RESUMO
The human circadian timing system depends on the light/dark cycle as its main cue to synchronize with the environment, and thus with solar time. However, human activities depend also on social time, i.e. the set of time conventions and restrictions dictated by society, including Daylight Saving Time (DST), which adds an hour to any degree of desynchrony between social and solar time. Here, we used Google Trends as a data source to analyze diurnal variation, if any, and the daily peak in the relative search volume of 26 Google search queries in relation to the transitions to/from DST in Italy from 2015 to 2020. Our search queries of interest fell into three categories: sleep/health-related, medication and random non sleep/health-related. After initial rhythm and phase analysis, 11 words were selected to compare the average phase of the 15 days before and after the transition to/from DST. We observed an average phase advance after the transition to DST, and a phase delay after the transition to civil time, ranging from 25 to 60 minutes. Advances or delays shorter than 60 minutes, which were primarily observed in the sleep/health-related category, may suggest that search timing for these queries is at least partially driven by the endogenous circadian rhythm. Finally, a significant trend in phase anticipation over the years was observed for virtually all words. This is most likely related to an increase in age, and thus in earlier chronotypes, amongst Google users.
RESUMO
The objective of the present study was to test the effects of an inpatient management system (CircadianCare) aimed at limiting the negative impact of hospitalization on sleep by enhancing circadian rhythmicity. Fifty inpatients were randomized to either CircadianCare (n = 25; 18 males, 62.4 ± 1.9 years) or standard of care (n = 25; 14 males, 64.5 ± 2.3 years). On admission, all underwent a full sleep-wake evaluation; they then completed daily sleep diaries and wore an actigraph for the whole length of hospitalization. On days 1 (T0), 7 (T1), and 14 (T2, if still hospitalized), salivary melatonin for dim light melatonin onset (DLMO) and 24-h skin temperature were recorded. In addition, environmental noise, temperature, and illuminance were monitored. Patients in the CircadianCare arm followed 1 of 3 schedules for light/dark, meal, and physical activity timings, based on their diurnal preference/habits. They wore short-wavelength-enriched light-emitting glasses for 45 min after awakening and short-wavelength light filter shades from 18:00 h until sleep onset. While the first, primary registered outcome (reduced sleep-onset latency on actigraphy or diary) was not met, based on sleep diaries, there was a trend (0.05 < p < 0.1) toward an advance in bedtime for CircadianCare compared to standard of care patients between T0 and T1. Similarly, DLMO time significantly advanced in the small group of patients for whom it could be computed on both occasions, with untreated ones starting from earlier baseline values. Patients sleeping near the window had significantly higher sleep efficiency, regardless of treatment arm. As noise fluctuation increased, so did the number of night awakenings, regardless of treatment arm. In conclusion, the CircadianCare management system showed positive results in terms of advancing sleep timing and the circadian rhythm of melatonin. Furthermore, our study identified a combination of environmental noise and lighting indices, which could be easily modulated to prevent hospitalization-related insomnia.