Study on grasping age, period, and generation characteristics of 10 major causes of death by prefectures and application to health measures.
| Project/Area Number |
16K01809
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Applied health science
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| Research Institution | University of Tokyo Health Sciences |
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Principal Investigator |
Miwa Noriko 東京医療学院大学, 保健医療学部, 教授 (10377244)
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| Co-Investigator(Renkei-kenkyūsha) |
NAKAMURA Takashi 情報・システム研究機構, 統計数理研究所, 名誉教授
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| Project Period (FY) |
2016-04-01 – 2019-03-31
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| Project Status |
Completed (Fiscal Year 2018)
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| Budget Amount *help |
¥4,030,000 (Direct Cost: ¥3,100,000、Indirect Cost: ¥930,000)
Fiscal Year 2018: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Fiscal Year 2017: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2016: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
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| Keywords | 保健健康情報 / 年齢・時代・世代効果 / 健康施策 / 健康推進活動 |
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| Outline of Final Research Achievements |
The starting point for examining health policy and health promotion activities is to grasp "what caused" the disease trends. In this study, the method of deriving information useful for population strategies (measures applied to the entire population of an area) and high-risk strategies (measures applied to high-risk groups), based on extracted age, period, and generation characteristics by prefecture about the top ten most frequent causes of death in our country.
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| Academic Significance and Societal Importance of the Research Achievements |
各死因動向における都道府県別の年齢・時代・世代特性（効果）は３つの指標に応用でき、次のように集団戦略、高リスク戦略の検討に活用できる可能性が示唆された。①地域特性：各効果のパタンの類似性・相違性の観点から都道府県を捉え、背景因子との関連から具体的戦略の検討に繋げることができる。②将来推計：今後の集団戦略のシナリオ（現状維持・停滞・継続）のもとで、当該集団がもつ年齢・世代特性を加味した将来動向から、これからの重点死因、長期的戦略の検討に繋げることができる。③地域格差：時系列・年齢別・世代別にみた都道府県間のバラツキ（格差）状況から、日本全体あるいは特定の地域における取組みの成果を評価できる。
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Report
(4 results)
Research Products
(9 results)
