Data_Sheet_1_Predictive Utility of Mortality by Aging Measures at Different Hierarchical Levels and the Response to Modifiable Life Style Factors: Implications for Geroprotective Programs.docx

BackgroundAging, as a multi-dimensional process, can be measured at different hierarchical levels including biological, phenotypic, and functional levels. The aims of this study were to: (1) compare the predictive utility of mortality by three aging measures at three hierarchical levels; (2) develop a composite aging measure that integrated aging measures at different hierarchical levels; and (3) evaluate the response of these aging measures to modifiable life style factors.
MethodsData from National Health and Nutrition Examination Survey 1999–2002 were used. Three aging measures included telomere length (TL, biological level), Phenotypic Age (PA, phenotypic level), and frailty index (FI, functional level). Mortality information was collected until December 2015. Cox proportional hazards regression and multiple linear regression models were performed.
ResultsA total of 3,249 participants (20–84 years) were included. Both accelerations (accounting for chronological age) of PA and FI were significantly associated with mortality, with HRs of 1.67 [95% confidence interval (CI) = 1.41–1.98] and 1.59 (95% CI = 1.35–1.87), respectively, while that of TL showed non-significant associations. We thus developed a new composite aging measure (named PC1) integrating the accelerations of PA and FI, and demonstrated its better predictive utility relative to each single aging measure. PC1, as well as the accelerations of PA and FI, were responsive to several life style factors including smoking status, body mass index, alcohol consumption, and leisure-time physical activity.
ConclusionThis study demonstrates that both phenotypic (i.e., PA) and functional (i.e., FI) aging measures can capture mortality risk and respond to modifiable life style factors, despite their inherent differences. Furthermore, the PC1 that integrated phenotypic and functional aging measures outperforms in predicting mortality risk in comparison with each single aging measure, and strongly responds to modifiable life style factors. The findings suggest the complementary of aging measures at different hierarchical levels and highlight the potential of life style-targeted interventions as geroprotective programs.

背景 衰老是一个多维度的过程，可在生物学、表型与功能等不同层级水平进行测量。本研究的目标为：(1) 对比三种不同层级衰老指标对死亡风险的预测效能；(2) 构建一种整合不同层级衰老指标的复合衰老指标；(3) 评估上述衰老指标对可改变生活方式因素的响应情况。
方法 本研究使用了1999-2002年美国国家健康与营养调查（National Health and Nutrition Examination Survey, NHANES）的数据。三种衰老指标分别为端粒长度（telomere length, TL，生物学层面）、表型年龄（Phenotypic Age, PA，表型层面）以及衰弱指数（frailty index, FI，功能层面）。死亡率随访数据截至2015年12月。本研究采用Cox比例风险回归与多元线性回归模型开展分析。
结果 本研究共纳入3249名年龄介于20至84岁的参与者。在校正实际年龄后，PA与FI的衰老加速程度均与死亡风险存在显著关联，其风险比（HR）分别为1.67 [95%置信区间（confidence interval, CI）=1.41–1.98]与1.59（95% CI=1.35–1.87）；而TL的衰老加速程度与死亡风险无显著关联。据此，我们构建了一种整合PA与FI衰老加速程度的新型复合衰老指标（命名为PC1），并证实其相较于单一衰老指标具备更优的死亡风险预测效能。PC1以及PA、FI的衰老加速程度均对多种可改变生活方式因素存在响应，包括吸烟状态、体重指数、饮酒情况以及闲暇时间体力活动。
结论 本研究表明，尽管表型衰老指标（即PA）与功能衰老指标（即FI）存在固有差异，但二者均能有效捕捉死亡风险，并对可改变的生活方式因素产生响应。此外，整合表型与功能衰老指标的PC1相较于单一衰老指标，在死亡风险预测效能上更突出，且对可改变生活方式因素具有强烈响应。本研究结果提示不同层级衰老指标具有互补性，并凸显了以生活方式为靶点的干预措施作为老年保护方案的潜力。