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KAKEN_25380403seika.pdf
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要介護状態を考慮した長寿リスクのモデリングと評価 : ベイズ・アプローチ
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ヨウカイゴ ジョウタイ オ コウリョシタ チョウジュ リスク ノ モデリング ト ヒョウカ : ベイズ・アプローチ
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Yokaigo jotai o koryoshita choju risuku no moderingu to hyoka : Beizu apurochi
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Modeling and evaluating longevity risk in consideration with long term care status
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小暮, 厚之
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コグレ, アツユキ
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Kogure, Atsuyuki
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慶應義塾大学・総合政策学部・教授
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Research team head
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科研費研究者番号 : 80178251
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2017
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科学研究費補助金研究成果報告書
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2016
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平均寿命の増加は, 介護状態に陥る可能性の増大を伴う。我が国を始め高齢化を迎えている諸国では, いわゆる「長寿リスク」に加え「介護リスク」に直面している。介護リスクを考察する上で, 死亡率がいかに健康状態(要介護度)と関連するかを把握することが重要となる。しかし, 関連するデータの欠如によって, 死亡率と健康状態のダイナミックな関係に関する研究は乏しい。本研究では, 要介護状態別の死亡数データは欠如しているという想定の下で, 要介護状態に応じた死亡率を予測する新たなモデルを提案し, ベイズ法による予測の枠組みを構築した。この手法を我が国の介護年金制度のデータに適用し, 要介護状態別の死亡率の予測を行った。
Increased human lifetime is accompanied by a greater chance of becoming disabled. Aging populations such as Japan have faced with the so-called long-term care (LTC) risk in addition to the longevity risk. The key element of the solutions is how the mortality is related to health states. However, study on the complicated mortality dynamics between the mortality and the health state is limited due to lack of data. This research has proposed a new methodology to forecast mortality rates by the LTC status under the premise that the death data on the LTC sub-populations are not available, but the corresponding population exposures are available. Based on this model we have constructed a Bayesian methodology to forecast future mortality rates. We have applied the proposed methodology to the data from the Japanese long-term care insurance system and predicted the future mortality rates by the required level of the long-term care.
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研究種目 : 基盤研究(C)(一般)
研究期間 : 2013~2016
課題番号 : 25380403
研究分野 : 社会科学
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