Exploring the Causal Impact of Age and Nighttime Driving on Road Traffic Injuries among Elderly Drivers: A Bayesian LASSO Approach.

Objective: To determine the causal relationship between aging and nighttime driving and the odds of injury among elderly drivers.

Methods: In this cross-sectional study, 5460 car accidents were investigated from 2015 to 2016. The data were extracted from the Iranian Integrated Road Traffic Injury Registry System. Pedestrian accidents, motorcycle crashes, and fatalities were excluded from the study. To account for major confounders, Bayesian-LASSO, and treatment-effect cutting-edge approaches were used.

Results: Overall, 801 injuries (14.67%) were evaluated. The results of the univariable analysis indicated that aging and nighttime had adverse effects on the odds of road traffic injuries (RTIs), even after adjusting for the effect of other variables, these effects remained statistically significant. According to a newly developed approach, the overall effects of aging and nighttime were significantly and directly correlated with the odds of being injured for older adults (both p<0.001). Our findings indicated that drivers over 75 years old experienced 23% higher injury odds (OR=1.23, 95% CI:1.11 to 1.39; p<0.001), while driving at night increased the odds by 1.78 times (OR=1.78, 95% CI:1.51 to 1.83; p<0.001).

Conclusion: Aging and nighttime driving are significant risk factors for RTIs among elderly drivers. This highlights the importance of implementing targeted interventions to enhance road safety for this vulnerable population. Furthermore, the use of advanced Bayesian-LASSO and treatment-effect statistical methods highlights the importance of utilizing sophisticated methodologies in epidemiological research to effectively capture and adjust for potential confounding factors.