Dayna A Johnson1, Devin L Brown2, Lewis B Morgenstern3, William J Meurer4, Lynda D Lisabeth5. 1. Division of Sleep and Circadian Disorders, Brigham and Women's Hospital and Harvard Medical School, 221 Longwood Ave BLI 225, Boston, MA 02115, USA; Department of Epidemiology, School of Public Health, University of Michigan, 1415 Washington Heights 2649B SPH 1, Ann Arbor, MI 48109, USA. 2. Department of Neurology, University of Michigan, 1920 Taubman Center, Ann Arbor, MI 48109, USA; Stroke Program, University of Michigan, 1500 E Medical Center Dr CVC 3393, Ann Arbor, MI 48109, USA. 3. Department of Epidemiology, School of Public Health, University of Michigan, 1415 Washington Heights 2649B SPH 1, Ann Arbor, MI 48109, USA; Department of Neurology, University of Michigan, 1920 Taubman Center, Ann Arbor, MI 48109, USA; Stroke Program, University of Michigan, 1500 E Medical Center Dr CVC 3393, Ann Arbor, MI 48109, USA. 4. Department of Neurology, University of Michigan, 1920 Taubman Center, Ann Arbor, MI 48109, USA; Department of Emergency Medicine, University of Michigan, Ann Arbor, MI 48109, USA; Stroke Program, University of Michigan, 1500 E Medical Center Dr CVC 3393, Ann Arbor, MI 48109, USA. 5. Department of Epidemiology, School of Public Health, University of Michigan, 1415 Washington Heights 2649B SPH 1, Ann Arbor, MI 48109, USA; Department of Neurology, University of Michigan, 1920 Taubman Center, Ann Arbor, MI 48109, USA; Stroke Program, University of Michigan, 1500 E Medical Center Dr CVC 3393, Ann Arbor, MI 48109, USA. Electronic address: llisabet@umich.edu.
Abstract
BACKGROUND: Neighborhood characteristics have been linked to health outcomes. Various mechanisms link neighborhoods and health outcomes; sleep patterns may be 1 contributor; however, little is known about the social determinants of disordered sleep. We examined the association of neighborhood characteristics with sleep duration and daytime sleepiness. METHODS: Participants (n = 801) enrolled as pairs (55 without pair), from 10 churches in the Stroke Health and Risk Education project; 760 were included for analysis (41 withdrew). Sleep duration (hours of sleep at night) and daytime sleepiness (adaptation of Berlin questionnaire; range, 0-3 [more daytime sleepiness]) were self-reported. Neighborhood characteristics included disadvantage, per capita violent crime (census tract level), and safety (self-reported and individual level). We fit generalized linear mixed models and multinomial and binomial logistic regression models to examine the associations between neighborhood characteristics and sleep outcomes while accounting for the clustering within churches and pairs, before and after adjustment for self-reported confounders (age, gender, income, education, body mass index, depressive symptoms, hypertension, and diabetes). RESULTS: The mean hours of sleep duration is 6.7 ± 1.2, and the mean daytime sleepiness is 0.8 ± 0.9. Neighborhood characteristics were not associated with sleep duration. Higher perceived neighborhood safety was associated with an 18.4% lower odds of daytime sleepiness in the unadjusted model (odds ratio, 0.82 [95% confidence interval, 0.69-0.96]). The association was attenuated in the fully adjusted model. Neighborhood disadvantage and violent crime were related to lower daytime sleepiness; however, associations were not statistically significant. CONCLUSION: Self-reported neighborhood safety was associated with lower daytime sleepiness. Future exploration of the pathways linking neighborhood characteristics and sleep is warranted.
BACKGROUND: Neighborhood characteristics have been linked to health outcomes. Various mechanisms link neighborhoods and health outcomes; sleep patterns may be 1 contributor; however, little is known about the social determinants of disordered sleep. We examined the association of neighborhood characteristics with sleep duration and daytime sleepiness. METHODS:Participants (n = 801) enrolled as pairs (55 without pair), from 10 churches in the Stroke Health and Risk Education project; 760 were included for analysis (41 withdrew). Sleep duration (hours of sleep at night) and daytime sleepiness (adaptation of Berlin questionnaire; range, 0-3 [more daytime sleepiness]) were self-reported. Neighborhood characteristics included disadvantage, per capita violent crime (census tract level), and safety (self-reported and individual level). We fit generalized linear mixed models and multinomial and binomial logistic regression models to examine the associations between neighborhood characteristics and sleep outcomes while accounting for the clustering within churches and pairs, before and after adjustment for self-reported confounders (age, gender, income, education, body mass index, depressive symptoms, hypertension, and diabetes). RESULTS: The mean hours of sleep duration is 6.7 ± 1.2, and the mean daytime sleepiness is 0.8 ± 0.9. Neighborhood characteristics were not associated with sleep duration. Higher perceived neighborhood safety was associated with an 18.4% lower odds of daytime sleepiness in the unadjusted model (odds ratio, 0.82 [95% confidence interval, 0.69-0.96]). The association was attenuated in the fully adjusted model. Neighborhood disadvantage and violent crime were related to lower daytime sleepiness; however, associations were not statistically significant. CONCLUSION: Self-reported neighborhood safety was associated with lower daytime sleepiness. Future exploration of the pathways linking neighborhood characteristics and sleep is warranted.
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