Death as a multifactorial cumulative health event in older adults

描述(由申请人提供)： 在发达国家，大多数死亡发生在患有多种健康状况的70岁以上的人中。用目前的方法可能不能准确或完全地捕捉到这些多种情况对死亡的影响。主要的算法和判定方法可能具有误导性，既高估也低估了共存疾病和疾病的影响。现在是通过确定造成死亡的慢性和急性疾病的累积情况来补充现有死因确定方法的时候了。这个项目的两个Subaim是：1)检验假设，即多种慢性和急性疾病共同出现导致两个老年人队列中的死亡；以及2)确定这些疾病对死亡的影响程度(数量)。参与者是两个老年人纵向队列的成员。心血管健康研究(CHS)有5888名参与者，年龄在65岁以上，来自美国4个县。联邦医疗保险当前受益人研究(MCBS)包括在全国范围内抽样的65岁以上的代表性参与者。CHS和MCBS都收集了丰富的健康信息，包括慢性和急性情况以及生命状态。纳入时间依赖变量的比例风险模型(对于研究疾病的发生、发生和/或复发很重要)，将被用来推导有和没有特定条件的个人的死亡风险比率，同时控制其他条件(Subaim 1)。第二个Subaim扩展了确定每种情况导致死亡的程度的方法。分析的结果将是最终模型中每种条件对死亡的贡献量。个别情况可能会造成独立的影响，但也会导致死亡，这取决于其他情况的存在。使用创新的分析技术，我们将估计对这些条件的总贡献。一种反映导致死亡的多种情况的经验性方法应该会鼓励更明智的临床决策，以及更好地将研究和补偿资金与实际疾病负担相结合。随着婴儿潮一代步入晚年，对导致死亡的条件的准确估计对于健康和经济规划至关重要。

DESCRIPTION (provided by applicant): Description Most deaths in developed countries occur in persons over the age of 70 years who suffer from multiple health conditions. The contribution of these multiple conditions to death may not be accurately or completely captured with current methods. The predominant algorithmic, adjudication method approach may be misleading, both over- and under-estimating the contribution of co-existing diseases and conditions. It is time to complement existing methods for assigning cause of death by determining the cumulative chronic and acute conditions contributing to death. The two Subaims of this project are to: 1) test the hypothesis that multiple co-occurring chronic and acute conditions contributed to the deaths in two cohorts of older adults; and 2) determine the extent (amount) of the contribution of these conditions to the deaths. The participants are members of 2 longitudinal cohorts of older adults. The Cardiovascular Health Study (CHS) has 5,888 participants, age 65+ years from 4 U.S. counties. The Medicare Current Beneficiary Study (MCBS) includes representative participants age 65+ years sampled across the nation. Both CHS and MCBS collected a wealth of health information including chronic and acute conditions and vital status. Proportional hazards models, incorporating time-dependent variables (important for studying the onset, occurrence and/or reoccurrence of conditions), will be used to derive the ratio of the hazard of death for individuals with and without specific conditions, while controlling for the other conditions (Subaim 1). The second Subaim expands on methods for determining the extent to which each condition contributes to death. The product of the analyses will be the amount of contribution to death of each condition in the final model. Individual conditions likely will make an independent contribution but will also contribute to death dependent on the presence of other conditions. Using innovative analytical techniques we will estimate the total contribution attributed to the conditions. An empirically-derived method reflecting the multiple conditions contributing to death should encourage better informed clinical decision-making and better alignment of research and reimbursement dollars with actual disease burden. With baby boomers heading into their late years, accurate estimates of the conditions contributing to mortality are essential for health and economic planning.