Daylight Saving Time Transitions: Impact on Total Mortality

All cause and cause specific mortality associated with transition to daylight saving time in US: nationwide, time series, observational study

Objectives

To estimate the association between the transition to daylight saving time and the risks of all cause and cause specific mortality in the US.

Design

Nationwide time series observational study based on weekly data.

Setting

US state level mortality data from the National Center for Health Statistics, with death counts from 50 US states and the District of Columbia, from the start of 2015 to the end of 2019.

Population

13 912 837 reported deaths in the US.

Main outcome measures

Weekly counts of mortality for any cause, and for Alzheimer's disease, dementia, circulatory diseases, malignant neoplasms, and respiratory diseases.

Results

During the study period, 13 912 837 deaths were reported. The analysis found no evidence of an association between the transition to spring daylight saving time (when clocks are set forward by one hour on the second Sunday of March) and the risk of all cause mortality during the first eight weeks after the transition (rate ratio 1.003, 95% confidence interval 0.987 to 1.020). Autumn daylight saving time is defined in this study as the time when the clocks are set back by one hour (ie, return to standard time) on the first Sunday of November. Evidence indicating a substantial decrease in the risk of all cause mortality during the first eight weeks after the transition to autumn daylight saving time (0.974, 0.958 to 0.990). Overall, when considering the transition to both spring and autumn daylight saving time, no evidence of any effect of daylight saving time on all cause mortality was found (0.988, 0.972 to 1.005). These patterns of changes in mortality rates associated with transition to daylight saving time were consistent for Alzheimer's disease, dementia, circulatory diseases, malignant neoplasms, and respiratory diseases. The protective effect of the transition to autumn daylight saving time on the risk of mortality was more pronounced in elderly people aged ≥75 years, in the non-Hispanic white population, and in those residing in the eastern time zone.

Conclusions

In this study, transition to daylight saving time was found to affect mortality patterns in the US, but an association with additional deaths overall was not found. These findings might inform the ongoing debate on the policy of shifting daylight saving time.

Time series analysis in environmental epidemiology: challenges and considerations

In environmental epidemiology, time series analyses represent a widely used statistical tool. However, though being commonly used, there is soften confusion regarding the specific requirements, such as which link function might be most appropriate, when or how to control for seasonality or how to account for lags. The present overview draws from experiences in other disciplines and discusses the proper execution of time series analyses based on considerations that are relevant in environmental epidemiology. Time series analysis in environmental epidemiology focuses on acute events caused by short-term changes in exposure. These exposures should be fairly wide-spread affecting a large number of persons, usually all inhabitants of a political entity. Pollutants in air or drinking water as well as meteorological factors serve as typical examples. Despite the many time series analyses performed world-wide, some health effects that would lend themselves to that approach are still under-explored. This would include also some neurological and psychiatric endpoints. Int J Occup Med Environ Health. 2023;36(6):704-16.

Chronobiology: Is daylight saving time a deer-saving time?

Earlier human activity relative to sunrise and sunset, the very essence of daylight saving time, is linked with health and safety detriments in humans. A new study predicts that deer, at least, may benefit from earlier human activity through reduced deer-vehicle collisions.

Daylight saving time affects European mortality patterns

Daylight saving time (DST) consists in a one-hour advancement of legal time in spring offset by a backward transition of the same magnitude in fall. It creates a minimal circadian misalignment that could disrupt sleep and homoeostasis in susceptible individuals and lead to an increased incidence of pathologies and accidents during the weeks immediately following both transitions. How this shift affects mortality dynamics on a large population scale remains, however, unknown. This study examines the impact of DST on all-cause mortality in 16 European countries for the period 1998-2012. It shows that mortality decreases in spring and increases in fall during the first two weeks following each DST transition. Moreover, the alignment of time data around DST transition dates revealed a septadian mortality pattern (lowest on Sundays, highest on Mondays) that persists all-year round, irrespective of seasonal variations, in men and women aged above 40.

Phase Response Curve to Light under Ambulatory Conditions: A Pilot Study for Potential Application to Daylight Saving Time Transitions

Several studies have investigated the relationship between daylight saving time (DST) and sleep alterations, psychiatric disorders, cardiovascular events and traffic accidents. However, very few have monitored participants while maintaining their usual lifestyle before and after DST. Considering that DST transitions modify human behavior and, therefore, people's light exposure patterns, the aim of this study was to investigate the potential effects of DST on circadian variables, considering sleep and, for the first time, the human phase response curve to light. To accomplish this, eight healthy adults (33 ± 11 years old, mean ± SD) were recruited to monitor multivariable circadian markers and light exposure by means of a wearable ambulatory monitoring device: Kronowise^®. The following night phase markers were calculated: midpoints of the five consecutive hours of maximum wrist temperature (TM5) and the five consecutive hours of minimum time in movement (TL5), sleep onset and offset, as well as sleep duration and light intensity. TM5 for wrist temperature was set as circadian time 0 h, and the balance between advances and delays considering the phase response curve to light was calculated individually before and after both DST transitions. To assess internal desynchronization, the possible shift in TM5 for wrist temperature and TL5 for time in movement were compared. Our results indicate that the transition to DST seems to force the circadian system to produce a phase advance to adapt to the new time. However, the synchronizing signals provided by natural and personal light exposure are not in line with such an advance, which results in internal desynchronization and the need for longer synchronization times. On the contrary, the transition back to ST, which implies a phase delay, is characterized by a faster adaptation and maintenance of internal synchronization, despite the fact that exposure to natural light would favor a phase advance. Considering the pilot nature of this study, further research is needed with higher sample sizes.

Sleep and Alcohol Use Patterns During Federal Holidays and Daylight Saving Time Transitions in the United States

We conducted a retrospective observational study using remote wearable and mobile application data to evaluate whether US public holidays or Daylight Saving Time transitions were associated with significant changes in sleep behaviors, including sleep duration, sleep onset and offset, and the consistency of sleep timing, as well as changes in the point prevalence of alcohol use. These metrics were analyzed using objective, high resolution sleep-wake data (10,350,760 sleep episodes) and 5,777,008 survey responses of 24,250 US subscribers (74.5% male; mean age of 37.6 ± 9.8 years) to the wrist-worn biometric device platform, WHOOP (Boston, Massachusetts, United States), who were active users during 1 May 2020, through 1 May 2021. Compared to baseline, statistically significant differences in sleep and alcohol measures were found on most DST transitions, US public holidays, and their eves. For example, New Year's Eve corresponded with a sleep consistency decrease of 13.8 ± 0.3%, a sleep onset delay of 88.9 ± 3.2 min (00:01 vs. 22:33 baseline) later, a sleep offset delay of 78.1 ± 3.1 min (07:56 vs. 06:39), and an increase in the prevalence of alcohol consumption, with more than twice as many participants having reported alcohol consumption [+138.0% ± 6.7 (74.2% vs. 31.2%)] compared to baseline. In this analysis of a non-random sample of mostly male subscribers conducted during the COVID-19 pandemic, the majority of US public holidays and holiday eves were associated with sample-level increases in sleep duration, decreases in sleep consistency, later sleep onset and offset, and increases in the prevalence of alcohol consumption. Future work would be warranted to explore the generalizability of these findings and their public health implications, including in more representative samples and over longer time intervals.

Driving simulator performance worsens after the Spring transition to Daylight Saving Time

Circadian desynchrony and sleep deprivation related to the Spring transition to Daylight Saving Time (DST) have been associated with several unfavorable outcomes, including an increase in road traffic accidents. As previous work has mainly focused on analyzing historical crash/hospitalization data, there is virtually no literature investigating the effects of DST on specific driving performance indicators. Here, the effect of the Spring transition to DST on driving performance was investigated by means of a driving simulator experiment, in which participants completed two trials (one week distance, same time and day of the week) on exactly the same simulated route, the second trial taking place in the week after the transition to DST. Results were compared to those of a control group (who also underwent two trials, both before the DST transition), and documented significant worsening of driving performance after DST, as measured by a comprehensive set of simulator-derived indices.

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A simulator was used to study the effects of DST transition on driving behavior

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Several driving variables were negatively affected by DST transition

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These included reaction times, situation awareness and risk behavior

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DST-related circadian desynchrony is likely to result in driving impairment

Daylight savings time transitions and risk of out-of-hospital cardiac arrest: An interrupted time series analysis

BACKGROUND

Many studies have reported increases in the risk of acute cardiovascular events following daylight savings time (DST) transitions. We sought to investigate the effect of DST transition on the incidence of out-of-hospital cardiac arrest (OHCA).

METHODS

Between January 2000 and December 2020, we performed an interrupted time series analysis of the daily number of OHCA cases of medical aetiology from the Victorian Ambulance Cardiac Arrest Registry. The effect of DST transition on OHCA incidence was estimated using negative binomial models, adjusted for temporal trends, population growth, and public holidays.

RESULTS

A total of 89,409 adult OHCA of medical aetiology were included. Following the spring DST transition (i.e. shorter day), there was an immediate 13% (IRR 1.13, 95% CI: 1.02, 1.25; p = 0.02) increased risk of OHCA on the day of transition (Sunday) and the cumulative risk of OHCA remained higher over the first 2 days (IRR 1.17, 95% CI: 1.02, 1.34; p = 0.03) compared to non-transitional days. Following the autumn DST transition (i.e. longer day), there was a significant lagged effect on the Tuesday with a 12% (IRR 0.88, 95% CI: 0.77, 0.99; p = 0.04) reduced risk of OHCA. The cumulative effect following the autumn DST transition was also significant, with a 30% (IRR 0.70, 95% CI: 0.51, 0.96; p = 0.03) reduction in the incidence of OHCA by the end of the transitional week.

CONCLUSION

We observed both harmful and protective effects from DST transitions on the risk of OHCA. Strategies to reduce this risk in vulnerable populations should be considered.

A chronobiological evaluation of the risks of canceling daylight saving time

The long-term impact of seasonal regulation of clocks (Daylight Saving Time) is analyzed showing that it helped to mitigate the advance of the phase of human activity during the twentieth century and the exposure to the hours of the dawn in winter. The increased risks induced by circadian misalignment around transition dates are balanced by a better alignment of social clocks to the natural day in summer and in winter.

Daylight Saving Time: Pros and Cons

The original rationale for the adoption of daylight saving time (DST) was to conserve energy; however, the effects of DST on energy consumption are questionable or negligible. Conversely, there is substantial evidence that DST transitions have the cumulative effect on sleep deprivation with its adverse health effects. In light of current evidence, the European Commission in 2018 decided that biannual clock change in Europe would be abolished. Current indirect evidence supports the adoption of perennial standard time, which aligns best with the human circadian system and has the potential to produce benefits for public health and safety.

Nitrogen-Dioxide Remains a Valid Air Quality Indicator

In epidemiological studies, both spatial and temporal variations in nitrogen dioxide (NO₂) are a robust predictor of health risks. Compared to particulate matter, the experimental evidence for harmful effects at typical ambient concentrations is less extensive and not as clear for NO₂. In the wake of the “Diesel emission scandal—Dieselgate”, the scientific basis of current limit values for ambient NO₂ concentrations was attacked by industry lobbyists. It was argued that associations between NO₂ levels and medical endpoints were not causal, as NO₂ in older studies served as a proxy for aggressive particulate matter from incineration processes. With the introduction of particle filters in diesel cars, NO₂ would have lost its meaning as a health indicator. Austria has a high percentage of diesel-powered cars (56%). If, indeed, associations between NO₂ concentrations and health risks in previous studies were only due to older engines without a particle filter, we should expect a reduction in effect estimates over time as an increasing number of diesel cars on the roads were outfitted with particle filters. In previous time series studies from Vienna over shorter time intervals, we have demonstrated distributed lag effects over days up to two weeks and previous day effects of NO₂ on total mortality. In a simplified model, we now assess the effect estimates for moving 5-year periods from the beginning of NO₂ monitoring in Vienna (1987) until the year 2018 of same and previous day NO₂ on total daily mortality. Contrary to industry claims of a spurious, no longer valid indicator function of NO₂, effect estimates remained fairly stable, indicating an increase in total mortality of previous day NO₂ by 0.52% (95% CI: 0.35–0.7%) per 10 µg/m³ change in NO₂ concentration.