Poor sleep is associated with lifestyle, however, few studies have addressed the association between sleep quality and the neighborhood environment. This study aimed to investigate the associations between living environment factors and sleep quality in older people. Participants were community-dwelling people aged ≥65 years who participated in the 2010 Japanese Gerontological Evaluation Study. The data of 16,650 people (8102 men, 8548 women) were analyzed. Sleep quality (good or poor) was evaluated using a self-administered questionnaire. Multilevel Poisson regression analysis stratified by depressive status (measured by the Geriatric Depression Scale-15 [GDS]) was conducted with sleep quality as the dependent variable and social and physical environmental factors as explanatory variables. The 12,469 non-depressive respondents and 4181 depressive respondents were evaluated. The regression analysis indicated that non-depressive participants slept better if they lived in environments with few hills or steps (prevalence ratio [PR] = 0.75, 95% CI: 0.56–0.9) and with places where they felt free to drop in (PR = 0.51, 95% CI: 0.26–0.98). For depressive participants, these associations were not evident. Living alone, poor self-rated health, low income, and unemployment were associated with poor sleep quality. In addition to support with these individual factors, improving environmental factors at the neighborhood level may improve the sleep quality of community-dwelling older adults.
Background: Homebound status is one of the most important risk factors associated with functional decline and long-term care in older adults. Studies show that neighborhood built environment and community social capital may be related to homebound status. This study aimed to clarify the association between homebound status for community-dwelling older adults and community environment-including social capital and neighborhood built environment-in rural and urban areas. Methods: We surveyed people aged 65 years and older residing in three municipalities of Niigata Prefecture, Japan, who were not certified as requiring long-term care. The dependent variable was homebound status; explanatory variables were communitylevel social capital and neighborhood built environment. Covariates were age, sex, household, marital status, socioeconomic status, instrumental activities of daily living, the Geriatric Depression Scale-15, self-rated health, number of diseases under care, and individual social capital. The association between community social capital or neighborhood built environment and homebound status, stratified by rural=urban areas, was investigated using multilevel logistic regression analysis. Results: Among older adults (n = 18,099), the homebound status prevalence rate was 6.9% in rural areas and 4.2% in urban areas. The multilevel analysis showed that, in rural areas, fewer older adults were homebound in communities with higher civic participation and with suitable parks or pavements for walking and exercising. However, no significant association was found between community social capital or neighborhood built environment and homebound status for urban older adults. Conclusions: Community social capital and neighborhood built environment were significantly associated with homebound status in older adults in rural areas.
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