基本チェックリストと健診データを用いた縦断研究に基づく要支援・要介護リスク評価尺度の開発  [in Japanese] Development of risk assessment scales for Needed Support/Long-Term Care certification: A longitudinal study using the Kihon Checklist and medical assessment data  [in Japanese]

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Author(s)

    • 高木 大資 TAKAGI Daisuke
    • 東京大学大学院医学系研究科保健社会行動学分野 Department of Health and Social Behavior, School of Public Health, The University of Tokyo
    • 近藤 尚己 KONDO Naoki
    • 東京大学大学院医学系研究科保健社会行動学分野 Department of Health and Social Behavior, School of Public Health, The University of Tokyo
    • 近藤 克則 KONDO Katsunori
    • 千葉大学予防医学センター|国立長寿医療研究センター老年学・社会科学研究センター老年学評価研究部 Center for Preventive Medical Sciences, Chiba University|Department of Gerontological Evaluation, Center for Gerontology and Social Science, National Center for Geriatrics and Gerontology

Abstract

<p><b>目的</b> 本研究は,市が保有する基本チェックリストと健康診断(以下,健診),約4年間の要支援・要介護認定データを結合し,その認定を予測するための要支援・要介護リスク評価尺度を開発することを目的とした。</p><p><b>方法</b> K市(政令指定都市)に在住し,2011年に基本チェックリストへの回答が得られた72,127人の高齢者を分析対象とする後ろ向きコホート研究を実施した。基本チェックリストのうち,第7期の介護予防・日常生活圏域ニーズ調査(以下,ニーズ調査)の必須項目12項目とオプション項目7項目に,2011年の健診データ(受診の有無,血圧・血液生化学検査5項目)と2011~15年の要支援・要介護認定情報を結合した。新規要支援・要介護認定をエンドポイントとする4つのCox比例ハザードモデル— 1) 性,年齢,必須項目12項目,2) 1)+オプション項目7項目,3) 2)+健診受診の有無,4) 3)+健診6項目をそれぞれ説明変数とし,変数増加法を用いて分析した。選択された各項目に対し,非標準化偏回帰係数(<i>B</i>)を基に点数を割り当て,それらを合計する「要支援・要介護リスク評価尺度」を作成した。各評価尺度の予測妥当性を比較するため,receiver operating characteristics(ROC)解析を実施し,感度・特異度を算出した。</p><p><b>結果</b> 最長4年2か月の追跡期間中に11,039人(15.3%)が新たに要支援・要介護認定を受けた。性,年齢とニーズ調査の必須項目10項目から,0~55点の幅となる評価尺度が作成された。合計点数ごとの新規認定割合は,10点:3.2%,20点:14.7%,30点:31.6%,40点:56.7%,50点:75.0%であった。ROC曲線の曲線下面積は0.783であり,カットオフを20/21点とした場合,感度0.705,特異度0.731であった。ニーズ調査のオプション項目や健診項目を含めた評価尺度であっても,それらの値はほとんど変わらなかった(曲線下面積:0.786~0.787,感度:0.721~0.730,特異度:0.710~0.717)。</p><p><b>結論</b> 健診データを含めなくとも,基本チェックリスト10項目(ニーズ調査の必須項目に含まれる)から作成した評価尺度が,要支援・要介護認定リスクの予測評価に有用であることが示唆された。各保険者が保有する基本チェックリストまたは今後収集するニーズ調査データを活用し,個人レベルや地域レベルのリスクの予測評価が可能な要支援・要介護リスク評価尺度が開発できた。</p>

<p><b>Objectives</b> This study aimed to develop risk assessment scales for predicting the incidence of Needed Support/Long-Term Care certification, by aggregating data from the Kihon Checklist, medical assessments, and long-term care insurance certification during a follow-up period (a maximum of 4 years and 2 months) conducted in a municipality.</p><p><b>Methods</b> This retrospective cohort study included 72,127 older adults aged 65 years or older living in K City (an ordinance-designated city) who responded to the Kihon Checklist in 2011. We linked their medical assessment data (examined/unexamined, blood pressure, and five blood biochemical items) from 2011 and information on the incidence of long-term care insurance certification from 2011 to 2015 to the Kihon Checklist data (the 12 essential items and seven optional items from the Needs Survey). We constructed four Cox proportional hazards models as follows: 1) age, sex, and the Needs Survey's 12 essential items; 2) model 1 plus seven optional items; 3) model 2 plus examined/unexamined at medical assessment; and 4) model 3 plus blood pressure and five blood biochemical items, as independent variables. Recent requirement for Support/Long-Term Care certification was included as an outcome with stepwise forward selection. We assigned scores for each item based on the non-standardized regression coefficients obtained (<i>B</i>) and the sum of those scores was used to establish the risk assessment scales for predicting Needed Support/Long-Term Care certification from each model. A receiver operating characteristic (ROC) analysis was conducted to estimate the sensitivity and specificity in order to compare predictive validity of the scales.</p><p><b>Results</b> During the follow-up period, 11,039 (15.3%) individuals required a new incidence of a Needed Support/Needed Long-Term Care certification. A risk assessment scale of 0-55 was established based on age, sex, and the 10 essential items from the Needs Survey's. The incidence of certification were 3.2%, 14.7%, 31.6%, 56.7%, and 75.0% at scores of 10, 20, 30, 40, and 50, respectively. The area under the ROC curve (AUC) was 0.783, and the sensitivity and the specificity were 0.705 and 0.731, respectively (cut-off: 21/22). These values remained almost unchanged despite the addition of optional and medical assessment items (AUC: 0.786-0.787, sensitivity: 0.721-0.730, and specificity: 0.710-0.717).</p><p><b>Conclusion</b> Although the medical assessment data was not aggregated, the scale developed from the Kihon Checklist's 10 items (included in the Needs Survey's essential items) is useful for predicting the incidence of Needed Support/Long-Term Care certification. The scale, which evaluates the risk of needed support/long-term care at individual and community levels, was developed using the existing Kihon Checklist data or the Needs Survey's data collected subsequently by municipalities.</p>

Journal

  • Nihon Koshu Eisei Zasshi(JAPANESE JOURNAL OF PUBLIC HEALTH)

    Nihon Koshu Eisei Zasshi(JAPANESE JOURNAL OF PUBLIC HEALTH) 64(5), 246-257, 2017

    Japanese Society of Public Health

Codes

  • NII Article ID (NAID)
    130006942743
  • NII NACSIS-CAT ID (NCID)
    AN00189323
  • Text Lang
    JPN
  • ISSN
    0546-1766
  • NDL Article ID
    028213980
  • NDL Call No.
    Z19-216
  • Data Source
    NDL  J-STAGE 
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