Fatality risks in eccentric time localities: Not that elevated

Abstract

Dear Editors, Recently, Gentry et al. (2022) analyzed the impact of the east–west gradient within a US time zone on the vehicle fatalities from the year 2006 to the year 2017. They distinguished control localities—those inside the physical time zone corresponding to their winter local time, referred as solar, as an example Houston, Texas—and the tested localities—those outside, west of, their physical time zone, referred as Eccentric Time Locality (ETL), as an example Amarillo, Texas. Their results were summarized on their Table 3, where population sizes P, accumulated fatalities F, and the fatality rates R = F/P are listed for the solar and the ETL groups. Gentry et al. (2022) reported worse scores (larger fatalities) in the Eastern, Central, and Mountain ETL: 23.8%, 17.7%, 26.5%, respectively, comparing pairwise a solar location to their corresponding ETL. All else equal, east–west gradient may impact societal issues like traffic accident rates. However, the impact reported by Gentry et al. (2022) is staggering large. I offer an alternative explanation for their findings. In their analysis, the authors implicitly assume that F scales with P through different geographical localities. However, when dealing with heterogenous social magnitudes like F, one should consider F }Pαe, where αe is an empirical exponent, which may or may not be equal to one. I provide an analogy based on mortality. I got weekly numbers of deaths in Spain since the year 2000 disaggregated by NUTS3 regions (N = 52). I tested the logarithm of the accumulated values against the logarithm of the average population in every region. I found αe = 0.921 with 95% confidence interval (CI) [0.864, 0.978] and Person’s