J Korean Med Sci.  2016 Oct;31(10):1546-1552. 10.3346/jkms.2016.31.10.1546.

Characteristics of Workplace Injuries among Nineteen Thousand Korean Firefighters

• Yoon JH
• Kim YK
• Kim KS
• Ahn YS

• KMID: 2468243
• DOI: http://doi.org/10.3346/jkms.2016.31.10.1546

Abstract

To determine the actual firefighter injury statistics in Korea, we conducted a survey on the nature of on-duty injuries among all male firefighters in Korea. We distributed questionnaires to all Korean male firefighters via email, and data from the 19,119 workers that responded were used for data analysis. The job types were categorized into fire suppression, emergency medical service (EMS) and officers. As estimated of age standardized injury prevalence per one thousand workers, 354 fire extinguishing personnel, 533 EMS workers, and 228 officers experienced one or more injuries during the previous 12 months. The odds ratio (95% confidence interval) of injuries was 1.86 (1.61-2.15) for fire suppression and 2.93 (2.51-3.42) for EMS personnel compared to officers after adjusting for age, marital status, smoking habit and career period. Age standardized absence days from work due to injuries per one thousand workers were 1,120, 1,337, and 676 for fire suppression, EMS and officers, respectively. Car accident (24.5%) was the most common cause and wound (42.3%) was the most common type of injuries. Our nationwide representative study showed that fire suppression and EMS workers are at greater risk of on-duty injuries compared to officers. We observed different injury characteristics compared to those reported in other countries.

Keyword

Injury; Firefighter; Emergency Medical Service; Korea

MeSH Terms

Accidents, Occupational/*statistics & numerical data
Accidents, Traffic/statistics & numerical data
Adult
Asian Continental Ancestry Group
Blast Injuries/epidemiology
Electronic Mail
Emergency Medical Services
*Firefighters
Humans
Male
Middle Aged
Odds Ratio
Prevalence
Republic of Korea/epidemiology
Surveys and Questionnaires
Workplace
Wounds and Injuries/*epidemiology

Figure

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  Fig. 1 Odds ratio of suffering one or more accident during past 12 months according to job categories. Age, marital status, career period, smoking status were controlled by multiple logistic regression model.

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