Logan D Schneider1, Robert E Moss2, Daniel M Goldenholz3. 1. Stanford Center for Sleep Sciences and Medicine, Stanford University, Palo Alto, California. 2. Seizure Tracker LLC, Alexandria, Virginia. 3. Division of Epilepsy, Beth Israel Deaconess Medical Center, Harvard University, Boston, Massachusetts.
Abstract
OBJECTIVE: Given the known association of daylight saving time (DST) transitions with increased risk of accidents, heart attack, and stroke, we aimed to determine whether seizures, which are reportedly influenced by sleep and circadian disruption, also increased in frequency following the transition into DST. METHODS: Using Seizure Tracker's self-reported data from 12 401 individuals from 2008-2016, 932 717 seizures were assessed for changes in incidence in relation to DST transitions. Two methods of standardization-z scores and unit-scaled rate ratios (RRs)-were used to compare seizure propensities following DST transitions to other time periods. RESULTS: As a percentile relative to all other weeks in a given year, absolute seizure counts in the week of DST fell below the median (DST seizure percentiles mean ± SD: 19.68 ± 16.25, P = 0.01), which was concordant with weekday-specific comparisons. Comparatively, RRs for whole-week (1.06, 95% confidence interval [CI] 1.02-1.10, P = 0.0054) and weekday-to-weekday (RR range 1.04-1.16, all P < 0.001) comparisons suggested a slightly higher incidence of seizures in the DST week compared to all other weeks of the year. However, examining the similar risk of the week preceding and following the DST-transition week revealed no significant weekday-to-weekday differences in seizure incidence, although there was an unexpected, modestly decreased seizure propensity in the DST week relative to the whole week prior (RR 0.94, 95% CI 0.91-0.96, P < 0.001). SIGNIFICANCE: Despite expectations that circadian and sleep disruption related to DST transitions would increase the incidence of seizures, we found little substantive evidence for such an association in this large, longitudinal cohort. Although large-scale observational/epidemiologic cohorts can be effective at answering such questions, additional covariates (eg, sleep duration, seizure type, and so on) that may underpin the association were not able available, so the association has not definitively been ruled out. Wiley Periodicals, Inc.
OBJECTIVE: Given the known association of daylight saving time (DST) transitions with increased risk of accidents, heart attack, and stroke, we aimed to determine whether seizures, which are reportedly influenced by sleep and circadian disruption, also increased in frequency following the transition into DST. METHODS: Using Seizure Tracker's self-reported data from 12 401 individuals from 2008-2016, 932 717 seizures were assessed for changes in incidence in relation to DST transitions. Two methods of standardization-z scores and unit-scaled rate ratios (RRs)-were used to compare seizure propensities following DST transitions to other time periods. RESULTS: As a percentile relative to all other weeks in a given year, absolute seizure counts in the week of DST fell below the median (DST seizure percentiles mean ± SD: 19.68 ± 16.25, P = 0.01), which was concordant with weekday-specific comparisons. Comparatively, RRs for whole-week (1.06, 95% confidence interval [CI] 1.02-1.10, P = 0.0054) and weekday-to-weekday (RR range 1.04-1.16, all P < 0.001) comparisons suggested a slightly higher incidence of seizures in the DST week compared to all other weeks of the year. However, examining the similar risk of the week preceding and following the DST-transition week revealed no significant weekday-to-weekday differences in seizure incidence, although there was an unexpected, modestly decreased seizure propensity in the DST week relative to the whole week prior (RR 0.94, 95% CI 0.91-0.96, P < 0.001). SIGNIFICANCE: Despite expectations that circadian and sleep disruption related to DST transitions would increase the incidence of seizures, we found little substantive evidence for such an association in this large, longitudinal cohort. Although large-scale observational/epidemiologic cohorts can be effective at answering such questions, additional covariates (eg, sleep duration, seizure type, and so on) that may underpin the association were not able available, so the association has not definitively been ruled out. Wiley Periodicals, Inc.