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人群中特定慢性病的消除:发病的压缩与扩展。

The elimination of selected chronic diseases in a population: the compression and expansion of morbidity.

作者信息

Nusselder W J, van der Velden K, van Sonsbeek J L, Lenior M E, van den Bos G A

机构信息

Netherlands Institute for Primary Health Care, Utrecht, The Netherlands.

出版信息

Am J Public Health. 1996 Feb;86(2):187-94. doi: 10.2105/ajph.86.2.187.

Abstract

OBJECTIVES

This study evaluates the effect of eliminating a specific disease on the mortality, long-term disability, and overall health status of a population. Primarily, it examines whether elimination leads to a compression of morbidity.

METHODS

The Sullivan method was used to calculate disability-free life expectancy. Cause-deleted disability prevalence was estimated with a multiple logistic regression model that used data from the Dutch National Survey of General Practice. Cause-deleted probabilities of dying were derived with the cause-elimination life-table technique, assuming independence among competing causes of death.

RESULTS

Eliminating disabling nonfatal diseases such as arthritis/back complaints results in a decline in life expectancy with disability--that is, an absolute compression of morbidity. Eliminating highly fatal diseases such as cancer leads to an increase in the number of years and the proportion of life with disability--that is, a relative expansion of morbidity.

CONCLUSIONS

While eliminating fatal diseases leads to an increase in disability-free life expectancy, life expectancy with disability may increase as well. This represents an increasing burden to society. On the other hand, eliminating nonfatal disabling diseases leads to absolute compression of morbidity.

摘要

目的

本研究评估消除特定疾病对人群死亡率、长期残疾和总体健康状况的影响。主要研究消除疾病是否会导致发病期的压缩。

方法

采用沙利文方法计算无残疾预期寿命。使用来自荷兰国家全科医学调查的数据,通过多元逻辑回归模型估计病因消除后的残疾患病率。采用病因消除生命表技术,假设死亡的竞争原因之间相互独立,得出病因消除后的死亡概率。

结果

消除致残性非致命疾病(如关节炎/背部疾病)会导致有残疾的预期寿命下降,即发病期的绝对压缩。消除高度致命疾病(如癌症)会导致残疾年限和残疾生活比例增加,即发病期的相对延长。

结论

虽然消除致命疾病会导致无残疾预期寿命增加,但有残疾的预期寿命也可能增加。这给社会带来了越来越大的负担。另一方面,消除非致命致残疾病会导致发病期的绝对压缩。

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The compression of morbidity.发病压缩
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