Unpacking temporal trends in U.S. road injury mortality by mode of transportation and sex: An age–period–cohort analysis

Road traffic injuries remain a major health burden in the United States, with vulnerable road users—pedestrians, bicyclists, and motorcyclists—disproportionately affected. Although age is a well-established determinant of road traffic injury risk, most research treats age effects as static, overlooking generational (cohort) differences and historical (period) shifts that shape risk across time. This study applied an Age–Period–Cohort (APC) model to U.S. road mortality data from 1980 to 2021, using Global Burden of Disease estimates disaggregated by age, sex, and mode of transportation. By isolating the contributions of age, cohort, and period effects, findings reveal that conventional cross-sectional methods can misrepresent age-related risk by conflating it with temporal influences, leading to over- or underestimations. For motor vehicle and pedestrian injuries, where risks declined both across historical periods and among more recent cohorts, cross-sectional analyses tend to overestimate risk among older adults and underestimate it among the young. For motorcyclists, age-related risk is often overstated due to unfavorable period effects, while for bicyclists, it is understated due to safety improvements among newer cohorts. Stratifying by sex further reveals disparities in two-wheeled travel: young male motorcyclists face the highest risks, while young female bicyclists experience disproportionate risks often obscured in aggregate data. These results highlight the value of APC modeling in uncovering hidden patterns and providing a more nuanced, temporally sensitive understanding of road risks across demographic and modal lines. Such insights can guide targeted interventions, such as youth-focused motorcycle safety programs, policy measures to protect adolescent female bicyclists, and APC-aware surveillance tools that better anticipate emerging risks.