2022 Fiscal Year Final Research Report
Exploring association between weight trajectory and lifestyle diseases with artificial intelligence in post-menopausal women
Project/Area Number |
18K18146
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Research Category |
Grant-in-Aid for Early-Career Scientists
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Allocation Type | Multi-year Fund |
Review Section |
Basic Section 62010:Life, health and medical informatics-related
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Research Institution | The University of Tokyo |
Principal Investigator |
Ejima Keisuke 東京大学, 大学院医学系研究科(医学部), 客員研究員 (70730240)
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Project Period (FY) |
2018-04-01 – 2023-03-31
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Keywords | 疫学 / 肥満 / 生存解析 |
Outline of Final Research Achievements |
BMI trajectory was analyzed to assess its relationship with mortality risk in the Japanese population. I used data from the Japanese large cohort study (JPHC) with subjects aged 40 to her 69 who were followed for 20 years until the early 1990s. Six BMI trajectory groups were identified. Survival analyses revealed an increased risk of all-cause mortality in the BMI decreasing group (groups 3 and 5), stable underweight (group 1), and normal to obesity (group 6).
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Free Research Field |
数理疫学
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Academic Significance and Societal Importance of the Research Achievements |
単一時点のBMIは、個人および集団レベルの疾患および死亡リスクを評価するための有用なツールとして使用されてきているが、BMIの軌跡を考慮すると、より精度よく死亡リスクを評価できる可能性があることが示唆された。 生涯にわたるBMIの変遷と死亡リスクの関連性を調査するには、さらなる研究が必要と思われる。
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