Fixed Traits and Mortality at the Oldest Ages

描述(由申请人提供)：年龄最大的老年人是跑得最快的人之一 越来越多的人口，但我们对风险因素知之甚少 最高年龄的死亡率。只有几项研究考察了风险因素 对于85岁以上的人，没有人检查这些因素是否会增加 或在85-100岁的年龄范围内重要性下降。中国的死亡率模型 不同的种群表明死亡率的差异是如何在 个人可能会导致关于重要性下降的误导性结论 个人风险因素。拟议的研究将使用以下方法来研究这一问题 一个结合了三项调查信息的数据集：国家 纵向死亡率，健康和退休研究，以及AHEAD研究。 综合这些调查中对60岁及以上人群的观察结果， 提供足够大的样本，以详细检查相对风险 固定性状的比例会随着年龄而变化。合并后的数据集还包括 足够长的时间，可以检查风险的变化 在近20年的时间里，队列中的比率。该计划的目标是 研究是1)将调查合并到单个数据集，2)研究变化 在不同时期和队列中固定特征的相对风险随年龄增长而增加，3)比较 基于固定脆弱性的模型的相对风险变化，以及4)检验 基于两个或更多风险因素的模型。这些模型将被用于研究 种族/族裔、教育、婚姻状况的影响变化(从不 结婚)和出生地。

DESCRIPTION (provided by applicant): The oldest old are one of the fastest growing segments of the population, but we know little about the risk factors for mortality at the oldest ages. Only a few studies have examined risk factors for those over age of 85, and none have examined whether those factors increase or decrease in importance in the age range 85-100. Models of mortality in heterogeneous populations have shown how variation in mortality among individuals can lead to misleading conclusions about declines in the importance of individual risk factors. The proposed research will examine this issue using a data set that combines information from three surveys: the National Longitudinal Mortality, the Health and Retirement Study, and the AHEAD study. Combining the observations for persons aged 60 and over in these surveys will provide a sufficiently large sample to examine in detail how the relative risks of fixed traits change with age. The combined data set also covers a sufficiently long period that it will be possible to examine changes in risk ratios within cohorts over a period of almost 20 years. The aims of the research are to 1) combine the surveys into a single data set, 2) study changes over age in relative risks for fixed traits in periods and cohorts, 3) compare changes in relative risks with models based on fixed frailty, and 4) test models based on two or more risk factors. The models will be used to study changes in the effects of race/ethnicity, education, marital status (never married), and place of birth.