Abstract
Mass gatherings, particularly in the context of sporting events, pose distinct public health challenges, particularly regarding the medical needs of athletes. Despite the critical role of on-site medical care in reducing hospital transfers, studies that directly compare injury patterns across various sporting events are scarce. This study analyzed injury rates and severity among athletes participating in various sports during the National Games in Taiwan. By doing so, the study aimed to enhance medical preparedness for future large-scale sporting events. This retrospective study involved a chart review of athletes who sought medical support during the National Games in Taiwan in 2017, 2019, and 2021. Data on patient demographics, event type, injury characteristics, and the need for hospital transport were collected. Sports were categorized in accordance with the American Heart Association and American College of Cardiology classifications ( based on their static and dynamic components). Statistical analyses were conducted to determine injury rates and identify factors associated with hospital transfers. Over the three years, 20,585 athletes participated in the games, with 527 (2.56%) seeking medical support. Injury rates significantly varied among the groups of sports with differing static and dynamic demands. Sports classified as having both high static and dynamic demands had the highest injury rates. Handball, martial arts, and rowing resulted in the highest rates of medical support-seeking behavior. The need for hospital transport was more frequently associated with sports that involved both high static and dynamic demands. The study highlights the varying injury patterns across different sports in mass gatherings, with sports involving higher physical demands posing greater risks of injury. These findings underscore the importance of developing tailored medical preparedness strategies for different types of sports to ensure timely and effective provision of medical care during large-scale sporting events.
Keywords: Mass gatherings, Sports injuries, Athlete medical care, National games in Taiwan, Static and dynamic sports classification, Retrospective chart review, Injury rate, Hospital transport, Public health, Event medical preparedness
Subject terms: Public health, Health care, Risk factors
Introduction
Mass gatherings, as defined by the World Health Organization (WHO), refer to a concentration of individuals at a specific location for a specific purpose over a set period, potentially placing strain on the planning and response capacities of the host country or community1. These gatherings can be classified into two categories: spontaneous and planned, with the latter including sporting, cultural, religious, and political events1. The field of mass gathering medicine focuses on managing emergencies in settings where large crowds are present, often resulting in delayed response times due to restricted access to patients or other environmental and locational factors2. This field represents a considerable public health challenge related to the well-being of attendees, the local population, and the health-care personnel involved3. WHO statistics indicate that, on average, 1–2% of attendees at a mass gathering will require some form of first aid or medical care. Of these, approximately 10% will require ongoing on-site treatment, and approximately 1% will require transport to a hospital by ambulance1.
One study demonstrated that the presence of on-site physicians can reduce the number of ambulance transports by up to 89%4. However, research comparing various events, particularly different types of sporting events, remains limited. Most studies have focused on single mass gathering events5,6 or trends observed over five years7,8, primarily addressing overall injuries rather than those specific to athletes. Research on mass gathering sporting events, especially those involving athletes, has predominantly centered on marathons9. These events are characterized by a highly energetic and potentially emotionally charged atmosphere, which increases the risks of injuries, violence, and cardiovascular events1. The American Heart Association and the American College of Cardiology have classified sports based on their strength component, measured by the relative intensity of static muscle contractions, and their endurance component, reflected by the relative intensity of dynamic exercise10.
This study specifically focuses on analyzing injury patterns among athletes participating in the Taiwan National Games, excluding injuries unrelated to competitions, such as those caused by spectators, crowding, dehydration, projectiles, or terrorist attacks. The objective of this study was to analyze athletes’ injury patterns across various sporting events by employing the aforementioned classifications to enhance medical preparedness for future mass-gathering sporting events.
Method
Data source
Institutional review board approval
We conducted a retrospective chart review of all athletes who sought medical support during Taiwan’s National Games in 2017, 2019 and 2021. These games are premier national sporting events, featuring thousands of athletes competing in 45 different sports categories. The study protocol was approved by the Institutional Review Board of Taipei Medical University (IRB No. N202305083).
Participants
This study was conducted in accordance with the institutional guidelines, approved by the Institutional Review Board of Taipei Medical University (IRB No. N202305083). Due to the retrospective nature of the study, Institutional Review Board of Taipei Medical University waived the requirement for obtaining informed consent. The National Games in Taiwan, typically held every two years in October, are the country’s leading national sporting event, featuring thousands of athletes competing in 45 categories (with some variation between years). The participants are elite athletes representing various counties in Taiwan, many of whom are either current or prospective Olympics and national team delegates. All competition venues hosting the National Games meet the standards required for international sporting events.
A retrospective review of all individuals seeking medical support during the National Games in 2017, 2019, and 2021 was conducted. The data collected included the year of the event, event type, (whether it was held indoors or outdoors), duration of the competition (in days), sex, age, identity (i.e., athlete, referee, coach, staff, or audience member), chief complaint, injury site, chronic disease, on-site treatment, and disposition (i.e., whether the patient received an ambulance transport).
This study exclusively focused on injuries sustained by athletes during competition events. Non-competition-related injuries, such as those caused by crowding, dehydration, or other environmental factors, were not included in the scope of analysis.
Patients identified as referees, coaches, staff members, or audience members were excluded; only athletes were retained in the analysis. This decision was made because the excluded patients predominantly experienced minor injuries, with only one requiring a transfer to the hospital for further management. Figure 1 presents a flowchart illustrating the participant selection process for this study. A total of 690 medical support instances were recorded during the National Games in 2017, 2019, and 2021. After excluding 163 non-athlete cases, including 13 referees and 4 coaches, the final dataset comprised 527 athletes. This flowchart emphasizes the systematic application of exclusion criteria, ensuring that the analysis remained focused exclusively on athletes. This approach aligns with the study’s objective of investigating injury patterns specific to participants in competitive events.
Fig. 1.
Study flowchart.
Procedure for collecting and analyzing medical data
Classification of sports
The American Heart Association and American College of Cardiology and American College of Cardiology (ACC) classify sports on the basis of two key components: representing strength is the static component, which is the relative intensity (low, moderate, or high) of static muscle contractions, and representing endurance is the dynamic component, which is the relative intensity (low, moderate, or high) of dynamic exercise [5]. The 45 sports included in this study were categorized following the AHA/ACC framework. The sports involved in the National Games in Taiwan were categorized in this manner, as outlined in the AHA/ACC recommendations. While we acknowledge that some sports, such as track and field, encompass events with varying static and dynamic intensities (e.g., shot put vs. marathon), the classification applied here is based on the overarching categorization provided by the AHA/ACC guidelines to maintain consistency and comparability. This study identified 14, 13, and 18 sports with high, moderate, and low static demands, respectively, and 10, 12, and 23 sports with low, moderate, and high dynamic demands, respectively. Table 1 presents the classification of sports based on the aforementioned criteria. Sports categorized with high static or high dynamic demands tend to involve greater physical exertion, increasing the likelihood of musculoskeletal injuries. Additionally, sports that require both high static and high dynamic components, such as wrestling and rowing, impose significant strain on athletes, potentially leading to an increased incidence of both acute and overuse injuries.
Table 1.
Sport categories by static and dynamic demands.
| Sport | Static | Dynamic | ||||
|---|---|---|---|---|---|---|
| Low | Moderate | High | Low | Moderate | High | |
| Archery | V | V | ||||
| Badminton | V | V | ||||
| Baseball | V | V | ||||
| Basketball | V | V | ||||
| Beach volleyball | V | V | ||||
| Boating | V | V | ||||
| Bowling | V | V | ||||
| Boxing | V | V | ||||
| Canoe obstacle slalom | V | V | ||||
| Canoeing | V | V | ||||
| Cycling | V | V | ||||
| Diving | V | V | ||||
| Equestrian | V | V | ||||
| eSports | V | V | ||||
| Fencing | V | V | ||||
| Rugby | V | V | ||||
| Golf | V | V | ||||
| Gymnastics | V | V | ||||
| Handball | V | V | ||||
| Hockey | V | V | ||||
| Judo | V | V | ||||
| Kabaddi | V | V | ||||
| Karate | V | V | ||||
| Marathon | V | V | ||||
| Martial arts | V | V | ||||
| Modern pentathlon | V | V | ||||
| Open water | V | V | ||||
| Roller skating | V | V | ||||
| Rowing | V | V | ||||
| Sailing | V | V | ||||
| Shooting | V | V | ||||
| Soccer | V | V | ||||
| Soft tennis | V | V | ||||
| Softball | V | V | ||||
| Swimming | V | V | ||||
| Table tennis | V | V | ||||
| Taekwondo | V | V | ||||
| Tennis | V | V | ||||
| Track and field | V | V | ||||
| Triathlon | V | V | ||||
| Volleyball | V | V | ||||
| Water polo | V | V | ||||
| Water sports | V | V | ||||
| Weightlifting | V | V | ||||
| Wrestling | V | V | ||||
Outcomes: calculation of injury rates based on sport categories
The primary outcome measure in this study was the injury rate among athletes. The secondary outcome was the severity of injuries, with a focus on whether hospitalization was required. The transport to hospital rate was calculated as (number of athletes transported to hospital/number of athletes seeking medical support) × 100%. Additionally, we defined the rate of seeking medical support per 10 games for presentation purposes. While the raw occurrence rate per game (typically < 1) was accurate, presenting the data per 10 games provided a more intuitive and interpretable metric for understanding the frequency of medical support requests across multiple games.
Statistical analysis
The categorical variables of independent groups were compared using the chi-square test or Fisher’s exact test, where applicable, and are presented as numbers and percentages. The continuous data of independent groups were compared using Student’s t tests, a statistical method for comparing the means of two independent groups, and are presented as means and standard deviations (SDs). In addition, analysis of variance (ANOVA) was used for more than two group comparisons. Multivariable logistic regression was performed to assess the effects of multiple influential factors on the target outcomes. A p value of < 0.05 was considered statistically significant for all analyses.
Results
In 2017, a total of 39 events were held, followed by 40 events in both 2019 and in 2021, although the types of events did not completely overlap across the years. A total of 6,773 athletes participated in the 2017 events, 7,332 athletes in 2019, and 7,575 athletes in 2021 (Table 2). Over the three years, participation in high static and high dynamic demand sports increased, aligning with the overall rise in athlete numbers.
Table 2.
Athlete information.
| Characteristic/year | Overall | 2017 | 2019 | 2021 | p | |
|---|---|---|---|---|---|---|
| Number of sports (n) | 42 | 39 | 40 | 40 | ||
| Number of Sports classified by static demands | ||||||
| Low | 22 | 22 | 23 | |||
| Moderate | 19 | 22 | 19 | |||
| High | 35 | 37 | 41 | |||
| Number of Sports classified by dynamic demands | ||||||
| Low | 23 | 22 | 21 | |||
| Moderate | 18 | 19 | 17 | |||
| High | 35 | 40 | 45 | |||
| Athletes(n) | 21,679 | 6773 | 7332 | 7574 | ||
| Sex | ||||||
| Female | 9156 (42.25%) | 2840 (41.93%) | 3093 (42.18%) | 3233 (42.69%) | 0.3249 | |
| Male | 12,280 (56.67%) | 3879 (57.27%) | 4189 (57.13%) | 4212 (55.61%) | ||
| Mix game | 233 (1.08%) | 54 (0.80%) | 50 (0.68%) | 129 (1.70%) | ||
| Sports classified by static demands | 0.9993 | |||||
| Low | 37 (31.09%) | 12 (30.77%) | 12 (30.00%) | 13 (32.50%) | ||
| Moderate | 33 (27.73%) | 11 (28.21%) | 11 (27.50%) | 11 (27.50%) | ||
| High | 49 (41.18%) | 16 (41.03%) | 17 (42.50%) | 16 (40.00%) | ||
| Athletes in sports classified by static demands | 0.0186 | |||||
| Low | 5944 (27.42%) | 1896 (27.99%) | 1946 (26.54%) | 2102 (27.75%) | ||
| Moderate | 4640 (21.40%) | 1523 (22.49%) | 1502 (20.49%) | 1615 (21.32%) | ||
| High | 11,095 (51.18%) | 3354 (49.52%) | 3884 (52.97%) | 3857 (50.92%) | ||
| Sports classified by dynamic demands | 0.9973 | |||||
| Low | 30 (25.21%) | 10 (25.64%) | 10 (25.00%) | 10 (25.00%) | ||
| Moderate | 32 (26.89%) | 11 (28.21%) | 11 (27.50%) | 10 (25.00%) | ||
| High | 57 (47.90%) | 18 (46.15%) | 19 (47.50%) | 20 (50.00%) | ||
| Athletes in sports classified by dynamic demands | < 0.001 | |||||
| Low | 3797 (17.15%) | 1214 (17.92%) | 1249 (17.03%) | 1334 (17.61%) | ||
| Moderate | 5497 (25.36%) | 1904 (28.11%) | 1864 (25.42%) | 1729 (22.83%) | ||
| High | 12,385 (57.13%) | 3655 (53.96%) | 4219 (57.54%) | 4511 (59.56%) | ||
Athlete characteristics and sport categorization
Regarding sex, 9,156 (42.25%) athletes were female and 12,280 (56.67%) were male, with the difference between sexes being non-significant. When categorizing athletes on the basis of the static demands of their respective sport, 5,944 athletes (27.42%), 4,640 athletes (21.40%), and 11,095 athletes (51.18%) were found to have participated in a sport belonging to the low, moderate, and high demand groups, respectively; this variation was significant (p = 0.0186). Over time, the number of sports classified as high static demand increased from 35 in 2017 to 41 in 2021, while the number of high dynamic demand sports rose from 35 to 45, reflecting a shift toward more physically demanding competitions. Similarly, when classified on the basis of the dynamic component, 3,797 athletes (17.15%), 5,497 athletes (25.36%), and 12,385 athletes (57.13%) were found to have participated in a sport belonging to the low, moderate, and high dynamic demand groups, respectively, with the variation being significant (p < 0.001).
Medical support utilization and injury rates
Table 3 provides an overview of the athletes who sought medical support during the competitions. The proportion of athletes seeking medical support increased across the study period, with 156 (2.30%) sought medical support in 2017, 149 (2.03%) in 2019, and 222 (2.93%) in 2021, with these differences being significant (p < 0.001). When categorized by sex, 69 (44.23%) female athletes sought medical support in 2017, 58 (38.93%) in 2019, and 93 (41.89%) in 2021. The numbers of athletes of the two sexes seeking medical support were not significantly different (p = 0.6424). Regarding age, the average age of the athletes who sought medical support was 22.30 ± 6.04 years in 2017, 21.62 ± 6.79 years in 2019, and 23.40 ± 7.76 years in 2021, with no significant differences discovered (p = 0.1044).
Table 3.
Numbers and percentages of patients who sought medical support (n [%]).
| Characteristic\year | 2017 | 2019 | 2021 | p | |
|---|---|---|---|---|---|
| Seeking medical support | 156 (2.30%) | 149 (2.03%) | 222 (2.93%) | < 0.001 | |
| Sex | 0.6424 | ||||
| Female | 69 (44.23%) | 58 (38.93%) | 93 (41.89%) | ||
| Male | 87 (55.77%) | 91 (61.07%) | 129 (58.11%) | ||
| Age (mean, SD), y | 22.30 (6.04) | 21.62 (6.79) | 23.40 (7.76) | 0.1044 | |
| Athletes in sports classified by static demands | < 0.001 | ||||
| Low | 38 (24.36%) | 14 (9.59%) | 62 (27.93%) | ||
| Moderate | 51 (32.69%) | 53 (36.30%) | 33 (14.86%) | ||
| High | 67 (42.95%) | 79 (54.11%) | 127 (57.21%) | ||
| Athletes in games classified by dynamic demands | 0.0015 | ||||
| Low | 20 (12.82%) | 37 (25.34%) | 22 (9.91%) | ||
| Moderate | 46 (29.49%) | 37 (25.34%) | 63 (28.38%) | ||
| High | 90 (57.69%) | 72 (49.32%) | 137 (61.71%) | ||
| Location | 0.0027 | ||||
| Indoor | 82 (52.56%) | 82 (55.03%) | 86 (38.74%) | ||
| Outdoor | 74 (47.44%) | 67 (44.97%) | 136 (61.26%) | ||
| Chief complaint | 0.4159 | ||||
| Injury | 144 (92.31%) | 139 (93.29%) | 196 (88.29%) | ||
| Illness | 8 (5.13%) | 9 (6.04%) | 21 (9.46%) | ||
| Environmental | 4 (2.56%) | 1 (0.67%) | 4 (1.80%) | ||
| Mental health | 0 (00.00%) | 0 (00.00%) | 1 (0.45%) | ||
| Transported to hospital | 40 (0.59%) | 13 (0.18%) | 23 (0.30%) | < 0.001 | |
Injury patterns and sports with the highest injury rates
Tables 4 and 5 summarize the distribution of injuries by sport type and movement demands. Across all years, handball and martial arts consistently ranked among the top sports for medical support requests, while other sports, such as diving and sailing, exhibited substantial year-to-year variations. The highest injury rates were recorded in sports with high static and high dynamic demands, particularly those requiring repetitive forceful movements or sustained endurance.
Table 4.
Five sports for which the rate of athletes seeking medical support was highest (n [%])
| Sport, n(%) | Rank 1 | Rank 2 | Rank 3 | Rank 4 | Rank 5 |
|---|---|---|---|---|---|
| Overall | Handball | Martial arts | Rowing | Soccer | Sailing |
| 45 (0.21%) | 45 (0.21%) | 35 (0.16%) | 30 (0.14%) | 28 (0.13%) | |
| 2017 | Handball | Kabaddi | Soccer | Rugby | Canoe obstacle slalom |
| 18 (0.27%) | 17 (0.25%) | 14 (0.21%) | 8 (0.12%) | 8 (0.12%) | |
| 2019 | Martial arts | Handball | Canoe obstacle slalom | Rugby | Wrestling |
| 25 (0.34%) | 20 (0.27%) | 17 (0.23%) | 14 (0.19%) | 10 (0.14%) | |
| 2021 | Soccer | Sailing | Boating | Martial arts | Wrestling |
| 21 (0.28%) | 21 (0.28%) | 19 (0.25%) | 15 (0.20%) | 11 (0.15%) |
Table 5.
Top five sports with the highest injury rates based on overall participation (2017–2021).
| 2017 | 2019 | 2021 | ||||
|---|---|---|---|---|---|---|
| 1 | Diving | 15.79% | Martial arts | 16.23% | Sailing | 19.81% |
| 2 | Rugby | 8.33% | Rugby | 14.58% | Triathlon | 10.53% |
| 3 | Handball | 7.50% | Diving | 14.29% | Karate | 9.18% |
| 4 | Water polo | 6.67% | Modern Pentathlon | 12.73% | Martial arts | 8.88% |
| 5 | Golf | 6.00% | Handball | 7.81% | Boating | 7.88% |
Across the three tournament years, sports with consistently high injury rates included handball, martial arts, and soccer, which are characterized by high dynamic demands and frequent physical contact. However, other sports, such as diving, sailing, and rugby, also appeared among the top injury-prone sports, varying by year. These sports exhibit a mix of static and dynamic demands, with diving involving high static strength requirements, while rugby and sailing demand a combination of endurance and physical exertion. The variability in injury-prone sports across different years underscores the importance of continuously assessing injury risks based on both participation trends and sport-specific movement characteristics.
Injury occurrences by static and dynamic demands
When examining injury occurrences based on static demand, athletes competing in high static demand sports were more likely to seek medical attention compared to those in moderate or low static demand sports (p < 0.001). This trend was also observed for dynamic demand, where athletes in high dynamic demand sports had a significantly higher likelihood of requiring medical support (p = 0.0015).
Injury distribution across competition venues
A notable shift in injury locations was observed over time. In 2017 and 2019, the percentage of athletes seeking medical assistance at indoor venues was relatively stable at 52.56% and 55.03%, respectively. However, in 2021, significantly fewer athletes sought medical assistance at indoor venues (38.74%, p = 0.0027), indicating a higher proportion of injuries occurring outdoors.
Primary causes of medical assistance
When classified by chief complaint, injury was the predominant problem in all three years, accounting for 144 (92.31%) athletes in 2017, 139 (93.29%) in 2019, and 196 (88.29%) in 2021. Illness was the second most common, affecting 8 (5.13%) athletes in 2017, 9 (6.04%) in 2019, and 21 (9.46%) in 2021. Complaints related to environmental factors—defined as medical issues caused by external environmental conditions, such as insect bites (n = 5), dehydration (n = 2), heat cramps (n = 1), and sunburn (n = 1)— involved 4 (2.56%) athletes in 2017, 1 (0.67%) in 2019, and 4 (1.80%) in 2021. Mental health complaints were rare, with only one case reported in 2021.
Hospitalization trends
The hospitalization rate fluctuated over time. In 2017, 0.59% of injured athletes required hospitalization, whereas in 2019, this rate dropped to 0.18% before slightly increasing to 0.30% in 2021 (p < 0.001).
Sports with the highest injury rates
Across all three years, handball, martial arts, and soccer were consistently associated with the highest number of medical support requests. In 2017, handball (0.27%) and kabaddi (0.25%) had the highest injury rates, while in 2019, martial arts (0.34%) and handball (0.27%) ranked first and second, respectively. By 2021, soccer (0.28%) and sailing (0.28%) emerged as the top injury-prone sports, followed by boating (0.25%) and martial arts (0.20%).
Figure 2 presents the odds ratios (ORs) for athletes seeking medical support in sports with low versus medium static demands. The OR for seeking medical assistance when competing in a sport in the moderate static demand group compared with a sport in the low static demand group was 1.54 (confidence interval [CI] = 1.20–1.98). This indicates that athletes participating in a sport with moderate static demands are significantly more likely to seek medical aid than those participating in a sport with low static demands. For every 10 games, this OR was 1.21 (CI = 0.76–1.94). Regarding hospital transportation, the OR was 2.01 (CI = 0.98–4.15). When the data were scaled for every 10 games, this OR was 1.21 (CI = 0.76–1.94). Regarding hospital transportation, the OR was 2.01 (CI = 0.98–4.15), which decreased slightly to 1.79 (CI = 0.45–7.15) when scaled for every 10 games. Lastly, for the combined outcome of seeking medical support and being transported to the hospital, the OR was 1.37 (CI = 0.63–2.96).
Fig. 2.
Odds ratio of five outcomes among varying sport categories.
Similarly, Fig. 2 also presents the ORs for medical support sought in sports with high versus low static demands. The OR for seeking medical assistance in high static demand sports compared to low static demand sports was 1.30 (CI = 1.04–1.62), which increased to 2.46 (CI = 1.58–3.84) when analyzed over 10 games. This finding indicates that athletes in high static demand sports are consistently more likely to seek medical aid than their counterparts participating in a sport with low static demands, particularly when data are scaled to account for every 10 games. Regarding hospital transfers, the OR was 2.02 (CI = 1.07–3.83), rising to 3.99 (CI = 1.08–14.79) when adjusted for every 10 games,, underscoring a greater likelihood of hospital transport for high static demand sports compared with low static demand sports, especially when adjusted for the 10-game metric. For the combined outcome of seeking aid and being transported to the hospital, the OR was 1.68 (CI = 0.85–3.31).
For moderate dynamic demands, the OR for seeking medical assistance when competing in a sport in the moderate versus low dynamic demand group was 1.28 (CI = 0.97–1.69),increasing slightly to 1.31 (CI = 0.81–2.13) when scaled for every 10 games. Regarding hospital transfers, the OR was 2.01 (CI = 0.98–4.13), rising to 2.22 (CI = 0.60–8.21) per 10 games. Finally, for the combined outcome of seeking medical aid and being transported to the hospital, the OR was 1.71 (CI = 0.79–3.72).
For high dynamic demands, the OR for seeking medical assistance in high versus low dynamic demand sports was 1.16 (CI = 0.91–1.50). When adjusted for every 10 games, the OR was marginally higher at 1.17 (CI = 0.73–1.88). In terms of hospitalizations, the OR was 1.13 (CI = 0.56–2.28), rising to 1.17 (CI = 0.29–4.67) when adjusted for every 10 games. For the combined metric of seeking medical aid and being transported to the hospital, the OR was 0.97 (CI = 0.46–2.06).
Discussion
During the observed years of 2017, 2019, and 2021, the number of events held remained relatively consistent, with 39 events in 2017 and 40 events in both 2019 and 2021. Notably, the types of events varied. Athlete participation increased steadily over these years, rising from 6,773 participants in 2017 to 7,332 in 2019, and reaching 7,575 in 2021. An analysis of the sex distribution revealed 56.67% male and 42.25% female athletes; this difference was nonsignificant. A notable trend was the preference for sports with high static demands and high dynamic demands, as evidenced by a significant majority of athletes participating in these events (51.18% and 57.13%, respectively).
An analysis of the medical support sought during competitions revealed a significant increase in the number of athletes seeking medical attention over time. However, variations in medical support based on sex or age were not significant. Notably, a significant difference in the nature of the sports for which athletes sought medical help was discovered, with help more frequent for athletes participating in events with high static and dynamic demands.
Additionally, sports with dual-motion requirements—those combining both static and dynamic demands—present unique injury risks. While dynamic movements inherently involve a higher likelihood of injuries due to their intensity and physical exertion, the combination of dynamic and static components can amplify overall risk. These dual-motion characteristics require tailored prevention strategies that address both types of physical demands.
Type of competition venue also influenced the number of athletes seeking medical assistance, with notable differences discovered across the years. In 2021, a higher proportion of injuries occurred during outdoor events compared to indoor events, suggesting that external environmental factors, such as weather and terrain, may contribute to increased risks. Injury was the predominant health concern, followed by illness; help was sought in only a few cases for environmental factors or mental health concerns. Other research has indicated that dehydration is a common concern among individuals presenting at medical stations7, and dehydration is often linked to outdoor environments and high heat indices11. However, these studies have typically included spectators, who are less likely to manage hydration as carefully as are athletes. Consequently, athletes, who are generally more aware of their hydration needs, were found to report few cases related to environmental factors in this study.
The hospitalization rate varied annually. Prior research on the effect of mass-gathering events on emergency departments has demonstrated that most patients transported to the emergency room typically present with minor conditions, resulting in a low subsequent hospitalization rate12,13. Although these studies included all participants, including spectators, this study focuses solely on athletes, providing a more specific context for understanding hospitalization trends related to competition-related injuries in mass-gathering settings.
Handball and martial arts were consistently among these sports most frequently leading to medical support throughout the observed period. Other studies have extensively analyzed handball injuries, highlighting shoulder and anterior cruciate ligament (ACL) injuries as the most prevalent14–16. Studies have also confirmed that prevention programs are effective in mitigating the risk of shoulder, lower extremity, knee, ankle, and ACL injuries17. This evidence underscores the importance of implementing preventive measures for handball players and adequately preparing medical support during competitions. Similarly, martial arts have been associated with high injury rates18, with the incidence found to be higher among those with greater experience and competing at a higher competitive level19. This information is crucial for guiding protective strategies for athletes and planning the setup of medical stations for future events.
An analysis of the top five sports with the highest injury rates during the National Games highlights significant year-to-year variations in injury risk (Table 5). These findings demonstrate that while certain sports, such as martial arts and handball, consistently rank among those with high injury rates, other sports like diving, sailing, and rugby also present substantial risks depending on the year. This variability highlights the need to account for sport-specific participation levels when interpreting injury data. For example, diving and sailing—sports with relatively fewer participants—show notably high injury rates, emphasizing their inherent risk despite lower absolute injury counts. This analysis underscores the necessity of tailoring medical preparedness and intervention strategies to the unique risk profiles of each sport. By accounting for injury rates rather than raw injury counts, it becomes possible to prioritize resource allocation and develop targeted prevention programs for high-risk sports. Additionally, the findings support the importance of continuous monitoring and adaptation of injury prevention measures to reflect evolving participation trends and injury patterns.
The study’s findings, presented in the various figures, reveal notable patterns in the ORs concerning the static and dynamic attributes of sports. As depicted in Fig. 2, athletes participating in a sport with moderate static demands are significantly more likely to seek medical aid than those participating in a sport with low static demands, with this trend persisting when analyzed across a 10-game framework. Additionally, athletes participating in a sport with moderate static demands were found to be more likely to require hospital transport. Figure 2 highlights that athletes participating in a sport with high static demands were consistently more likely to seek medical assistance compared with those participating in a sport with low static demands. This trend underscores the physical strain associated with prolonged muscle contractions and load-bearing activities, which are prone to causing musculoskeletal injuries. Preventive strategies should include tailored strength and conditioning programs, as well as enhanced on-site medical readiness to address these specific risks. Figure 2, which compares help seeking for sports with moderate versus low dynamic demands, reveals slightly higher medical aid and hospitalization rates for athletes participating in moderate dynamic demand sports. This may be due to the repetitive, high-frequency movements inherent in such sports, emphasizing the need for improved warm-up protocols, dynamic stretching, and athlete education to mitigate risks. Regular monitoring for signs of overuse injuries is also recommended. Conversely, Fig. 2 indicates that athletes participating in high dynamic demand sports were only slightly more likely to seek medical help than those participating in low dynamic demand sports. However, overall, the likelihood of medical consultation and hospital transfer was comparable in the high and low dynamic demand groups. This suggests that effective injury prevention measures may already be in place for these sports; however, continued focus on hydration management, recovery protocols, and fatigue monitoring remains essential to further reduce injury risks.
Limitations
This study has several limitations. First, as a retrospective analysis, it is subject to potential selection bias. Second, not all athletes who required medical assistance sought treatment, and some declined therapies and associated documentation. This study relies on reported data collected at the medical stations during the National Games, which may not fully capture all instances of injuries or medical issues, particularly if athletes chose not to seek assistance or declined treatment. Third, the medical records were not comprehensive. Given the retrospective design, the initial checkbox-style records may not have comprehensively captured all relevant information. Moreover, the variability in medical staff across different games resulted in inconsistent documentation quality. Fourth, while the original data included information on event location and time, environmental factors such as temperature and humidity were not analyzed in this study. Although past research highlights the influence of environmental conditions on athlete injuries (e.g., exertional heat illness)20, our dataset recorded only three cases with suspected heat-related issues, and none of the transported patients were diagnosed with heat injuries. Without baseline data such as body temperature, linking environmental factors to potential heat-related injuries would be limited. This omission should be addressed in future studies. Fifth, the scope of our database is restricted to medical records from only three tournaments, which limits our ability to discern long-term trends. Finally, conducting a prospective study would enable the inclusion of environmental data and provide a more comprehensive collection of medical records for future analyses.
Conclusion
This study—which examined the medical support sought by athletes during the National Games in Taiwan in 2017, 2019, and 2021—provides valuable insights for enhancing medical preparedness at mass-gathering sporting events. The number of competing athletes consistently increased over the investigated years, and male athletes slightly outnumbered their female counterparts. Athletes participating in a sport with high static and dynamic demands were more likely to seek medical support, underscoring the importance of targeted medical preparedness for these high-risk activities. Injury was the predominant reason for medical support, followed by illness, with few cases due to environmental or mental health factors. The hospitalization rate fluctuated, with a notable increase in 2021, which may be attributable to improved documentation and reporting practices. Sports with consistently high injury rates, such as handball and martial arts, underscored the need for sport-specific injury prevention and medical preparation. Additionally, the inclusion of sports like diving, rugby, and sailing in the list of top injury-prone events highlights the necessity of adopting medical strategies year-to-year, accounting for variations in injury trends and participation. To better address these challenges, tailored resource allocation, including the strategic placement of medical personnel and specialized equipment near high-risk venues, should be prioritized. Furthermore, pre-event planning should incorporate athlete education programs, sport-specific conditioning routines, and hydration strategies to reduce injury risks. In addition, a transition to digitalized medical record systems that include real-time data entry and environmental metrics such as temperature, humidity, and UV index is recommended. These systems could provide critical insights for injury prevention and aid in developing evidence-based medical interventions. Collaborations among sports medicine experts, event organizers, and local healthcare providers are essential to create a robust medical support framework that is adaptable to the specific demands of mass-gathering sporting events.However, the study’s retrospective nature and the limited scope of data from three tournaments present some limitations. Future research should include a broader time frame and employ a prospective design to facilitate comprehensive data collection. Overall, the study highlights the necessity of tailored medical strategies to enhance safety and response in future mass-gathering sporting events.
Author contributions
PH Ho: Conceptualization, Data Curation, Writing-Original draft preparation. JC Ou: Methodology, Software, Formal analysis and Writing-Original draft preparation. HP Ma and CS Wong: Supervision, Writing-Review & Editing. HC Lin and CH Hsu: Conceptualization, Resources, Project administration and Writing-Review & Editing.
Data availability
The data are available from the corresponding authors upon reasonable request.
Declarations
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Hua-Chen Lin and Chia-Hung Hsu contributed equally to this work.
Contributor Information
Hua-Chen Lin, Email: jacklin1315@gmail.com.
Chia-Hung Hsu, Email: 12119@s.tmu.edu.tw.
References
- 1.Organization, W. H. Public health for mass gatherings: key considerations. (2015).
- 2.Arbon, P. Mass-gathering medicine: a review of the evidence and future directions for research. Prehosp Disaster Med.22 (2), 131–135 (2007). [DOI] [PubMed] [Google Scholar]
- 3.Memish, Z. A. et al. Mass gatherings medicine: public health issues arising from mass gathering religious and sporting events. Lancet393 (10185), 2073–2084 (2019). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Grange, J. T., Baumann, G. W. & Vaezazizi, R. On-site physicians reduce ambulance transports at mass gatherings. Prehosp Emerg. Care. 7 (3), 322–326 (2003). [DOI] [PubMed] [Google Scholar]
- 5.Feldman, M. J. et al. Half-a-million strong: the emergency medical services response to a single-day, mass-gathering event. Prehosp Disaster Med.19 (4), 287–296 (2004). [DOI] [PubMed] [Google Scholar]
- 6.Nguyen, R. B., Milsten, A. M. & Cushman, J. T. Injury patterns and levels of care at a marathon. Prehosp Disaster Med.23 (6), 519–525 (2008). [DOI] [PubMed] [Google Scholar]
- 7.Grant, W. D., Nacca, N. E., Prince, L. A. & Scott, J. M. Mass-gathering medical care: retrospective analysis of patient presentations over five years at a multi-day mass gathering. Prehosp Disaster Med.25 (2), 183–187 (2010). [DOI] [PubMed] [Google Scholar]
- 8.Goldberg, S. A. et al. The Gillette stadium experience: A retrospective review of mass gathering events from 2010 to 2015. Disaster Med. Public. Health Prep. 12 (6), 752–758 (2018). [DOI] [PubMed] [Google Scholar]
- 9.Jena, A. B., Mann, N. C., Wedlund, L. N. & Olenski, A. Delays in emergency care and mortality during major U.S. Marathons. N Engl. J. Med.376 (15), 1441–1450 (2017). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Levine, B. D. et al. Eligibility and disqualification recommendations for competitive athletes with cardiovascular abnormalities: task force 1: classification of sports: dynamic, static, and impact: A scientific statement from the American heart association and American college of cardiology. Circulation132 (22), e262–e266 (2015). [DOI] [PubMed] [Google Scholar]
- 11.Locoh-Donou, S. et al. Mass gathering medicine: event factors predicting patient presentation rates. Intern. Emerg. Med.11 (5), 745–752 (2016). [DOI] [PubMed] [Google Scholar]
- 12.DeMott, J. M., Hebert, C. L., Novak, M., Mahmood, S. & Peksa, G. D. Characteristics and resource utilization of patients presenting to the ED from mass gathering events. Am. J. Emerg. Med.36 (6), 983–987 (2018). [DOI] [PubMed] [Google Scholar]
- 13.Ranse, J. et al. Impacts on in-event, ambulance and emergency department services from patients presenting from a mass gathering event: A retrospective analysis. Emerg. Med. Australas. 31 (3), 423–428 (2019). [DOI] [PubMed] [Google Scholar]
- 14.Langevoort, G., Myklebust, G., Dvorak, J. & Junge, A. Handball injuries during major international tournaments. Scand. J. Med. Sci. Sports. 17 (4), 400–407 (2007). [DOI] [PubMed] [Google Scholar]
- 15.Møller, M. et al. Handball load and shoulder injury rate: a 31-week cohort study of 679 elite youth handball players. Br. J. Sports Med.51 (4), 231–237 (2017). [DOI] [PubMed] [Google Scholar]
- 16.Raya-González, J., García-Esteban, S., Castillo, D. & de Ste Croix, M. Injury profile in professional handball players during 4 consecutive seasons according to playing positions: A longitudinal study. Sports Health. 14 (2), 273–282 (2022). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Naderi, A., Shaabani, F., Keikha, M. & Degens, H. Is an Exercise-Based Injury-Prevention program effective in team handball players?? A systematic review and Meta-Analysis. J. Athl Train.59 (8), 845–856 (2024). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Yiemsiri, P. & Wanawan, A. Prevalence of injuries in Wushu competition during the 1st Asian martial arts games 2009. J. Med. Assoc. Thai. 97 (Suppl 2), S9–13 (2014). [PubMed] [Google Scholar]
- 19.Su, A. W., Johns, W. L. & Bansal, S. Martial arts: orthopaedic injuries and related biomechanics. J. Am. Acad. Orthop. Surg.32 (1), e1–e12 (2024). [DOI] [PubMed] [Google Scholar]
- 20.American College of Sports Medicine et al. American college of sports medicine position stand. Exertional heat illness during training and competition. Med. Sci. Sports Exerc.39 (3), 556–572. 10.1249/MSS.0b013e31802fa199 (2007). PMID: 17473783. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data are available from the corresponding authors upon reasonable request.