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Prevalence and Risk Factors of Poor Sleep Quality among Chinese Elderly in an Urban Community: Results from the Shanghai Aging Study
Open accessAbstract
BACKGROUND: Sleep disorders causes a significant negative effect on mental and physical health, particularly among the elderly. The disease burden and risk factors of poor sleep quality of the elderly need to be verified using a validated form of measurement in urban mainland China. METHODS: This study included 1086 community residents aged ≥ 60 years who completed the Chinese version of the Pittsburgh Sleep Quality Index (CPSQI). Poor sleeper was defined by a CPSQI global score of >5. Subjects also accepted the neurological and neuropsychological assessments, including the Mini-Mental State Examination, Center for Epidemiological Studies Depression Scale, and Zung Self-Rating Anxiety Scale (ZSAS). A history of chronic diseases was confirmed by the medical records of each participant. RESULTS: The prevalence of poor sleep quality in this population was 41.5% (95% confidence interval (CI) = 38.6-44.5%), with a higher rate observed in elderly females (45.8% [95% CI = 41.9-49.7%]) than that in elderly males (35.8% [95% CI = 31.4-40.1%]). The prevalence rate increased with age, from 32.1% (95% CI = 27.8-36.4%) in those aged 60-69 years to 52.5% (95% CI = 45.9-59.1%) in those aged ≥ 80 years (p value for trend<0.001). Multivariate logistic regression analysis indicated that age (OR = 1.03[95% CI = 1.01-1.05], p<0.001), less education duration (OR = 1.04 [95% CI = 1.01-1.08, p = 0.014), living alone (OR = 1.62 [95% CI = 1.02-2.58], p = 0.04), anxiety (ZSAS score: OR = 1.09 [95% CI = 1.05-1.12], p<0.001), number of chronic disease (OR = 1.18 [95% CI = 1.07-1.30], p = 0.14) and arthritis (OR = 1.45[95% CI = 1.05-2.01], p = 0.025) were risk factors of poor sleep quality. CONCLUSIONS: Poor sleep quality is highly prevalent among elderly Chinese residents in urban Shanghai. Growing attention and comprehensive countermeasures involving psycho-social and personal activities might alleviate the sleep problem in the elderly.
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“Several diverse factors may contribute to sleep disturbances in a large percentage of older adults including retirement, health problems, death of spouse/family members,(Jackowska, Dockray, Hendrickx, and Steptoe 2011;Luo, Zhu, Zhao, Guo, Meng, Hong, and Ding 2013) and changes in circadian rhythm.”
From Successful aging: Advancing the science of physical independence in older adults (2015) · cites this paper as Luo et al. 2013
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Metadata
- Authors
- Luo, J., Zhu, G., Zhao, Q., Guo, Q., Meng, H., Hong, Z., & Ding, D.
- Affiliations
- Fudan University (CN)
- Corresponding author
- Ding, Ding
- Venue
- PLoS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2013-11-25
- Volume
- 8
- Issue
- 11
- Pages
- e81261
- ISSN
- 1932-6203 (ISSN-L)
- PMC
- PMC3839883
- OpenAlex
- W2081433986
- Cited by
- 219
- References
- 46
- Citations by year
- 2026: 10 · 2025: 19 · 2024: 19 · 2023: 24 · 2022: 17 · 2021: 31 · 2020: 21 · 2019: 21 · 2018: 20 · 2017: 15 · 2016: 9 · 2015: 9 · 2014: 4
- FWCI
- 9.91
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- PLoS ONE (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- National Natural Science Foundation of China
- Topics
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Sleep and related disorders
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Aging, Health, and Disability
- Health Sciences › Medicine › Physiology (medical) › Obstructive Sleep Apnea Research
- Keywords
- poor sleep quality, older adults, sleep disorders, risk factors, prevalence, Chinese older adults, urban communities, Pittsburgh Sleep Quality Index, anxiety, depression, chronic disease, arthritis, living alone, educational attainment
- MeSH terms
- Aged, Aged, 80 and over, China, Female, Humans, Male, Risk Factors, Sleep, Urban Population, Prevalence, Logistic Models
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