Missing data approaches in longitudinal studies of aging: A case example using the National Health and Aging Trends Study.
Missing data approaches in longitudinal studies of aging: A case example using the National Health and Aging Trends Study.
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DOI：
10.1371/journal.pone.0286984
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发表时间：
2023
期刊：
影响因子：
3.7
通讯作者：
中科院分区：
文献类型：
--
作者：
缺失数据是老龄化纵向研究中的一个关键方法学考虑因素。我们描述了缺失数据的挑战和潜在的方法解决方案，使用一个描述老年人队列中五年虚弱状态转变的案例。我们使用了来自国家健康和老龄化趋势研究的纵向数据，这是一个具有全国代表性的医疗保险受益人队列。我们评估了Fried虚弱表型的五个组成部分，并根据其组成部分的数量对虚弱进行分类（健壮：0，虚弱前期：1-2，虚弱：3-5）。一年、两年和五年的虚弱状态转换被定义为虚弱状态或死亡之间的运动。使用热板插补对缺失的脆弱性组件进行插补。使用逆概率权重来解释潜在的信息性失访。我们进行了情景分析，以测试与缺失数据相关的一系列假设。缺失数据常见于使用身体评估（步行速度、握力）测量的虚弱部分。在5年时，36%的个体失访，与基线虚弱状态相比存在差异。缺失数据机制的假设影响了关于个体虚弱改善或恶化的推断。数据缺失和失访在老龄化纵向研究中很常见。强有力的流行病学方法可以提高老龄化相关研究的严谨性和可解释性。
Missing data is a key methodological consideration in longitudinal studies of aging. We described missing data challenges and potential methodological solutions using a case example describing five-year frailty state transitions in a cohort of older adults. We used longitudinal data from the National Health and Aging Trends Study, a nationally-representative cohort of Medicare beneficiaries. We assessed the five components of the Fried frailty phenotype and classified frailty based on their number of components (robust: 0, prefrail: 1–2, frail: 3–5). One-, two-, and five-year frailty state transitions were defined as movements between frailty states or death. Missing frailty components were imputed using hot deck imputation. Inverse probability weights were used to account for potentially informative loss-to-follow-up. We conducted scenario analyses to test a range of assumptions related to missing data. Missing data were common for frailty components measured using physical assessments (walking speed, grip strength). At five years, 36% of individuals were lost-to-follow-up, differentially with respect to baseline frailty status. Assumptions for missing data mechanisms impacted inference regarding individuals improving or worsening in frailty. Missing data and loss-to-follow-up are common in longitudinal studies of aging. Robust epidemiologic methods can improve the rigor and interpretability of aging-related research.
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影响因子：
0.9
作者：
Kaufman, Sol;Kaufman, Jay S.;MacLehose, Richard F.
通讯作者：
MacLehose, Richard F.
影响因子：
6.3
作者：
Pollack LR;Litwack-Harrison S;Cawthon PM;Ensrud K;Lane NE;Barrett-Connor E;Dam TT
通讯作者：
Dam TT
DOI：
10.7326/0003-4819-139-5_part_2-200309021-00007
发表时间：
2003-09-02
影响因子：
39.2
作者：
Diehr, P;Patrick, DL
通讯作者：
Patrick, DL
影响因子：
5.6
作者：
Li, Chih-Ying;Al Snih, Soham;Ottenbacher, Kenneth J.
通讯作者：
Ottenbacher, Kenneth J.
影响因子：
5
作者：
Cole, Stephen R.;Lau, Bryan;Mugavero, Michael J.
通讯作者：
Mugavero, Michael J.