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ID 31854
JaLCDOI
フルテキストURL
著者
Oishi, Junko Department of Epidemiology, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences
Doi, Hiroyuki Department of Epidemiology, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences Kaken ID publons researchmap
Kawakami, Norito Department of Mental Health, Graduate School of Medicine and Faculty of Medicine, the University of Tokyo
抄録

A cross-sectional study was conducted to evaluate the association between dietary intake and depressivesymptoms in community-dwelling elderly persons. Five-hundred elderly persons aged 65 to 75 years were randomly selected from the population of O city in Okayama Prefecture, Japan. Among 401 respondents (response rate, 80.0%), data from 279 (133 males, 146 females) who completed the questionnaire concerning dietary intake and depressive state were analyzed using logistic regression. Each of 17 dietary intakes was classified into tertiles:high intake, moderate intake, and low intake. The Center for Epidemiology Studies Depression scale (CES-D) was used. Among males, the observed odds ratios (the 95% confidence intervals) for the depressive state were 0.36 (95% CI:0.13-0.98) in the highest tertile of carotene intake, 0.33 (95% CI:0.12-0.93) in the highest tertile of vitamin C intake, 0.29 (95% CI:0.10-0.85) in the highest tertile of carbohydrate intake, and 0.33 (95% CI:0.12-0.92) in the medium tertile of vitamin E intake. Among females, similar results were observed, but these results were not statistically significant. The results suggested that carbohydrate, carotene, and vitaminC intakes are associated with lowering depressive symptoms among elderly persons dwelling in communities in Japan.

キーワード
dietary intake
depressive symptoms
elderly persons
cross-sectional study
gender
Amo Type
Original Article
発行日
2009-02
出版物タイトル
Acta Medica Okayama
63巻
1号
出版者
Okayama University Medical School
開始ページ
9
終了ページ
17
ISSN
0386-300X
NCID
AA00508441
資料タイプ
学術雑誌論文
言語
English
論文のバージョン
publisher
査読
有り
PubMed ID
Web of Science KeyUT