Department of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado, Aurora, CO.
Department of Biostatistics, School of Medicine, Virginia Commonwealth University, Richmond, VA.
Med Sci Sports Exerc. 2024 Oct 1;56(10):1926-1934. doi: 10.1249/MSS.0000000000003497. Epub 2024 Jul 1.
Objectively measured physical activity (PA) is a modifiable risk factor for mortality. Understanding the predictive performance of PA is essential to establish potential targets for early intervention to reduce mortality among older adults.
The study used a subset of the National Health and Nutrition Examination Survey (NHANES) 2011-2014 data consisting of participants 50 to 80 yr old ( n = 3653, 24297.5 person-years of follow-up, 416 deaths). Eight accelerometry-derived features and 14 traditional predictors of all-cause mortality were compared and ranked in terms of their individual and combined predictive performance using the 10-fold cross-validated concordance (C) from Cox regression.
The top 3 predictors of mortality in univariate analysis were PA related: average Monitor-Independent Movement Summary (MIMS) in the 10 most active hours (C = 0.697), total MIMS per day (C = 0.686), and average log-transformed MIMS in the most 10 active hours of the day (C = 0.684), outperforming age (C = 0.676) and other traditional predictors of mortality. In multivariate regression, adding objectively measured PA to the top performing model without PA variables increased concordance from C = 0.776 to C = 0.790 ( P < 0.001).
These findings highlight the importance of PA as a risk marker of mortality and are consistent with prior studies, confirming the importance of accelerometer-derived activity measures beyond total volume.
客观测量的身体活动(PA)是死亡率的可改变风险因素。了解 PA 的预测性能对于确定潜在的早期干预目标以降低老年人的死亡率至关重要。
本研究使用了 2011-2014 年国家健康和营养检查调查(NHANES)数据的一个子集,其中包括 50 至 80 岁的参与者(n=3653,24297.5 人年随访,416 例死亡)。使用 Cox 回归的 10 折交叉验证一致性(C)比较并排名了 8 个加速度计衍生特征和 14 个全因死亡率的传统预测因素,就其个体和综合预测性能而言。
单变量分析中死亡率的前 3 个预测因素与 PA 相关:10 小时最活跃时间内的平均监测独立运动摘要(MIMS)(C=0.697)、每天的总 MIMS(C=0.686)和白天最活跃的 10 小时内的平均对数转换的 MIMS(C=0.684),优于年龄(C=0.676)和其他死亡率的传统预测因素。在多变量回归中,将客观测量的 PA 添加到没有 PA 变量的表现最佳模型中,一致性从 C=0.776 提高到 C=0.790(P<0.001)。
这些发现强调了 PA 作为死亡率风险标志物的重要性,与先前的研究一致,证实了加速度计衍生活动测量的重要性,超过了总容量。