Bulletin of emergency and trauma · 2025
Predictive Factors Influencing Helmet Usage Among Motorcyclists: A Study at the Largest Trauma Center in Southern Iran.
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Yadollahi Mahnaz, Farbodan Farshid, Zamani Maryam, Bolandparvaz Shahram
Аннотация
OBJECTIVES: This study aimed to identify factors influencing helmet usage behavior among motorcyclists.
METHODS: A cross-sectional study of injured motorcyclists was conducted at Shahid Rajaee Hospital (Shiraz, Iran), using the convenience sampling method. Data were collected via a structured medical form, and logistic regression with the "Backward" technique was applied to identify risk factors associated with helmet use.
RESULTS: Among 147 patients, 139 (94.55%) were un-helmeted, and 8 (5.45%) were helmeted. The mean age of helmeted riders was 41.46±17.44 years, compared to 29.21±12.23 years for un-helmeted riders. After data balancing, key predictors of helmet use included riding before noon (OR=10.164, 95% CI [4.543, 22.738]), crashes in urban areas (OR=21.740, 95% CI [5.535, 85.383]), absence of head/neck injuries (OR=4.549, 95% CI [2.075, 9.970]), absence of facial injuries (OR=5.108, 95% CI [1.587, 8.694]).
CONCLUSION: These findings could assist policymakers in understanding helmet usage behavior and increasing helmet usage rates. They also support evidence-based strategies to reduce traffic crashes. Addressing helmet-related discomfort and enhancing public awareness of helmet benefits could significantly reduce motorcycle-related trauma.
METHODS: A cross-sectional study of injured motorcyclists was conducted at Shahid Rajaee Hospital (Shiraz, Iran), using the convenience sampling method. Data were collected via a structured medical form, and logistic regression with the "Backward" technique was applied to identify risk factors associated with helmet use.
RESULTS: Among 147 patients, 139 (94.55%) were un-helmeted, and 8 (5.45%) were helmeted. The mean age of helmeted riders was 41.46±17.44 years, compared to 29.21±12.23 years for un-helmeted riders. After data balancing, key predictors of helmet use included riding before noon (OR=10.164, 95% CI [4.543, 22.738]), crashes in urban areas (OR=21.740, 95% CI [5.535, 85.383]), absence of head/neck injuries (OR=4.549, 95% CI [2.075, 9.970]), absence of facial injuries (OR=5.108, 95% CI [1.587, 8.694]).
CONCLUSION: These findings could assist policymakers in understanding helmet usage behavior and increasing helmet usage rates. They also support evidence-based strategies to reduce traffic crashes. Addressing helmet-related discomfort and enhancing public awareness of helmet benefits could significantly reduce motorcycle-related trauma.