Abstract
BACKGROUND:
Risk factors for motorcycle injuries are associated with rider-related factors and crash-related factors.
OBJECTIVE:
This study investigates the effects of age and violations on occupational accidents among motorcyclists performing food delivery.
METHODS:
This study analyzed 1,317 injured couriers regarding rider-related factors and crash-related factors according to rider’s age or violations.
RESULTS:
Among injured riders, 67.4% were temporary workers, 76.1% worked in small companies with <5 employees, 58.7% in the nighttime, and 51.5% had a work experience of <1 month. However, among the injured teens, 93.5% were temporary workers, 87.0% in companies with <5 employees, 79.5% in nighttime, and 61.4% with work experience of <1 month. The proportion of novice with <1 month, of the temporary worker, of ‘head/face/neck’ injury, or of the ‘concussion/hemorrhage’ type of injury all decreased with age. However, the proportion of ‘fracture,’ ‘rider alone,’ or ‘death or disability’ accidents increased with age. Furthermore, the violation rate was high in teens (17.4%), at night (15.4%), or in type of ‘crash with a car’ (26.2%). The violation rate decreased with age.
CONCLUSIONS:
The results are expected to be useful for injury prevention policies and guidelines in the food delivery industries.
Introduction
Because of the convenience in the congested traffic and the ease of parking in narrow streets, the use of motorcycles in commercial transportation has been rising in Asian Countries [1]. However, motorcyclists are especially vulnerable to injuries because of its small vehicular structures that offer poor protection, coupled with the high speeds they can acquire, and their difficulty to be seen in traffic [2–5]. Motorcyclists accounted for 12% of all traffic-related fatalities in the Americas [2], and motorcycle crashes accounted for more than 50% of the total number of traffic deaths in some Asian countries [1].
Motorcycle crashes are related to the age, lack of protection, riding speed [2–6], helmet wearing [4, 7], alcohol and other drug use [4, 8], licensure and ownership, inexperience, driver training [4, 9–10], risk-taking behaviors [11–13], and driving conditions or nature of the roads [1, 4].
Food delivery workers in the Korean Standard Classification of Occupations [14] refer to persons who deliver restaurant foods to the home. Some restaurants have offered home delivery services for many years. This traditionally involved receiving orders by telephone and then dispatching these orders by staff on motorcycles. Some pizza and chicken restaurants have based the majority of their business around in-house home delivery service provided by food delivery staff using motorcycles [1, 15]. In recent years, delivery specialists have taken the role of intermediaries between the restaurant and customer in the provision of home-delivered foods. They provide websites and mobile phone apps for ordering foods [15].
The motorcycle rider performing food delivery is a poorly paid job in South Korea. The motorcyclists usually work as temporary workers, and the majority of them work in small-sized firms with less than five employees [15]. A person aged 16 or older can acquire a motorcycle driver’s license under 125cc in South Korea. Because of low barriers to entry even for teenagers, the proportion of teenage workers is high. The motorcyclists performing food delivery must work in a wide range of temperature and humidity depending on the season. Although food delivery services often commence at lunchtime and continue throughout the day, the most significant period of food delivery activity takes place during the evening [15]. Weekend delivery is usually higher in demand than that on weekdays.
Development of preventive measures require a systematic analysis of occupational accidents. Risk factors for motorcycle crashes are associated with rider-related factors and crash-related factors. The analysis of human factors in traffic crashes usually reference the theory by Reason et al. [16], who analyzed the human errors of traffic crashes regarding mistakes, slips, lapses, and violations [17, 18]. Risk-taking behaviors among motorcycle riders may include speeding, alcohol and other drug use, not using a helmet while riding, unlicensed riding, running red lights, and driving the wrong lane [4, 16–18]. Delivery motorcyclists traditionally work under time pressure, and in poor and unsafe working conditions leading to a significant increase in rider’s violations or risk-taking behaviors [2]. However, there are only a few studies on the aspects of occupational motorcycle crashes caused by rider’s violations [2, 12]. This study used the occupational compensation records to investigate the characteristics of occupational crashes caused by motorcycle riders. The workers’ compensation records for work-related traffic crashes are based on police reports and drivers’ interview [15, 16, 19–21]. Thus, this study aims to investigate the characteristics of occupational crashes and work-related injuries of motorcyclists performing the food delivery. This study also examines the characteristics of motorcycle crashes caused by rider’s intentional violations.
Methods
Research variables
Table 1 presents the research variables used in this study, divided into rider-related factors and crash-related factors. Rider-related factors include age, work experience, type of employment, and company size. The age of injured riders was classified as teens, 20 s, or 30 years or older. Regular workers work under a contract of more than one year, and temporary workers work under a contract of less than one year. The company size refers to the total number of employees hired by the company.
Definition of research variables and description
Definition of research variables and description
The crash-related factors include rider’s violations, time of crash, crash type, injury type, injured body part, and severity of the injury. This study analyzed the characteristics of motorcycle crashes based on rider’s compensation data. In South Korea, employers are required to report an accident to the relevant enforcing authority for compensation purposes [15–16, 19–22]. The compensation data received from the Korea Occupational Safety and Health Agency (KOSHA) does not include the information regarding velocity at the time of crash. Since this study targeted crashes registered as industrial accidents, any traffic crashes due to drinking alcohol or taking drugs were not included. Thus, in this study, the violations are limited to the signal or lane violations, excluding speeding violation. These include violations such as running a red light/sign, crossing over a center lane, or taking an improper U-turn or turning at an intersection.
The injury severity was classified as death or disability, and minor injuries. Disabilities, approved by Industrial Accident Compensation, refer to any permanent incapacity of body part left by the crash. The crash type was classified as ‘rider alone,’ ‘crash with vehicle,’ ‘crash with pedestrian,’ and ‘crash with motorcycle.’ There were several different accidents in which the types were mixed. Thus, these are not mutually exclusive.
From the national compensation injury data approved in 2015, which resulted in at least 4 days of absence from work, 1,317 injuries were classified as motorcycle riders performing food delivery.
This study analyzed the characteristics of motorcycle crashes caused by the food delivery workers according to age group or rider violations, respectively. The Chi-square test was used to analyze whether there is a significant difference in the distribution of the injured riders, according to age groups or intentional violations, regarding work experience, employment type, company size, time of crash, crash type, injury type, injured body part, and severity of injury. The statistical package SPSS 18.0 was used for the analysis, and the significance level was 0.05.
Results
Characteristics of injured riders
Distributions of injured riders by age and violation
Table 2 shows the age distribution of the injured riders according to violations. The injured riders with their 30s and older (46.8%) were the most common, 31.0% of injuries occurred with riders in their 20s, and 22.2% of injuries occurred in riders in their teens. As shown in the table, 87.1% of injured riders had crashes without rider violations, and 12.9% of injured riders had crashes with violations.
Distributions of injured riders by age and violation
Distributions of injured riders by age and violation
The distribution of injured riders by age group was statistically different in regard to the violations (χ2 = 14.493, p = 0.001). In the case of teens, 17.4% of motorcycle crashes occurred with intentional violations, 15.2% in their 20s, and 9.3% in their 30s or older. That is, the violation rate decreased with age.
Table 3 shows the distribution of injuries by work experience according to age and violations. As shown in the table, 51.5% of injured riders had work experience of <1 month and 75.4% of injured riders had <3 months of work experience.
Distributions of injured riders by work experience
Distributions of injured riders by work experience
There was a significant difference in the age distribution of the injured riders according to work experience (χ2 = 41.512, p < 0.001). The percentage of injuries with <1 month of work experience was relatively higher in their teens (61.4%) than in their 20s (52.0%) or their ≥30 years of age (46.4%). However, the percentage of injuries with ≥6 months of work experience was relatively higher in their ≥30 years (17.7%) than that in their 20s (11.0%) or their teens (4.4%). That is, the ratio of injured riders with <1 month of work experience decreased with age, while the ratio of injured riders with ≥6 months of work experience increased with age.
There was no significant difference in the distribution of injured rider work experience associated with violations (χ2 = 1.676, p = 0.795).
Table 4 shows the distribution of injured riders by employment type according to age or violations. As shown in the table, 67.4% of injured riders held part-time or temporary occupations.
Distributions of injured riders by employment type
Distributions of injured riders by employment type
The age distribution of injured riders shows a significant difference according to employment type (χ2 = 139.708, p < 0.001). The percentage of the temporary worker was relatively higher in their teens (93.5%) than that in their 20s (68.0%) or their ≥30 years (54.2%). That is, the ratio of working in temporary jobs decreased with age.
The violation rate caused by temporary workers (14.0%) was higher than that by regular workers (10.7%). However, there was no statistically significant difference in the distribution of injuries regarding the violations and type of employment (χ2 = 2.775, p = 0. 096).
Table 5 shows the distribution of injured riders by company size according to age or violations. As shown in the table, 76.1% of injured riders worked in a small restaurant with fewer than five employees. Moreover, 90.7% of them worked in a restaurant with less than 15 employees.
Distributions of injured riders by company size
Distributions of injured riders by company size
The age distribution of injured riders was statistically different according to company size (χ2 = 63.715, p < 0.001). Most of the injured riders worked in a small restaurant with fewer than five employees, whom were teenagers (87.0%) or in their 30s or older (78.6%). The proportion of the injured riders working in a restaurant with ≥15 employees was relatively higher for workers in their 20s (17.2%) than in other ages (3.8% –6.7%).
The violation rate was 13.8% in firms with less than five employees, 10.9% with 5–15, 9.0% with more than 15 employees. However, the distribution of injured riders between company size and the violation displayed no significant difference (χ2 = 3.015, p = 0.212).
Analysis by time of crash
Table 6 shows the distribution of injured riders by time of the crash according to age or violations. Among injured riders, 773 riders (58.7%) suffered the injury at night (from 18 : 00 to 6 : 00), and 544 riders (41.3%) in the daytime (from 6 : 00 to 18 : 00).
Distributions of injured riders by time of crash
Distributions of injured riders by time of crash
The age distribution of injuries was statistically different according to the time of crash (χ2 = 92.786, p < 0.001). In their teens (79.5%) or their 20s (62.3%), the ratio of the crash in the nighttime was much higher than that of the daytime. While, in their 30s or older, the ratio of the crash in the daytime (53.6%) was higher than that of the nighttime. The lower the age group, the higher the composition ratio of accidents in the night.
The distribution of crashes due to violations according to crash time was statistically different (χ2 = 10.292, p = 0.001). The violation rate was higher at night (15.4%) than that of the daytime (9.4%).
Table 7 shows the distribution of injured riders by crash type according to age or violations. In Table 7, the types of crashes are not mutually exclusive. The composition ratio of injured riders according to the type of crash; 55.2% of crashes were ‘rider overturned alone (rider alone),’ 39.7% by ‘crash with car,’ 5.0% by ‘crash with motorcycle,’ and 3.6% by ‘crash with pedestrian.’
Distributions of injured riders by crash type
Distributions of injured riders by crash type
*1 = if rider overturned alone, 0 = otherwise.
The distribution of injured riders was statistically different between age and ‘rider alone’ (χ2 = 50.252, p < 0.001), ‘crash with car’ type (χ2 = 19.704, p < 0.001), or ‘crash with pedestrian’ (χ2 = 16.231, p < 0.001). The percentage of ‘rider alone’ was relatively lower among teens (48.8%) than that in their 20s (52.0%) or their ≥30 years (60.4%). In other words, the proportion of ‘rider alone’ accidents increased with age. However, the proportion of ‘crash with car’ or ‘crash with pedestrian’ types decreased with age. Whereas, the distribution of injured riders was not statistically different according to age and ‘crash with motorcycle’ accidents (χ2 = 5.638, p = 0.060).
The violation rate was highest in the ‘crash with car’ (26.2%) type. The distribution of injured riders was statistically different between the violation and ‘rider alone’ (χ2 = 148.925, p < 0.001) or ‘crash with car’ (χ2 = 136.230, p < 0.001) accidents. The violation rate was lower in ‘rider alone’ crashes (2.8%) than the other types (25.4%). Meanwhile, the violation rate was higher in ‘crash with car’ (26.2%) than the other types (4.2%). The distribution of injured riders was not statistically different amongst violation and ‘crash with motorcycle’ (χ2 = 2.849, p = 0.091) or ‘crash with pedestrian’ classifications (χ2 = 0.223, p = 0.636).
Table 8 shows the distribution of injured riders by injury type according to age or violations. The most common type of injury was ‘fracture’ (54.0%), followed by ‘sprain’ (15.7%), ‘laceration/bruise/abrasion’ (14.4%), ‘concussion/hemorrhage’ (7.9%), and ‘rupture’ (6.8%).
Distributions of injured riders by injury type
Distributions of injured riders by injury type
There was a significant difference in the distribution of injured riders between age and injury type (χ2 = 50.252, p < 0.001). In the case of teenagers, ‘fracture’ (44.4%) was the most common type of injury, followed by ‘laceration/bruise/abrasion’ (20.5%), ‘sprain’ (14.3), and ‘concussion/hemorrhage’ (13.3%). On the other hand, the most common type of injury in their 30s or older was ‘fracture’ (60.2%), followed by ‘sprain’ (17.4%), ‘laceration/bruise/abrasion’ (9.3%), and ‘rupture’ (6.2%). That is, the leading type of injury in all age groups was a fracture. However, as the age of rider increases, the proportion of injury involving ‘fracture’ increases. On the other hand, as the age of rider increases, the ratio of the injury in the form of ‘laceration/bruise/abrasion’ or ‘concussion/hemorrhage’ decreases, respectively.
The violation rate was high in ‘mixed’ (23.5%), ‘concussion/hemorrhage’ (17.3%), and ‘fracture (14.2%) injuries. However, the distribution of crashes due to violations according to injury type was not statistically different (χ2 = 9.420, p = 0.093).
Table 9 shows the distribution of injured riders by injured body part according to age or violations. The body sites most vulnerable to injury are ‘leg/feet’ (42.9%), followed by ‘shoulder/arm/hand’ (25.4%), ‘head/face/neck’ (19.4%), and ‘trunk/back’ (10.5%).
Distributions of injured riders by injured body part
Distributions of injured riders by injured body part
There was a significant difference in age distribution of injured riders by injured body part (χ2 = 78.195, p < 0.001). In the case of teens, the body sites most vulnerable to injury are ‘leg/feet’ (38.2%), followed by ‘head/face/neck’ (32.1%), and ‘shoulder/arm/hand’ (20.1%). Meanwhile, the body sites most vulnerable to injuries in their 20s were ‘leg/feet’ (48.5%), followed by ‘shoulder/arm/hand’ (25.7%), and ‘head/face/neck’ (17.2%). On the other hand, the body sites most vulnerable to injuries in their 30s or older were ‘leg/feet’ (41.4%), followed by ‘shoulder/arm/hand’ (27.8%), ‘trunk/back’ (15.4%), and ‘head/face/neck’ (14.8%). The most common injured body sites in all age groups were ‘lower limbs (leg/feet)’. Injuries of the ‘head/face/neck’ are higher in the teenage group than other age groups. As the age of rider increases, the proportion of the rider injured on the ‘head/face/neck’ decreases.
The violation rate was high in ‘head/face/neck’ injury (14.9%). However, the distribution of injured riders was not statistically different according to injured body part and violation (χ2 = 1.410, p = 0.842).
Table 10 shows the distribution of injury severity of riders according to age or violations. Overall, 1,132 injuries (86.0%) were minorly injured, 185 (14.0%) resulted in disability or deaths.
Distributions of injured riders by severity of injury
Distributions of injured riders by severity of injury
The distribution of injured riders by age group was statistically different according to injury severity (χ2 = 10.177, p = 0.006). In teens, the proportion of ‘death or disability’ accounted for 8.9%, 13.7% in their 20s, and 16.7% in their 30s or older. The proportion of ‘death or disability’ increased with age.
The violation rate was higher in ‘death/disabilities’ (16.2%) than those with minor injuries (12.4%). However, the distribution of injured riders by injury severity was not statistically different according to the rider violations (χ2 = 2.095, p = 0.148).
This study analyzed the characteristics of occupational crashes of motorcyclists performing motorcycle food delivery according to age or rider violations.
This study showed that 67.4% of injured riders were temporary workers, and 75.4% of injured riders had <3 months of work experience. The problems of frequent labor turnover and part-time or temporary employment are common in motorcycle riders performing food delivery [15]. It is difficult for new riders to recognize the hazards. As a part-time job or temporary job, new riders sometimes work without proper education or training on motorcycle safety [12, 19]. It is important to ensure that motorcyclists who work outdoors have access to safety information as well as training during regular working hours. Therefore, general safety training, as well as training on the use of a motorcycle, is essential to improve the novice rider’s health and safety.
In this study, 76.1% of injured riders worked in small companies with <5 employees. The delivery riders, working in small restaurants, may be more likely to be using a motorcycle that is old, poorly maintained, and lacking a protective structure [15]. Thus, they work in workplaces where the necessary protective devices are relatively insufficient.
This study found that the proportion of ‘fracture,’ ‘rider alone,’ or ‘death or disability’ accidents increased with age. Motorcycle riders work under time pressure, and require high speeds on congested or narrow streets. Older workers have a relatively poor sense of balance, perceptive ability and lack of judgment in the dark [23–24]. Increases in the number of deaths among the elderly may reflect their greater likelihood of serious complications and poorer prognosis after injury [25]. Also, because traffic crashes of older riders can cause serious injuries, it is necessary to develop means to motivate and train older workers.
Because of low barriers to entry even for teenagers, the proportion of teenage workers in delivery service is high in South Korea [15]. However, this study showed that 93.5% of teenage injured riders were temporary workers, 87.0% in companies with <5 employees, and 79.5% during the nighttime. That is, teenage injured riders worked under more severe working conditions. Younger workers are more likely to commit violations because of inattention, impulsiveness, overestimation of capacity and pride, recklessness, and lack of family responsibilities [23, 26]. Accordingly, the violation rate was highest in teens (17.4%) and decreased with age in this study. Also, the injuries on the ‘head/face/neck’ were common in the teenage group, and the proportion of the ‘head/face/neck’ injuries decreased with age. Furthermore, the proportion of ‘concussion/hemorrhage’ decreased with age. Thus, it is necessary to introduce appropriate support policies tailored to teen riders.
The results of this study also showed that the most common injured body part was the lower limbs (leg/feet), and the leading type of injury in all age groups was a fracture. Corresponding reports have also documented that the lower extremity was the most common site of an injury in all motorcycle crashes [27], and fractures were most frequent [28]. Protective clothes seem to reduce the risk of soft tissue injuries among motorcyclists. Heavy boots and work shoes are effective in protecting against ankle and foot injuries [4], and crash bars on motorcycles protect riders’ lower legs when impacted from the side [29]. Compared with helmeted riders, non-helmeted riders are at higher risk for severe head injuries of all types, as well as facial injuries and high-severity facial fractures [4]. Comprehensive helmet laws are significantly associated with an increase in helmet usage followed by declines in the total number of motorcycle deaths, head injuries, days of hospitalization [4]. A high proportion of motorcyclists incorrectly use motorcycle safety devices possibly due to inadequate education and lack of law enforcement; for example, about one-third of motorcyclists had their helmets fastened improperly or were wearing non-standard helmets [30]. It is necessary to have an adequate helmet law, and requirements for helmets to meet specific safety standards.
Finally, the results of this study align with the Haddon’s matrix for risk factors for motorcycle crash injuries [4]. Some risk factors such as age and nighttime cannot be directly modified to prevent motorcycle crash injuries. Their effects can be accounted for the riding hours as well as modifiable factors such as helmet wearing, inexperience and driver training, conspicuity of the motorcyclist, driving licensure, riding speed, and risk-taking behaviors. These modifiable factors have more relevance in developing and designing prevention programs [4]. In South Korea, there is no limit on consecutive driving hours per day and break time for the motorcycle riders performing food delivery [15, 20–21]. Thus, legislative frameworks will likely need to address issues going beyond protective gear use [15], driving hour limits [20–21] and motorcycle driver’s licensing procedures [4, 15] to include motorcycle industry responsibilities and occupational safety provisions for workers.
This study has some limitations: (1) minor accidents are not included in the analysis because we used compensation records, which is documented for > 4 days of absence from work; (2) the accident rates reported in this study show a lower frequency rate than those reported in traffic accident analysis; and (3) violation rates may be underestimated due to data set. Despite these limitations, the results of the present study illustrated the actual safety problems experienced in the food delivery industry of South Korea. The results of this study are expected to be useful for injury prevention policies and guidelines in the food delivery industries.
Conflict of interest
None to report.
Footnotes
Acknowledgments
This research was financially supported by Hansung University.
