Imagine driving at night while the sun is still high. This is the effect of daylight saving time, or DST. A study analyzed 10β―million fatal crashes across the contiguous United States. Nationally, fatalities drop about 0.10β―% during DST. However, when examined by zone, the pattern changes. Central and Eastern zones see a 2β―% decline when the clock moves forward. Pacific and Mountain zones experience a slight rise, about 0.3β―%. Why? Timeβzone differences affect driversβ circadian rhythms. In the Pacific, a later clock disrupts sleep, increasing fatigue. In the Mountain zone, an earlier clock can lower vigilance at sunset. Authorities can use these findings to act. For example, in Pacific and Mountain areas, limiting alcohol or drug use during DST is advisable. In the Central zone, monitoring visibility at dawn or dusk is crucial. In the East, safety improves if drivers avoid earlyβhour travel right after the change. In short, daylight saving is not a oneβsizeβfitsβall solution; it varies by location. Targeted policies can make roads safer for everyone.
The study employed a hierarchical multilevel model, combining national data with zonal information to capture geographic variations related to daylight saving time. Analyzing more than ten million fatal crash records from 2000 to 2022, researchers identified an average 0.10β―% decrease nationally during DST, but regional differences were pronounced. In central and eastern zones, the decline was about 2β―%, linked to better circadian alignment with daytime work hours, reducing morning drowsiness. Conversely, in Pacific and Mountain zones risk rose by 0.3β―%, because the time shift occurs when natural light is limited, forcing drivers to operate in lowβvisibility or sleepy conditions. The key mechanism is melatonin modulation: moving to summer time delays nighttime secretion, disrupting sleepβwake cycles and affecting reaction time. Additionally, sun angle varies with latitude, influencing light perception and fatigue. Recommended policies include restricting alcohol and drug use during highβrisk hours, especially in regions with larger time changes, and implementing visibility checks at dawn and dusk in zones with extended transition periods. Integrating meteorological and traffic data with spatiotemporal models enables prediction of incident spikes and optimisation of road safety resources.
