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題名：建構一預測臺灣老人開始需要照護的周全性簡易評估量表之研究
作者：許維中
作者(外文)：Wei-Chung Hsu
校院名稱：亞洲大學
系所名稱：健康產業管理學系健康管理組
指導教授：蔡仲弘
學位類別：博士
出版日期：2015
主題關鍵詞：老人；開始需要照護；衰弱；功能下降；預測需要照護；older adults；new-onset care-need；frailty；functional decline；predicting care-need
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背景：人口老化為世界各國的普遍現象，但預測開始需要照護的工具則尚待建構。
目的：本研究嘗試建構一預測台灣老人開始需要照護之量表。
方法：本研究分析「臺灣地區中老年身心社會生活狀況長期追蹤調查研究」 (Taiwan Longitudinal Survey on Aging, TLSA) 1999與2003年之資料；以1999年年齡≥65歲共2890位參與者，排除於基準點需要照護的286位與失去追蹤的83位之後，2521位為本研究的總樣本。本研究首先基於生理原理、現有文獻、TLSA中可用的資料，確認年齡、體位指標 (anthropometrics)、身體功能 (physical functioning)、心理狀態、社會因素 (居住安排、社會支持、經濟狀況)、醫療指標 (住院或急診利用、共病、視力與聽力狀態)、總體性指標 (食慾、體重降低、自評健康) 為開始需要照護的可能預測因素；再選擇各構面最具預測需要照護能力的變項或題項；然後以建模樣本 (從總樣本2521人中隨機抽取2017位，80%) 建立量表模型，而其餘的504位則為驗證樣本，用以驗證所建立的模型。本研究以多變項邏輯斯迴歸 (multivariable logistic regression) 分析並比較各可能指標對隨後四年開始需要照護之預測能力。根據Wald值、勝算比、相對統計顯著度，建構量表題項與各題項之配分。再以接受操作特性曲線 (Receiver Operating Characteristic curve, ROC curve) 之曲線下面積 (area under curve, AUC) 比較各模組預測隨後四年開始需要照護的能力。
結果：年齡、身體功能、小腿圍、住院次數、自評健康、與配偶同住、共病、體重減輕等八項指標達到預測開始需要照護所採的統計標準，以此八項依各指標之預測能力建立最具預測能力的五題項、六題項和所有八題項的三模組。所建立的三模組皆具相當的預測能力，五、六、八題項量表的Nagelkerke R2 (NR2) 值，依次為0.238、0.243和0.246，ROC-AUC值為0.751、0.753和0.755。根據隨後四年開始需要照護之建議切點 (依三均等分範圍分為低、中、高需要照護風險)，在五、六、八題項量表的NR2值，依次為0.187、0.196和0.198，ROC-AUC值為0.693、0.692和0.697。以驗證樣本驗證的結果顯示，五、六、八題項量表的NR2值，依次為0.174、0.179和0.185，ROC-AUC值為0.681、0.681和0.688。
結論：依所採的統計標準有八項指標符合標準，被選為預測開始需要照護的題項。三模組包括五、六、所有八題項均對社區老人在四年內開始需要照護的風險，有可接受的預測能力。此量表將有助於老人的健康促進及老年生活規畫。
Background: Population aging is a worldwide phenomenon, but a tool to predict the new-onset care-need is not yet available.
Objective: The present study attempted to construct a scale to predict the new-onset care-need for older Taiwanese.
Methods: We analyzed the 1999 and 2003 datasets (total 2890 participants who aged ≥65 years old in 1999) of the “Taiwan Longitudinal Survey on Aging” (TLSA). After excluding 286 participants who required care at the baseline and 83 who were lost to follow-up, the rest of 2521 served as the sample of the present study. Based on physiological principles, available literatures, and availability of data in TLSA, we first identified the age, anthropometrics, physical functioning, mental status, social factors (living arrangement, social support, and economic status), medical indicators (hospitalization, emergency use, co-morbidities, and hearing and vision status), and global indicators (appetite, weight loss, and self-rated health) as the potential predictors of new-onset care-need. We used the total sample (2521 participants) to select the most predicable variables or items to new-onset care-need in each dimension. Then, we randomly selected 2017 (80%) from the 2521 participants to serve as training sample for developing the new-onset care-need scale, and the remaining 504 participants to serve as validating sample. We estimated the abilities of the potential indicators in predicting new-onset care-need during the subsequent 4 years using multivariable logistic regression analysis. We then constructed the predictive models and assigned proper scores to the items according to Wald values, odds ratios, and the relative statistical significance of the scale items. We used Receiver Operating Characteristics area under curves (ROC-AUC) to compare the predictive abilities of the constructed models.
Results: Three models including 5, 6, and 8 items, respectively, were constructed. The 8-item model includes all 8 items (age, physical functioning, calf circumference, hospitalization, self-rated health, living with spouse, co-morbidities, and weight loss) that met the pre-set statistical criteria for predicting new-onset care-need. All three models showed comparable predictive abilities; Nagelkerke R2 (NR2) values were 0.238, 0.243, and 0.246, and ROC-AUC values were 0.751, 0.753, and 0.755 for the 5-, 6-, and 8-item scales, respectively. Based on the proposed cut-offs (according to three equal ranges for low, moderate, and high risk) for the subsequent 4-year new-onset care-need, the NR2 values were 0.187, 0.196, and 0.198, and ROC-AUC values were 0.693, 0.692, and 0.697 for the 5-, 6-, and 8-item scales, respectively. Results from the validating sample confirmed the training sample; and the respective NR2 values were 0.174, 0.179, and 0.185, and the ROC-AUC values were 0.681, 0.681, and 0.688 for the 5-, 6-, and 8-item scales.
Conclusion: Eight indicators met the selection criteria and were used to construct three new-onset care-need predicting scales. The three scales contained 5-, 6-, and 8-items, respectively, and showed acceptable abilities in predicting new-onset care-need of community-living older adults. These scales should be useful for geriatric health promotion and for planning care-need and living arrangement of older adults.
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