| Project/Area Number |
13670411
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Public health/Health science
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| Research Institution | Obirin University (2004)
National Institute for Longevity Sciences,NCGG (2001-2003) |
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Principal Investigator |
NIINO Naoakira Obirin University, Graduate school, Professor, 大学院・国際学研究科, 教授 (40201686)
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| Co-Investigator(Kenkyū-buntansha) |
SHIMOKATA Hiroshi National Institute for longevity Sciences, Epidemiology, Head, 研究所・疫学研究部, 部長 (10226269)
ANDO Fujiko National Institute for longevity Sciences, Epidemiology, Chief, 研究所・疫学研究部, 室長 (90333393)
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| Project Period (FY) |
2001 – 2004
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| Project Status |
Completed (Fiscal Year 2004)
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| Budget Amount *help |
¥3,300,000 (Direct Cost: ¥3,300,000)
Fiscal Year 2004: ¥800,000 (Direct Cost: ¥800,000)
Fiscal Year 2003: ¥800,000 (Direct Cost: ¥800,000)
Fiscal Year 2002: ¥800,000 (Direct Cost: ¥800,000)
Fiscal Year 2001: ¥900,000 (Direct Cost: ¥900,000)
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| Keywords | community-dwelling elderly / depressive symptoms / risk factor / prevalence / GDS / cross-sectional study / longitudinal study / 高齢者 / 在宅 / 心理的要因 / 身体的的要因 / 社会的要因 |
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| Research Abstract |
The purpose of this study was to investigate the prevalence and risk factors of depressive symptoms among community dwelling elderly people. Data on depressive symptoms from the 1^<st>, 2^<nd>, and 3^<rd> survey of NILS-LSA (National Institute for Longevity Sciences, Longitudinal Study of Aging) were analyzed cross-sectionally and longitudinally. Depressive symptoms were measured by the Short Version of Geriatric Depression Scale (SGDS).
The results were
1.Prevalence of depressive symptoms (the proportion of the elderly whose SGDS-scores were 6 or higher) was 19.9% at the 1^<st> survey, 20.2% at the 2^<nd>, and 19.5% at the 3^<rd>.
2.Data from the 1st survey were analyzed cross-sectionally. Low ADL (activities of daily living), low subjective health, and fear of falling were significant correlates of depressive symptoms by multiple logistic regression analysis
3.Data from the 2nd survey were combined with data from the 1st survey to examine the predictors of depressive symptoms. By multiple logistic regression analysis, history of depression symptoms and low subjective health remained significant predictors of depressive symptoms.
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