背景：全球人口老化現象逐漸增加，老人生活品質一直是研究的重點。跨國研究比較不同國
家老人的生活品質型態，可以增進對老人的瞭解。
目的：本研究主要的目的在探討英國與台灣老人的生活品質型態，以及生活品質型態與死亡
風險的關係。
方法：資料來源包括英國1989年的諾丁漢老人活動縱貫性研究，以及台灣地區1989年中老年
身心社會生活狀況長期追蹤調查。本研究使用集群分析觀察英國及台灣老人的生活品 質型態和特性，然後以存活分析比較英國及台灣老人生活品質型態與死亡風險之間的 關係。
結果：集群分析出英國老人樣本15個分群，台灣老人樣本20個分群。以英國的15個分群及台
灣的20個分群進行存活分析結果，老人生活品質的型態與14年的死亡風險有明顯的關 係。
結論：本研究使用集群分析認定英國及台灣老人在生活品質上的不同層級及特性，最重要的
是探索老人在生活品質上的不同層級及特性與存活率之間的關係，因為從生活品質上 的不同層級及特性，可以發現生活品質的某些因素會增加死亡風險。

Background: As the numbers and proportions of elderly people in the global population increase, quality of life (QOL) within this group becomes an important research issue. Undertaking crossnational comparisons of elderly people can provide a better understanding of QOL patterns.
Purpose: This study examines QOL patterns using a harmonization data set from two longitudinal studies of the older people in the United Kingdom (UK) and Taiwan and explores the relationship between clusters of older people and mortality hazards in these countries.
Methods: Data were derived 什om the 1989 wave of the Nottingham Longitudinal Study of Activity and Ageing and the Survey of Health and Living Status of the Elderly in Taiwan. Cluster analysis was used to observe QOL patterns in the older people and their profiles. Cox regression analysis was used to test for the presence of clusters associated with mortality hazards.
Result: Fifteen subgroups were extracted from cluster analysis of the Nottingham Longitudinal Study of Activity and Ageing sample (n = 690), and 20 groups were generated from cluster analysis of the Survey of Health and Living Status of the Elderly in Taiwan data set (n = 1,438). Cox regression analyses revealed a relationship between mortality risk and certain clusters over a 14-year period in the UKand Taiwan.
Conclusions: Using cluster analyses to group the older people according to shared characteristics identified different QOL levels across these profiles both in the UK and Taiwan. The author also identified differences in the same profile levels between the two countries. It is important to explore the relationship between clusters and mortality hazards because clusters reflect important QOL factors affecting mortality risk.