Background Although biological aging has been proposed as a more accurate measure of aging, few biological aging measures have been developed for Asians, especially for young adults. Methods A total of 521,656 participants were enrolled in the MJ cohort (1996 -2011) and were followed until death, loss-to-follow-up, or Dec 31, 2011, whichever came first. We selected 14 clinical biomarkers including chronological age using random forest algorithm and developed a multi-dimensional aging measure (MDAge). Model performance was assessed by area under the curve (AUC) and internal calibration. We evaluated the associations of MDAge and residuals from regressing MDAge on chronological age (MDAgeAccel) with mortality and morbidity, and assessed the robustness of our findings. Results MDAge achieved an excellent AUC of 0.892 in predicting all-cause mortality (95% confidence interval [CI]: 0.889-0.894). Participants with higher MDAge at baseline were at a higher risk of death (per 5 years, HR=1.671, 95%CI: 1.662–1.680), and the association remained after controlling for other variables and in different subgroups. Furthermore, participants with higher MDAgeAccel were associated with shortened life expectancy. For instance, compared to men who were biologically younger (MDAgeAccel≤0) at baseline, men in the highest tertiles of MDAgeAccel had shortened life expectancy by 17.23 years. In addition, higher MDAgeAccel was associated with having chronic disease either cross-sectionally (per 1-SD, OR=1.564, 95%CI: 1.552-1.575) or longitudinally (per 1-SD, OR=1.218, 95% CI: 1.199-1.238). Conclusions MDAge accurately predicted mortality and morbidity, which has great potential in the early identification of individuals at higher risk, and therefore promoting early intervention.

中文翻译：

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开发一种新的多维老化测量方法来预测前瞻性 MJ 队列中的死亡率和发病率

背景 尽管生物衰老被提议作为更准确的衰老测量方法，但很少有针对亚洲人，尤其是年轻人开发的生物学衰老测量方法。方法 共有 521,656 名参与者被纳入 MJ 队列 (1996 -2011)，并被随访至死亡、失访或 2011 年 12 月 31 日，以先到者为准。我们使用随机森林算法选择了 14 种临床生物标志物，包括实足年龄，并开发了多维老化测量 (MDAge)。模型性能通过曲线下面积 (AUC) 和内部校准进行评估。我们评估了 MDAge 和实足年龄回归 MDAge 残差 (MDAgeAccel) 与死亡率和发病率的关联，并评估了我们研究结果的稳健性。结果 MDAge 实现了出色的 AUC 0。892 预测全因死亡率（95% 置信区间 [CI]：0.889-0.894）。基线时 MDAage 较高的参与者死亡风险较高（每 5 年，HR=1.671，95%CI：1.662–1.680），并且在控制其他变量和不同亚组后，这种关联仍然存在。此外，具有较高 MDAgeAccel 的参与者与预期寿命缩短有关。例如，与基线时生物学上更年轻 (MDAgeAccel≤0) 的男性相比，处于 MDAgeAccel 最高三分位数的男性的预期寿命缩短了 17.23 年。此外，较高的 MDAgeAccel 与横断面（每 1-SD，OR=1.564，95%CI：1.552-1.575）或纵向（每 1-SD，OR=1.218，95%CI：1.199）慢性病相关-1.238）。结论 MDAge 准确预测死亡率和发病率，