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Collecting Sleep, Circadian, Fatigue, and Performance Data in Complex Operational Environments
Published on: August 8, 2019
Circadian-informed modeling predicts regional variation in obesity and stroke outcomes under different permanent US
1Department of Bioengineering, Schools of Engineering and Medicine, Stanford University, Stanford, CA 94305.
Abstract:
Seasonal changes in time policy, such as switching between Standard Time (SDT) and Daylight Saving Time (DST), have been adopted by many countries, including the United States. While transitioning between SDT and DST has notable acute negative population health impacts, the chronic impact of these time policies on health has not been well evaluated. To estimate the impact of permanent SDT or DST on health, we modeled the circadian impact of SDT, DST, and Biannual Shifting (BAS) across a year in the contiguous, continental United States. We find that BAS produces a greater burden on the circadian system as compared to either permanent SDT or DST. Chronotype as well as location (latitude and location within time zones) impact this burden. Analyzing these data relative to county-level health data (Centers for Disease Control and Prevention Places dataset), we find that, under idealized light exposure conditions and after controlling for health and socioeconomic factors, there would be a decrease in the prevalence of both obesity [[Formula: see text]0.78% ([Formula: see text]0.06% to [Formula: see text]1.49%)] and stroke [[Formula: see text]0.09% ([Formula: see text]0.04% to [Formula: see text]0.14%)] under SDT compared with the current policy. The prevalence of both obesity [[Formula: see text]0.51% ([Formula: see text]0.09% to [Formula: see text]0.93%)] and stroke [[Formula: see text]0.07% ([Formula: see text]0.04% to [Formula: see text]0.09%)] would also decrease under permanent DST, though to a lesser degree. Our data, reflecting the impact of time policy on circadian burden and subsequent health benefits, support the cessation of BAS.
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