Leverhulme Centre for Demographic Science, University of Oxford, Oxford, UK.
The Research School of Biology, Australian National University, Canberra, ACT, Australia.
Sci Adv. 2023 May 19;9(20):eadf1294. doi: 10.1126/sciadv.adf1294.
Athleticism and the mortality rates begin a lifelong trajectory of decline during early adulthood. Because of the substantial follow-up time required, however, observing any longitudinal link between early-life physical declines and late-life mortality and aging remains largely inaccessible. Here, we use longitudinal data on elite athletes to reveal how early-life athletic performance predicts late-life mortality and aging in healthy male populations. Using data on over 10,000 baseball and basketball players, we calculate age at peak athleticism and rates of decline in athletic performance to predict late-life mortality patterns. Predictive capacity of these variables persists for decades after retirement, displays large effect sizes, and is independent of birth month, cohort, body mass index, and height. Furthermore, a nonparametric cohort-matching approach suggests that these mortality rate differences are associated with differential aging rates, not just extrinsic mortality. These results highlight the capacity of athletic data to predict late-life mortality, even across periods of substantial social and medical change.
运动能力和死亡率在成年早期开始呈现出终身下降的轨迹。然而，由于需要大量的随访时间，观察早期身体衰退与晚年死亡率和衰老之间的任何纵向联系在很大程度上仍然难以实现。在这里，我们使用关于精英运动员的纵向数据来揭示年轻时的运动表现如何预测健康男性人群晚年的死亡率和衰老。我们利用超过 10000 名棒球和篮球运动员的数据，计算出达到运动巅峰状态的年龄和运动表现下降的速度，以预测晚年的死亡率模式。这些变量的预测能力在退役后持续数十年，具有较大的效应量，并且与出生月份、队列、体重指数和身高无关。此外，一种非参数队列匹配方法表明，这些死亡率差异与衰老率的差异有关，而不仅仅是外在的死亡率。这些结果强调了运动数据预测晚年死亡率的能力，即使在社会和医疗发生重大变化的时期也是如此。
