Safiyyah M Okoye1, Adam P Spira2, Nancy A Perrin3, Jennifer A Schrack4, Hae-Ra Han5, Sarah Wanigatunga6, Casandra Nyhuis6, Sarah L Szanton7. 1. Johns Hopkins University School of Nursing, Baltimore, Maryland, USA; Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA; Johns Hopkins Center on Aging and Health, Baltimore, Maryland, USA. Electronic address: sokoye1@jhmi.edu. 2. Johns Hopkins Center on Aging and Health, Baltimore, Maryland, USA; Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA; Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, Maryland, USA. 3. Johns Hopkins University School of Nursing, Baltimore, Maryland, USA. 4. Johns Hopkins Center on Aging and Health, Baltimore, Maryland, USA; Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA. 5. Johns Hopkins University School of Nursing, Baltimore, Maryland, USA; Department of Health, Behavior and Society, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA. 6. Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA. 7. Johns Hopkins University School of Nursing, Baltimore, Maryland, USA; Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA; Johns Hopkins Center on Aging and Health, Baltimore, Maryland, USA.
Abstract
OBJECTIVE: To examine the association of housing and neighborhood conditions with sleep among disadvantaged older adults. METHODS: We used data from 136 low-income, predominantly Black older adults with disabilities. Predictors were indices of: interior housing conditions (eg, pests, tripping hazards); exterior housing conditions (eg, broken windows); and neighborhood disorder (eg, litter, vacant buildings). Outcomes were actigraphic total sleep time (TST), wake after sleep onset (WASO), and sleep efficiency (SE). RESULTS: In models adjusted for age, sex, education, living arrangement, comorbidities, and physical performance, each additional exterior housing problem was associated with 20.9-minutes less TST (95% confidence interval [CI]: -39.2, -2.6), 8.6-minutes more WASO (95% CI: 0.7, 16.5), and 2.3% lower SE (95% CI: -4.2, -0.4). The associations of interior housing conditions and neighborhood disorder with the sleep parameters were of smaller magnitude and not statistically significant. CONCLUSIONS: Future studies should examine the effects of housing repair on sleep health.
OBJECTIVE: To examine the association of housing and neighborhood conditions with sleep among disadvantaged older adults. METHODS: We used data from 136 low-income, predominantly Black older adults with disabilities. Predictors were indices of: interior housing conditions (eg, pests, tripping hazards); exterior housing conditions (eg, broken windows); and neighborhood disorder (eg, litter, vacant buildings). Outcomes were actigraphic total sleep time (TST), wake after sleep onset (WASO), and sleep efficiency (SE). RESULTS: In models adjusted for age, sex, education, living arrangement, comorbidities, and physical performance, each additional exterior housing problem was associated with 20.9-minutes less TST (95% confidence interval [CI]: -39.2, -2.6), 8.6-minutes more WASO (95% CI: 0.7, 16.5), and 2.3% lower SE (95% CI: -4.2, -0.4). The associations of interior housing conditions and neighborhood disorder with the sleep parameters were of smaller magnitude and not statistically significant. CONCLUSIONS: Future studies should examine the effects of housing repair on sleep health.
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