230 | 10.8 (6.9 to 16.0) | Reference | 3.1 (1.7 to 5.6) | ||
| Male (n = 136) | Total | 91 | 7148 | 12.7 (10.4 to 15.6) | 0.8 (0.6 to 1.1) | 1.8 (1.5–2.2) | |
| Gradual‐onset | 46 | 7148 | 6.4 (4.8 to 8.6) | 0.8 (0.5 to 1.1) | Reference group | 1.8 (1.3–2.2) | |
| Sudden‐onset | 45 | 7148 | 6.3 (4.7 to 8.4) | 0.9 (0.6 to 1.3) | 1.0 (0.6 to 1.5) | 1.7 (1.2–2.3) | |
| Training* | 15 | 5624 | 2.7 (1.5 to 4.4) | 0.8 (0.4 to 1.4) | Reference group | ||
| Match* | 16 | 1524 | 10.5 (6.0 to 17.1) | 0.9 (0.5 to 1.8) | 3.9 (1.8 to 8.5) | ||
| U15 | |||||||
| Female (n = 286) | Total | 313 | 19 682 | 15.9 (14.2 to 17.8) | Reference | 2.3 (2.0–2.7) | |
| Gradual‐onset | 188 | 19 682 | 9.6 (8.3 to 11.0) | Reference | Reference | 2.2 (1.9–2.6) | |
| Sudden‐onset | 125 | 19 682 | 6.4 (5.3 to 7.6) | Reference | 0.7 (0.5 to 0.8) | 2.4 (1.8–3.0) | |
| Training* | 40 | 16 654 | 2.4 (1.7 to 3.3) | Reference | Reference | ||
| Match* | 70 | 3028 | 23.1 (18.0 to 29.2) | Reference | 9.6 (6.4 to 14.6) | ||
| Male (n = 235) | Total | 204 | 15 461 | 13.2 (11.5 to 15.1) | 0.8 (0.7 to 1.0) | 2.0 (1.7–2.4) | |
| Gradual‐onset | 127 | 15 461 | 8.2 (6.9 to 9.8) | 0.9 (0.7 to 1.1) | Reference | 1.9 (1.6–2.3) | |
| Sudden‐onset | 77 | 15 461 | 5.0 (3.9 to 6.2) | 0.8 (0.6 to 1.0) | 0.6 (0.5 to 0.8) | 2.0 (1.5–2.4) | |
| Training* | 30 | 12 819 | 2.3 (1.6 to 3.3) | 1.0 (0.6 to 1.6) | Reference | ||
| Match* | 37 | 2642 | 14.0 (10.0 to 19.3) | 0.6 (0.4 to 0.9) | 6.0 (3.6 to 10.0) | ||
| U17 | |||||||
| Female (n = 85) | Total | 83 | 5107 | 16.3 (13.1 to 20.2) | Reference | 2.5 (1.9–3.2) | |
| Gradual‐onset | 38 | 5107 | 7.4 (5.4 to 10.2) | Reference | Reference | 1.7 (1.3–2.0) | |
| Sudden‐onset | 45 | 5107 | 8.8 (6.6 to 11.8) | Reference | 1.2 (0.8 to 1.9) | 3.2 (2.1–4.3) | |
| Training* | 14 | 4176 | 3.4 (1.8 to 5.6) | Reference | Reference | ||
| Match* | 28 | 931 | 30.1 (20.0 to 43.5) | Reference | 9.0 (4.6 to 18.4) | ||
| Male (n = 51) | Total | 53 | 2720 | 19.5 (14.9 to 25.5) | 1.2 (0.8 to 1.7) | 4.1 (2.5–5.8) | |
| Gradual‐onset | 25 | 2720 | 9.2 (6.2 to 13.6) | 1.2 (0.7 to 2.0) | Reference | 4.3 (1.8–6.9) | |
| Sudden‐onset | 28 | 2720 | 10.3 (6.9 to 14.9) | 1.2 (0.7 to 1.9) | 1.1 (0.6 to 2.0) | 3.6 (2.0–5.2) | |
| Training* | 13 | 2253 | 5.8 (3.1 to 9.9) | 1.7 (0.8 to 3.7) | Reference | ||
| Match* | 14 | 467 | 30.0 (17.4 to 50.3) | 1.0 (0.5 to 1.9) | 5.2 (2.3 to 12.0) | ||
Note: Sex and age group = 1 missing; *Sudden‐onset injuries; a total of 58 injuries were not classified as either match or training injuries.
Abbreviations: CI, 95% confidence interval; n, numbers.
Gradual‐onset knee injuries accounted for the highest injury burden in both females and males across all three burden estimates. Figure 2 illustrates the incidence and severity of injuries with the highest burden based on weeks with reported injury, while burden estimates based on time loss and OSTRC‐H2 severity score are provided in Supporting Information S5a and S5b.
FIGURE 2.
Risk matrices illustrating the incidence of all injuries with sudden and gradual‐onset and their severity (mean no. of weeks affected by injury) by sex. Only specific body regions are presented. Darker yellow represents greater injury burden and the curved lines indicate equal injury burden.
3.4. Illness Incidence Proportion
A total of 827 new illnesses were reported, with 425 players (45%) experiencing at least one illness during the surveillance period. The most frequently reported reason for illness was a COVID‐19 infection, accounting for 34% (95% CI 30% to 39%) of illnesses among female players and 38% (95% CI 33% to 44%) among male players. Psychological symptoms (e.g., depression, anxiety) and non‐COVID respiratory difficulties were infrequently reported (Supporting Information S6). On average, females were affected by illnesses for 1.4 (95% CI 1.3 to 1.6) weeks, while males were affected for 1.2 (95% CI 1.1 to 1.3) weeks, with 1.1 (95% CI 1.0 to 1.2) weeks of time loss due to illness for both sexes.
4. Discussion
This is the first study to prospectively track all health problems in a large cohort of youth community‐level handball players, including players under age 13 throughout a season. The injury incidence rate was high across age groups. Female players aged 13–15 years had a higher overall incidence rate and weekly average prevalence proportion compared to age‐matched male players. Gradual‐onset injuries were frequently reported, with gradual‐onset knee injuries being the most burdensome for both female and male players. Almost half of all reported new index or recurrent health problems were related to illness.
4.1. Injuries
We found a high overall and gradual‐onset incidence rate compared to previous studies [12, 21]. These disparities may be attributed to our inclusion of a younger age group, a community sport population, and the use of a broad injury definition. Nevertheless, our findings highlight the need for injury prevention initiatives to address gradual‐onset injuries in this population, particularly those affecting the knee, lower leg, and shoulder, as these were the most frequent and burdensome across sexes. This expands the existing primary prevention approach, which primarily targets sudden‐onset ankle and knee injuries and overall shoulder injuries via exercise‐based injury prevention programs [22, 23, 24, 25], and underscores an urgent need to gain a greater understanding of gradual‐onset injuries in this population. Specifically, it is essential to determine whether these issues involve actual tissue damage or are linked to pain only [26] and to clarify the types of injuries or pain syndromes encompassed by terms like for instance “lower leg”. Moreover, understanding the etiology, including factors such as growth, maturation [27, 28], and sudden increases in training load [29, 30] is critical for developing effective prevention and management strategies.
Importantly, we found a lower average severity of all injuries (Figure 2) compared to previous research involving older players from higher levels [12], and that the vast majority play handball while injured. While we cannot explain this finding based on the available data, it may be attributed to the inclusion of a younger age group and a community sport population. Still, the variability in injury duration (ranging from 0 to 16 weeks) underscores the need for further investigation into secondary and tertiary prevention and management strategies. Particularly, there is a critical need to guide decisions on when to continue playing with pain or injury, when to stop and seek professional care, and when to return to sport. This is especially important as many of our reported injuries were recurrent, consistent with previous studies [12, 21].
Our study showed tendencies of sex differences in injury reports, with females between 13 and 15 reporting a higher overall incidence rate and substantially higher mean weekly prevalence of injuries compared to males. However, this trend reversed in the age group of 15–17, although this should be interpreted with caution due to the smaller sample size in the oldest age group. Across sex, shoulder, knee, ankle/foot, hand, and lower leg were the most reported injury locations, but female players had almost twice the sudden‐onset knee injury rate compared to males, aligning with our previous findings [12]. Previous research on sex differences in overall injury rates in handball has shown mixed results [31, 32]. Across sports, it is well established that adolescent female athletes have a higher and increasing risk of serious knee injuries, such as anterior cruciate ligament injuries, compared to males, which may be partly explained by women's increasing participation in sports globally [33]. Substantial research supports that exercise‐based programs effectively prevent such injuries [34], and further research is thus urgently needed to improve the implementation of these programs.
Additionally, it is important to further examine relevant factors contributing to the knee injury rates in adolescent female athletes. We suggest that this should involve investigating sex and gender differences in the bio‐psychosocial aspects of sports participation [35]. From a biological perspective, this includes examining sex differences in physical development during adolescence alongside sports participation [36]. Recent findings suggest that female handball players may have a lower tolerance for weekly increases in training loads than males [37]. This reduced tolerance may partly result from greater fat mass gains and smaller increases in leg muscle mass, strength, and power during adolescence [38, 39], highlighting the relevance of including biological age rather than chronological age alone in future studies. However, these biological aspects should be investigated within the broader context of sports participation [40], incorporating psychosocial and sociocultural perspectives using interdisciplinary approaches to better understand and explain these sex differences in injury rates in youth sports [41].
The high proportion of players reporting injuries at baseline further underscores the critical need for targeted injury prevention from a young age to reduce early dropout, injury recurrence, and long‐term musculoskeletal issues [5, 42].
4.2. Illnesses
We found a higher mean weekly prevalence proportion of illnesses than in our previous Danish cohort of youth players [12], likely due to the COVID‐19 pandemic. COVID‐19 infection accounted for 36% of reported illnesses, reflecting broader public health trends [43]. Still, our prevalence proportions were lower than those reported by Bjørndal et al. (9%) [14], which may be due to their participants reporting daily whereas ours reported on a weekly basis potentially underestimating our reports. Further, our study included a two‐week national lockdown of sporting activities, which seemingly reduced illness reports during that period (Figure 1b). The illness‐related player unavailability increased in the weeks following the lockdown, significantly impacting handball participation (Figure 1b). Further research is needed to explore the relationship between illness, handball participation, and injury risk.
We found a low incidence of mental illness symptoms (e.g., depression, anxiety), which is notable given COVID‐19's impact on children's lives in the general Danish population in the same time period of our study [44]. Our study design does not allow us to explain this finding, but it is likely that the OSTRC‐H2 questionnaire does not adequately capture general wellbeing, highlighting the need for specific tools to better assess mental health in this age group.
4.3. Methodological Considerations
The study's methodological strengths include its prospective design, allowing weekly participant monitoring throughout a handball season, reducing recall bias [45]. The large sample size of our study, which covers a wide range of age groups and both sexes, enhances the applicability of our findings.
Limitations include the fact that players in this study were introduced to an injury prevention exercise program through their coaches, which may have influenced our reported injury epidemiology estimates, despite low adherence to the program [15]. Other limitations include the relatively low mean weekly response proportion. This may be partly due to challenges posed by the COVID‐19 pandemic and the inclusion of community‐level players, who may lack a clear incentive to participate in injury surveillance projects [46]. In our study, we applied the most commonly used approach in epidemiological research and did not impute missing data. Thus, weeks with missing athlete responses were treated as nonexistent in the analyses. This approach may have influenced our epidemiological outcomes compared to complete case analyses or approaches that include only participants with a minimum response rate (e.g., > 20%) [47]. Low responders in our study had a higher proportion of previous injuries, potentially leading to an underestimation of our epidemiological reports. Future studies should explore the impact of individual response proportions by, for example, preanalyzing data to define study‐specific cut‐offs for minimal response proportion in analyses of epidemiological outcomes [47].
Limitations also include the lack of specific diagnosis, and absence of clinical verification and objective medical assessment of reported injuries, which may have led to misclassification [48]. Additionally, using a broad injury definition may lead to the classification of delayed‐onset muscle soreness as gradual‐onset injuries, potentially leading to an overestimation of injury incidence. However, in this study, a great effort was made to qualify the self‐report by adapting the definitions of injuries and health problems to the adolescent target group (Supplementary File S1). Further, handball exposure was also based on self‐report only. While we have previously validated self‐reported injuries and handball exposure versus onsite registration for players over 14 years old, this validation has not been conducted for those under 14 years [49]. Lastly, we did not measure players' weekly exposure to other sports, which may have contributed to the recorded injuries.
The study was conducted during the COVID‐19 pandemic, which could have influenced both participation and the general health of the players. The extent of COVID‐19's impact remains unclear, and it may introduce an unknown factor in the interplay between sport, injury, illness, and performance.
5. Perspective
Our findings suggest that injury prevention initiatives in community handball should address both sudden‐onset and gradual‐onset injuries, with particular attention to gradual‐onset knee injuries. Early intervention is critical, as players aged 11–13 years in this cohort had already sustained injuries before the study began. Females had twice the sudden‐onset knee injury rate, while females aged 13–15 had a higher overall injury rate and average weekly prevalence proportion compared to age‐matched males. In the 15–17 age group, males had a higher incidence rate and prevalence proportion than females, though this should be interpreted cautiously due to the smaller sample size in the oldest group. Understanding these sex‐based injury trends warrants further investigation integrating the bio‐psychosocial aspects of sports participation utilizing interdisciplinary approaches. Illness accounted for over half of newly reported health problems and substantially affected player availability at certain times. Illness's potential impact on injury risk in this population should be investigated further.
Author Contributions
All authors contributed to the manuscript preparation. M.M., E.M.R., and A.K. contributed to the planning of the study. A.C.L. performed the analyses with guidance from S.M., and M.M., M.M. was responsible for the data collection and is responsible for the overall content (guarantor).
Ethics Statement
The study was approved by The Regional Committees on Health Research Ethics for Southern Denmark (20212000‐76) and the Danish Data Protection Agency (University of Southern Denmark, 10.925).
Conflicts of Interest
The authors declare no conflicts of interest.
Supporting information
Supporting Information S1. Key definitions through the lens of Danish youth athletes.
Supporting Information S2. Previous and current injuries by body region, sex, and age group.
Supporting Information S3. Risk matrix table for females (n = 522). Sudden‐onset and gradual‐onset injuries by body region.
Supporting Information S4. Risk matrix table for males (n = 422). Sudden‐onset and gradual‐onset injuries by body region.
Figure S5b. Risk matrices illustrating the incidence of all injuries with sudden and gradual‐onset and their severity based on the Oslo Sports Trauma Research Center severity score by sex. Only specific body regions are presented. Darker yellow represents greater injury burden and the curved lines indicate equal injury burden.
Figure S5b. Risk matrices illustrating the incidence of all injuries with sudden and gradual‐onset and their severity based on weeks with time loss by sex. Only specific body regions are presented. Darker yellow represents greater injury burden and the curved lines indicate equal injury burden.
Supporting Information S6 Categorization for illnesses.
Acknowledgments
The authors sincerely thank all the players for their invaluable contributions to this study and Alex Pedersen for his assistance with data collection. Dr. Roar Amundsen is also acknowledged for his support in developing the risk matrices (Figure 1a,b, and Supplementary Files S5a,b).
Funding: This work was supported by University of Southern Denmark, the Danish Handball Federation, Team Denmark, Danish Gymnastics and Sports Associations, Ministry of Culture in Denmark research funding (FPK.2018‐0067), Østifterne (2020‐0277), The Foundation for Advancement of Chiropractic Research and Postgraduate Education (A3488).
Data Availability Statement
The data that support the findings of this study are available from the corresponding author upon reasonable request.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Supporting Information S1. Key definitions through the lens of Danish youth athletes.
Supporting Information S2. Previous and current injuries by body region, sex, and age group.
Supporting Information S3. Risk matrix table for females (n = 522). Sudden‐onset and gradual‐onset injuries by body region.
Supporting Information S4. Risk matrix table for males (n = 422). Sudden‐onset and gradual‐onset injuries by body region.
Figure S5b. Risk matrices illustrating the incidence of all injuries with sudden and gradual‐onset and their severity based on the Oslo Sports Trauma Research Center severity score by sex. Only specific body regions are presented. Darker yellow represents greater injury burden and the curved lines indicate equal injury burden.
Figure S5b. Risk matrices illustrating the incidence of all injuries with sudden and gradual‐onset and their severity based on weeks with time loss by sex. Only specific body regions are presented. Darker yellow represents greater injury burden and the curved lines indicate equal injury burden.
Supporting Information S6 Categorization for illnesses.
Data Availability Statement
The data that support the findings of this study are available from the corresponding author upon reasonable request.