An innovative study by Dr Saul Newman of the Leverhulme Centre for Demographic Science finds that baseball and basketball players whose athletic skills peaked earlier or declined faster had significantly shorter lifespans.
Those who peaked earlier had a 1.2 year shorter adult life expectancy while those who maintained athletic performance for longer had an 0.8 year higher life expectancy.
The study used data spanning 150 years from 24,000 US male baseball and basketball players to calculate age at peak athleticism and rates of decline in athletic performance to predict late-life mortality patterns.
Data on the athletes’ height, Body Mass Index (BMI), and performance metrics, such as the batting average for baseball players and number of points scored by a basketball player per game, were used to calculate age at peak performance and the rate of decline for each athletic skill.
Athletes who peaked at an earlier age and maintained athletic performance for a shorter period than their counterparts had a significantly shorter lifespan than those who peaked later and maintained athletic performance for longer.
These differences had surprising and complex links to ageing. Athletes who peaked at different ages, or whose skills declined at different rates, also seemed to age at different rates. Those who peaked later had mortality rates that doubled every 7.6 years of age. Athletes that peaked early had mortality rates double every 8.4 years of age while their odds of death increased with age more slowly, potentially indicating slower rates of aging despite a shorter lifespan.
A further, more unexpected, finding was a positive association between height and late-life mortality rates in baseball and basketball players, meaning taller athletes were more likely to die earlier.
While this study highlights the capacity of athletic data to predict late-life mortality in male elite athletes in the United States, more research is needed to explore this link in female elite athletes, and to determine whether the link is translatable to the wider population.
Dr Newman concluded that the paper provides some exciting possibilities for future research:
The magnitude and unexpected time span of these results reveal an exciting prospect for the study of huge cohorts of individuals now tracking their own longitudinal changes in health through connected electronic devices.
Smart phones, watches, and wearables are currently capturing detail on the athletic capacity of ordinary people, at an unprecedented level of detail that eclipses the historical records of even the most elite athletes.
If early-life athleticism is also predictive of late-life mortality in the general population, then the value of wearables data in predicting mortality rates would extend far beyond the necessarily short time horizon and limited contexts that are currently accessible to testing.
Read more about the study here.
