Introduction The typical advice is that in order to avoid insomnia, people should avoid activities in bed other than sleep. Yet, activities such as reading and watching TV in bed are common. Methods Data were obtained from the Sleep and Health Activity, Diet, Environment, and Socialization (SHADES) Study, N=1,007 adults age 22-60. Sleep hygiene was assessed using items from the Sleep Practices and Attitudes Questionnaire (SPAQ), which asked whether respondents agree/disagree that they do the following in bed: Read, Watch TV, Eat, Work, Worry, and/or Argue. These were analyzed in relation to Insomnia Severity Index (ISI) score, Pittsburgh Sleep Quality Index (PSQI) score, Epworth Sleepiness Scale (ESS) score, Fatigue Severity Scale (FSS) score, and self-reported sleep duration (TST), sleep latency (SL), and wake after sleep onset (WASO). Covariates included age, sex, education, and income. Results Those that frequently engaged in activities were: reading (75%), watching TV (63%), eating (42%), working (32%), worrying (82%), and arguing (23%). Reading was associated with less WASO (B=-14min, p=0.02). Watching TV was associated with higher ISI (B=1.22, p=0.04), PSQI (B=1.04, p=0.007), and ESS (B=0.87, p=0.049), and less TST (B=-0.29, p=0.04). Eating was associated with higher ISI (B=1.75, p=0.01), PSQI (B=1.23, p=0.008), and FSS (B=4.36, p=0.002). Working was associated with higher ISI (B=1.82, p=0.019), PSQI (B=1.65, p=0.001), and ESS (B=1.78, p=0.002). Worrying was associated with higher ISI (B=7.34, p<0.0005), PSQI (B=4.40, p<0.0005), ESS (B=2.53, p=0.001), FSS (B=9.51, p<0.0005), and SL (B=19.39, p<0.0005), and less TST (B=-0.55, p=0.023). Arguing was associated with higher ISI (B=3.78, p<0.0005), PSQI (B=3.15, p<0.0005), ESS (1.47, p=0.023), and SL (B=10.97, p=0.013), and lower TST (B=-0.71, p=0.001). Conclusion Individuals who perform mentally distressing activities such as worrying and arguing experience especially worse sleep, and those who read in bed have fewer awakenings. Support The SHADES study was funded by R21ES022931. Dr. Grandner is supported by R01MD011600.

The effectiveness of scientific educational outreach among children has been difficult to measure because of many confounding variables such as teaching style, material taught and many other factors. To find clarity with this, an experiment was designed involving two 5th grade classes from Martinez, CA, John Swett Elementary and Las Juntas Elementary, and one 7th grade class from Pleasant Hill, CA, Sequoia Middle School. The experiment entailed using an educational poster with characters from a well‐known Disney movie, Inside Out, to teach students about emotional regulation and control guided by the Limbic system and its main components (hypothalamus, amygdala, hippocampus and thalamus). All three schools were approached using the same protocol: a pre‐test, an educational portion with the poster, a hands‐on activity, and then a post‐test. The hands‐on activity, creating emotion stress balls, was specifically meant to reinforce the material to the children and give them a broader understanding of how to positively deal with their own emotions. In addition to the quantitative pre‐and‐post‐test, a qualitative survey was also administered using the Likert scale to assess how the poster was perceived, the ease of understanding and other factors. The 5th grade students showed a statistically significant quantitative improvement between their pre‐and‐post‐test average results and the 7th graders showed a higher qualitative mean score, indicating they had a better appreciation of the outreach.This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.

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Introduction Sleep health impacts the community in many ways. Regional sleep health may reflect other important indicators of health and well-being. Few studies have examined sleep health at the regional level, though. Methods Data on neighborhood sleep health values were obtained from the “500 Cities” data collected by the CDC that includes census tract and proportion of the population in that region that report values associated with health, as assessed with the Behavioral Risk Factor Surveillance System. Data include the population of each census tract as well as census-estimated proportion of the population in each census tract that report obtaining at least 7 hours of sleep. Additional variables included as covariates in analyses included the proportion with healthcare access, that were obese, had high blood pressure, had diabetes, and were smokers. The Child Opportunity Index (COI) is a publicly-available index (DiversityDataKids.org) reported at the census tract level. It provides indices for “Education,” “Health & Environment,” and “Social & Economic” domains, as well as a global score. The present analysis merged the 500 Cities data with the COI data, using census tract as the matching variable. Linear regression analyses examined COI global and subscale scores as outcome variable and proportion of the population obtaining 7 hours of sleep as the independent variable, unadjusted and adjusted for covariates. When data were merged, 27,130 census tracts were included. Results Sleep sufficiency was associated with global COI, such that for each additional percent of the population that obtains >=7 hours of sleep, COI increases by 3.6 points (95%CI[3.57,3.64]; p<0.0001); this was attenuated in adjusted analyses (B=1.58; 95%CI[1.53,1.63]; p<0.0001). Each component of COI was related to sleep sufficiency, including education (B=3.06; 95%CI[1.19,1.33]; <0.0001), health & environment (B=3.61; 95%CI[3.57,3.64]; p<0.0001), and social & economic (B=2.23; 95%CI[2.19,2.28]; p<0.0001). All associations were attenuated but significant in adjusted analyses. Conclusion Regional prevalence of insufficient sleep was linearly associated with Child Opportunity Index, which itself is an important predictor of a wide range of health and economic outcomes. Community sleep health interventions may have wide-ranging benefits. Support (If Any)

Introduction Promoting sleep health at the neighborhood level may be an efficient way to promote overall health and well-being. This study examined the relative contribution of sleep health, versus other regional health metrics. Methods Neighborhood sleep health values were obtained from the “500 Cities” data collected by the CDC, which includes census tract and proportion that report values associated with health. Data include the population of each census tract as well as census-estimated proportion of the population in each census tract that report obtaining at least 7 hours of sleep. Other health indicators evaluated included access to health insurance, past-year routine medical or dental checkup, older adult preventive care, leisure-time activity, mammography, pap testing, and prevalence of arthritis, binge drinking, hypertension, antihypertensive use, cancer, asthma, coronary disease, cholesterol screening, colon screening, COPD, smoking, diabetes, hypercholesterolemia, kidney disease, poor mental and physical health, obesity, stroke, and teeth lost. The Child Opportunity Index (COI) is a publicly-available index (DiversityDataKids.org) reported at the census tract level. It provides indices for “Education,” “Health and Environment,” and “Social and Economic” domains, as well as a global score. The present analysis merged the 500 Cities data with the COI data, using census tract as the matching variable. When data were merged, 27,130 census tracts were included. Results In stepwise analyses adjusted for population size, with global COI as the dependent variable, sleep health emerged as the strongest predictor, accounting for 57.2% of the variance of global COI (p<0.0001). When all other health predictors were included in the model, the next largest contributors were teeth lost (additional 15.5%), health insurance (additional 3.0%), and asthma (additional 1.4%). Similarly, when stepwise analyses examined each component of COI as dependent variable, sleep health consistently emerged as the most substantial predictor, accounting for 41.2%, 24.3%, and 56.4% of the variance of “Education,” “Health and Environment,” and “Social and Economic” scores, respectively (all p<0.0001). Conclusion Sleep health is more strongly associated with overall COI (and all its components) than any other regional health metric. Public health efforts targeting sleep health may have disproportionately beneficial impact on factors that support family health and well-being. Support (If Any)