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Collaborative Research: Factors Affecting Ethnic Differences in Adult Mortality

Collaborative Research: Factors Affecting Ethnic Differences in Adult Mortality
合作研究:影响成人死亡率种族差异的因素
批准号:
9617905
负责人:
Richard Rogers
金额:
$7.31万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
1997
资助国家:
美国
项目状态:
已结题
起止时间:
1997-04-01 至 2000-03-31

项目摘要

项目成果

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中文摘要
翻译
这是一项关于成年人死亡率种族差异的研究。 它将采用人口学概念和方法来实现三个主要的研究目标,无论是对特定原因和多原因死亡率。 首先,它将开发一个比迄今为止提出的更全面的模型,将危险因素与种族死亡率差异联系起来。 第二,这项工作将扩大死亡率研究中常见的族裔类别的范围。 第三,它将采用一个独特的数据库,将详细的人口统计、社会经济、家庭结构、健康和行为因素与种族群体的死亡率联系起来。 该项目的具体目标是:(1)收集和调整一个完整的、前瞻性的数据库,以便在按死因分析成人死亡率的种族差异时,同时检查人口和社会经济背景因素、家庭结构、健康行为和健康史因素。(2)扩大了死亡率研究中通常发现的种族类别的范围,包括墨西哥人、土著人、非洲人、亚洲人和高加索美国人。(3)揭示为什么一些种族群体,特别是非洲裔美国人,经历相对较高的循环系统疾病死亡风险。(4)揭示为什么非裔美国人遭受不成比例的癌症死亡率高。(5)说明为什么呼吸系统疾病的死亡率在白人美国人中不成比例地高。(6)解释为什么墨西哥人、原住民和非洲裔美国人的糖尿病死亡率相对较高。(7)说明为什么墨西哥人,原住民和非洲裔美国人死于社会病理学的比率相对较高。(8)扩展死因分析,以包括潜在和多种死因。(9)说明按性别和年龄组分列的族裔死亡率模式的差异。(10)使用连续时间风险率模型,该模型允许按种族群体对死亡风险进行多变量检查。 在美国长期存在的种族死亡率差异是一个令人不安和具有挑战性的问题。虽然各群体之间的死亡率差异不断得到更好的记录,特别是非洲裔和高加索裔美国人之间的差异,但对差异的解释一直很弱,特别是在比较众多族裔群体时。例如,人们对墨西哥裔美国人的死亡率知之甚少,以至于他们有利的死亡率常常被称为“流行病学悖论”。“关于亚洲人和美洲原住民所表现出的不同死亡原因模式,人们所知更少。因此,本研究的主要目的是解释原因特异性死亡率的种族差异,使用一个模型,将人口统计学,社会经济学,家庭结构,行为和健康史因素与潜在和多原因死亡率差异联系起来。 一个更全面、更具体的模型将更容易确定社会项目、公共政策、医疗和未来研究可以产生最有益影响的关键领域。
英文摘要
This is a study of ethnic differences in adult mortality. It will employ demographic conceptual and methodological approaches to accomplish three main research goals both for cause-specific and multiple-cause mortality. First, it will develop a more comprehensive model relating risk factors to ethnic mortality differentials than has heretofore been presented. Second, the work will broaden the range of ethnic categories typically found in mortality studies. Third, it will employ a unique data base that links detailed demographic, socioeconomic, family structure, health, and behavioral factors to mortality of ethnic groups. The specific aims of the project are to: (1) Assemble and adapt an integral, prospective database that will permit simultaneous examination of demographic and socioeconomic background factors, family structure, health behaviors, and health history factors in an analysis of ethnic variations in adult mortality by cause of death. (2) Broaden the range of ethnic categories typically found in mortality studies to include Mexican, Native, African, Asian, and Caucasian Americans. (3) Uncover why some ethnic groups, notably African Americans, experience relatively high mortality risk from circulatory diseases. (4) Reveal why African Americans suffer disproportionately high rates of cancer mortality. (5) Show why respiratory disease mortality is disproportionately high among Caucasian Americans. (6) Illuminate why Mexican, Native, and African Americans exhibit relatively high rates of diabetes mortality. (7) Illustrate why Mexican, Native, and African Americans die at relatively high rates from social pathologies. (8) Extend the cause of death analysis to include both underlying and multiple causes of death. (9) Account for variations in ethnic mortality patterns by sex and age groupings. (10) Use continuous-time hazard rate models, which allow a multivariate examination of the risk of death by ethnic group. The ethnic differences in mortality that have so long persisted i n the U.S. represent a troubling and challenging question. While mortality differences between groups are continually better-documented, particularly between African and Caucasian Americans, the explanation of differences has been weak, particularly when numerous ethnic groups are compared. For example, so little is known about Mexican American mortality that their favorable mortality rates are often termed an "epidemiological paradox." Even less is known about the differing cause patterns of death exhibited by Asian and Native Americans. Thus, the principal purpose of this research is to explain ethnic differences in cause-specific mortality, using a model that relates demographic, socioeconomic, family structure, behavioral, and health history factors to both underlying and multiple cause mortality differentials. A more comprehensive and more specific model will make it easier to identify key areas where social programs, public policy, medical treatment, and future research can have the most beneficial effects.
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会议论文
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