Road Traffic Injuries among Children and Juveniles: Trends, Epidemiological Characteristics, and Factors Associated with Severe Injuries in Mueang Kanchanaburi District, Kanchanaburi Province
DOI:
https://doi.org/10.14456/dcj.2026.11Keywords:
road traffic accident, severe injury, children and juveniles, associated factorsAbstract
This research aimed to describe the situation of road traffic injuries among children and juveniles in Mueang Kanchanaburi District, Kanchanaburi Province, during the years 2022-2024. A retrospective study was conducted, including all 2,066 eligible patients under 18 years of age. Secondary data were retrieved from the Injury Surveillance system of Phahol-polpayuhasena Hospital. Data were analyzed using descriptive statistics, time series analysis, and multiple logistic regression analysis. Key findings showed that the number of injured and deceased patients increased from 579 cases in 2022 to 761 cases in 2024, representing an increase of 31.4% (p=0.003). Most cases were male (58.5%), aged 15-17 years (52.7%), were the driver (56.4%), used a motorcycle (90.1%), and did not wear a helmet (91.1%). Motorcycles were the most common counterparty (33.2%). Accidents primarily occurred on highways (89.8%) and during the daytime (61.7%). Factors associated with severe injury included the counterparty being a pickup truck (aOR=2.91, 95% CI: 1.89-4.50), truck/trailer (aOR=7.39, 95%CI: 2.63-20.76), occurring in other sub-districts (aOR=2.54, 95% CI: 1.85-3.50), on weekends (aOR=1.35, 95% CI: 1.06-1.74), festival holidays (aOR=2.29, 95% CI: 1.20-4.36), and nighttime (aOR=1.55, 95% CI: 1.23-1.97). In conclusion, the trend of road traffic injuries among children and juveniles has continuously increased. The high-risk group consisted of male juveniles driving motorcycles without wearing a helmet. Counterparty vehicle type, occurring incident sub-district, type of day, and time of day are statistically significant factors associated with severe injury. Therefore, relevant agencies must design measures specific to the age group, vehicle type, sub-districts distant from the hospital, and high-risk time periods to reduce losses.
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