RESUMEN
BACKGROUND: Sundown syndrome (ie, agitation later in the day) is common in older adults with dementia. The underlying etiology for these behaviors is unclear. Possibilities include increased caregiver fatigue at the end of the day and disruption of circadian rhythms by both age and neurodegenerative illness. OBJECTIVE: This study sought to examine circumseptan (weekly) patterns in search volumes related to sundown syndrome, in order to determine if such searches peaked at the end of the weekend, a time when caregiver supports are least available. We also sought to examine both seasonal differences and associations of state-by-state search activity with both state latitude and yearly sun exposure. METHODS: Daily Internet search query data was obtained from Google Trends (2005-2017 inclusive). Circumseptan patterns were determined by wavelet analysis, and seasonality was determined by the difference in search volumes between winter (December, January, and February) and summer (June, July, and August) months. Geographic associations between percent sunny days and latitude were done on a state-by-state basis. RESULTS: "Sundowning" searches showed a significant increase at the end of the weekend with activity being 10.9% (SD 4.0) higher on Sunday as compared to the rest of the week. Search activity showed a seasonal pattern with search activity significantly highest in the winter months (36.6 [SD 0.6] vs 13.7 [SD 0.2], P<.001). State-by-state variations in "sundowning" searches showed a significant negative association with increasing mean daily sunlight (R2=.16, ß=-.429 [SD .149], P=.006) and showed a positive association with increasing latitude (R2=.38, ß=.648 [SD .122], P<.001). CONCLUSIONS: Interest in "sundowning" is highest after a weekend, which is a time when external caregiver support is reduced. Searches related to sundown syndrome also were highest in winter, in states with less sun, and in states at more northerly latitudes, supporting disrupted circadian rhythms as another contributing factor to these behaviors.
RESUMEN
BACKGROUND: North American and European accreditation bodies have legislated progressively more strict work hour restrictions for residents in light of evidence that sleep deprivation leads to increased medical errors and decreased wellbeing. The purpose of the study is to determine the physiologic demands of internal medicine training during residency as well as document average sleep (on- and off-call) and physical activity performed using accelerometers. METHODS: A total of 40 internal medicine residents working on the clinical teaching unit at a single center were enrolled in the study from November 2011 to March 2016. There were 22 subjects that completed the study and were included in the analysis. SenseWear PRO 2 armband monitors were worn for 5 consecutive days including one call day. The primary outcomes of the study were to quantify and compare the calories per day, steps per day, METs per hour, hours of activity, hours of sleep, and sleep efficiency for on call versus post-call and non-call days. RESULTS: The average activity per day, calories per day, steps per day and METs per hour for the call day were 7.6 ± 7.6 h, 2647.0 ± 541.1, 11,261.1 ± 2355.9, and 1.7 ± 0.2 respectively. Each of these parameters had a statistically significant F statistic compared to post-call and non-call days. The subjects had a mean of 1.8 ± 2.0 h of sleep per day with a sleep efficiency of 77.3 ± 23.8% for the call day. The F statistic for sleep per day was significant with a p value < 0.001. CONCLUSION: This study shows that overnight call has a substantial impact on multiple metabolic parameters. These findings have potentially important implications on future resident working hour restrictions.
RESUMEN
BACKGROUND: Lack of physical activity and weight gain are two of the biggest drivers of health care costs in the United States. Healthy contemplations are required before any changes in behavior, and a recent study has shown that they have underlying periodicities. OBJECTIVE: The aim of this study was to examine seasonal variations in state-by-state interest in both weight loss and increasing physical activity, and how these variations were associated with geographic latitude using Google Trends search data for the United States. METHODS: Internet search query data were obtained from Google Trends (2004-2016). Time series analysis (every 2 weeks) was performed to determine search volume (normalized to overall search intensity). Seasonality was determined both by the difference in search volumes between winter (December, January, and February) and summer (June, July, and August) months and by the amplitude of cosinor analysis. RESULTS: Exercise-related searches were highest during the winter months, whereas weight loss contemplations showed a biphasic pattern (peaking in the summer and winter months). The magnitude of the seasonal difference increased with increasing latitude for both exercise (R2=.45, F1,49=40.09, beta=-.671, standard deviation [SD]=0.106, P<.001) and weight loss (R2=.24, F1,49=15.79, beta=-.494, SD=0.124, P<.001) searches. CONCLUSIONS: Healthy contemplations follow specific seasonal patterns, with the highest contemplations surrounding exercise during the winter months, and weight loss contemplations peaking during both winter and summer seasons. Knowledge of seasonal variations in passive contemplations may potentially allow for more efficient use of public health campaign resources.