Age-stratified analysis of the severity of injuries in electric tricycle accidents among the elderly, compared with other age groups.

OBJECTIVE

Electric tricycles are widely used for short-distance passenger and freight transport in China, particularly in urban-fringe and rural areas. Their rapid growth has raised safety concerns because these vehicles provide limited occupant protection and frequently operate in mixed-traffic environments. This study examined age-related heterogeneity in injury severity among electric tricycle drivers and identified factors associated with severe/fatal injury outcomes across different age groups.

METHODS

Police-reported electric tricycle crashes from 2020 to 2024 were analyzed. After data screening, 1,425 crashes were retained. Drivers were classified into three age groups: under 45 years, 45-59 years, and 60 years and above. Injury severity was categorized into three levels: property-damage-only, slight injury, and severe/fatal injury. Age-stratified random-parameters logit models were estimated to account for unobserved heterogeneity, and marginal effects were calculated to compare injury-severity patterns across age groups. In addition, a pooled model with age-by-risk-factor interaction terms and COVID-19 period sensitivity analyses were conducted to further examine age-related differences and the temporal robustness of the findings.

RESULTS

The results showed clear age-related heterogeneity in injury-severity determinants among electric tricycle drivers. Drivers aged 60 years and above accounted for the largest share of crashes and showed a more pronounced severe/fatal injury pattern than younger and middle-aged drivers. Among older drivers, helmet nonuse, unlicensed driving, pedestrian or rollover crashes, rear-end collisions, turning maneuvers, and signal-controlled intersections were more strongly associated with severe/fatal injury. By contrast, severe/fatal injury among drivers under 45 years was more closely associated with nighttime conditions and specific time-of-day factors, while injury severity among drivers aged 45-59 years was mainly related to selected maneuver and crash-configuration factors. The pooled interaction model further showed that, compared with younger unlicensed drivers, older unlicensed drivers had higher severe/fatal injury probabilities. Middle-aged and older drivers also showed higher severe/fatal injury probabilities in no-responsibility crashes. COVID-19 period analyses indicated that the main age-related findings were generally stable.

CONCLUSIONS

Older electric tricycle drivers bear a disproportionate burden of fatal and serious injury in police-reported crashes. Prevention strategies should therefore prioritize older adults through improved helmet use, strengthened licensing and safety management, age-friendly roadway and intersection design, and safer operating environments for electric tricycles. At the same time, interventions should also reflect the distinct risk profiles of younger and middle-aged drivers. Age-stratified safety policies may be more effective than one-size-fits-all approaches in reducing injury severity among electric tricycle users.