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美国的疾病负担——过去、现在与未来。

U.S. burden of disease--past, present and future.

作者信息

McKenna Matthew T, Zohrabian Armineh

机构信息

Office on Smoking and Health, Centers for Disease Control and Prevention, USA.

出版信息

Ann Epidemiol. 2009 Mar;19(3):212-9. doi: 10.1016/j.annepidem.2008.11.005.

Abstract

PURPOSE

To review the history and challenges of "burden of disease" studies, how these are dependent on robust epidemiologic data as well as complex conceptual constructions, and to identify the public health policy issues these studies can most usefully inform.

METHODS

The emergence of the concept of the "burden of disease" in the public health literature is reviewed, with a focus on the results of an analysis of data from the United States that used the methodology presented in the Global Burden of Disease Study.

RESULTS

The systematic analysis of public health mortality data to identify major health problems was conducted by Graunt in 16th-century London. He found that many of the predominant sources of mortality were not the focus of public attention. Today, despite refinements in epidemiologic measurement methods designed to capture the impact of non-fatal health conditions, there are similar incongruities between the major public health problems and expenditures on prevention interventions.

CONCLUSIONS

Controversies surrounding the interpretation of "burden of disease" studies are not new. Particularly in developed countries, these studies appear more useful for setting research priorities rather than allocating resources to support prevention efforts. Such investigations are not possible without ongoing support for systematic collection and analysis of descriptive epidemiologic data.

摘要

目的

回顾“疾病负担”研究的历史与挑战,探讨其如何依赖可靠的流行病学数据以及复杂的概念构建,并确定这些研究能最有效提供信息的公共卫生政策问题。

方法

回顾公共卫生文献中“疾病负担”概念的出现,重点关注一项使用《全球疾病负担研究》中提出的方法对美国数据进行分析的结果。

结果

16世纪伦敦的格兰特对公共卫生死亡率数据进行了系统分析,以确定主要的健康问题。他发现,许多主要的死亡原因并非公众关注的焦点。如今,尽管旨在捕捉非致命健康状况影响的流行病学测量方法有所改进,但主要的公共卫生问题与预防干预措施的支出之间仍存在类似的不一致。

结论

围绕“疾病负担”研究解释的争议并非新鲜事。特别是在发达国家,这些研究似乎在确定研究重点方面比为支持预防工作分配资源更有用。如果没有对描述性流行病学数据的系统收集和分析提供持续支持,此类调查是不可能进行的。

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