Chronobiology research has uncovered a host of maladies linked to social jetlag (SJL), the sleep-disrupting disconnect between solar time and social time. This interdisciplinary study applies chronobiology theory to the potential effect of misaligned time zones on motor-vehicle deaths. In the U.S. 53 million residents live in counties located outside their official time zones’ standard 15° span of longitude, based on degrees west of the prime meridian. We refer to these counties as eccentric time localities (ETLs), all of which lie west of their time zones’ standard western border in the U.S. In contrast, counties within 7.5° of their time zone’s standard geographic center are what we call solar zones. Solar zones do not vary more than 30 minutes from true solar time. ETL residents are forced to rise before dawn, possibly restricting their sleep-time and suppressing both morning and evening zeitgebers that would support their circadian entrainment. Hypothesizing that living in ETLs amplifies social jetlag, data on 417,399 traffic fatalities in the U.S. between 2006 and 2017 from the Fatality Analysis Reporting System (FARS) census were analyzed via GIS mapping and population-data statistics. Road fatalities among residents of solar zones were compared to those living in ETLs within the same official time zone. ETL residents across the U.S. indicated 21.8% higher fatality-rates than solar residents, with a mean of 1286 additional (i.e., unexpected) deaths-per-year. Results support circadian entrainment theory and are consistent with the SJL construct. The socio-political ramifications of these findings are discussed, as well as the subject of best practices when analyzing whole-population data. The authors conclude that the unquestioned rhetoric of time-zone boundaries should be reconsidered in social policy.

In a letter to Time & Society, José Maria Martín-Olalla (2023b) offers a critique of my team's study on traffic fatalities in misaligned time zones in the United States (Gentry et al., 2022). Unlike research that is met only with the sound of crickets, it is positively refreshing when other scholars take notice. This essay is reminiscent of his response to Malow (2022) on the subject of Daylight Saving Time (Martín-Olalla 2023a), and other constructive critiques.Our study identified a 21.8% elevated risk of traffic fatalities in eccentric time localities (ETLs) compared to solar zones in the United States. Dr. Martín-Olalla's essay takes issue with what he calls this "staggering large" result (p. 1). His subtitle is "Not that elevated" (p. 1).In framing my reply it helps to consider Martín-Olalla's (2023b) early statement, "In their analysis, the authors implicitly assume that F [fatalities] scales with P [population] through different geographic localities" (p. 1). Far from assuming, we tested a falsifiable hypothesis using data from the Fatality Analysis Reporting System (FARS) annual census. This carefully managed resource, curated by the National Highway Traffic Safety Administration (NHTSA), enumerates each U.S. highway death by county. Whole-population data carry the advantage of no standard error and no need to eliminate data (Alexander, 2015), a concept we explained rather than assumed. Whole-population data are appropriately analyzed via descriptive rather than inferential statistics.In contrast, Dr. Martín-Olalla's (2023b) extensive meta-statistical analyses seem to assume we collected only a sample of the population rather than the whole population. Note his concern about our "scarcity of observations" (p. 3). In fact, we accounted for each road fatality over a 12-year period, not a mere sample (n = 417,399). We cited Alexander (2015) and Wood (2016), who explain why inferential-statistical tests are not only unnecessary for whole-population data, but counterproductive. Wood (2016) notes, "Obviously if you've got the time and energy and resources to study the whole population you should do so because then you get the whole answer and don't need to mess around with p values or