Alcohol-related fatal-and-injury traffic crashes in Türkiye (2015–2024): temporal trends and an ecological evaluation of alcohol control policies

Alcohol-impaired driving is a well-established and preventable cause of road traffic deaths and injuries. This study examined national time trends in the relative burden of alcohol-related fatal-and-injury road traffic crashes in Türkiye between 2015 and 2024 and interpreted the findings within an ecological policy and enforcement context. We conducted a national ecological time-trend analysis using annual aggregate road traffic crash statistics from the Turkish Statistical Institute for 2015–2024. The outcome was the annual count of alcohol-related crashes resulting in death or injury. To estimate changes in the relative burden over time, the natural logarithm of the annual total number of fatal-and-injury crashes was included as an offset. Temporal trends were first assessed using Poisson regression; after overdispersion was identified, estimates were re-evaluated using negative binomial regression. Results are reported as incidence rate ratios (IRR) with 95% confidence intervals (CI). The proportion of alcohol-related fatal-and-injury crashes among all fatal-and-injury crashes declined from 2.13% in 2015 to 0.72% in 2024. In the Poisson model, calendar year was negatively associated with the relative burden (IRR 0.883; 95% CI 0.880–0.887; p < 0.001), although model fit indicated overdispersion. In the negative binomial model, the direction of the association remained negative but was not statistically significant (IRR 0.883; 95% CI 0.709–1.097; p = 0.260). Sensitivity analyses excluding 2020 alone and excluding both 2019 and 2020 yielded nearly identical estimates, indicating that the negative but non-significant trend was not materially driven by potentially atypical pandemic-period observations. Descriptive data showed a marked decline in the relative burden of alcohol-related fatal-and-injury road traffic crashes in Türkiye from 2015 to 2024. However, negative binomial regression did not confirm a statistically significant temporal trend, indicating that model-based evidence should be interpreted cautiously. Interpretation should consider the ecological nature of the data and the possibility of time-varying enforcement intensity, detection, and reporting practices.