Baseball and basketball players who peak early, die early: Oxford research

Baseball and basketball players, whose athletic skills peaked earlier or declined faster, had significantly shorter lifespans, according to an innovative study by Dr Saul Newman from Oxford’s Leverhulme Centre for Demographic Science published today in Science Advances.

Dr Newman probed data on athlete’s height, weight and performance and studied the data on all-time great baseball players, such as Willie Mays, Yogi Berra and Sugar Cain. He found, 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.

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 who peaked early had mortality rates double every 8.4 years of age with their odds of death increased with age more slowly, potentially indicating slower rates of ageing despite a shorter lifespan.

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. Also, the study found, athletes whose athletic skill declined at different rates also had very different mortality rates. This gap in mortality rates persisted for at least 40 years post-retirement.

An 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.
The study figure attached, for example, shows how the batting averages for Willie Mays, Yogi Berra, and Sugar Cain peaked at different ages and subsequently declined with age. This and other findings from the study suggest athletes have a single peak in overall performance instead of having different peaks at different ages.

The graph attached captures early-life peaks and rates of decline in athletic performance for batting average. Yogi Berra and Willie Mays have the same rate of decline in batting average, 2% of peak capacity per year, while Sugar Cain’s batting average decays at 12% per year. Sugar Cain passed away at 67 and Yogi Berra at 90 whilst Willie Mays is still alive at the age of 92.

Dr Newman explains, ‘We know reaction times, motor functions, aerobic and anaerobic performance all decline with the onset of ageing. However, little is known about the effect of early-life physiological decline on mortality. With this study, I hoped to gain insights on this link by examining unique and rich historical data from elite athletes, which capture the early-life physical capacity of a unique group of people.’

He concludes, ‘This study finds that data on early-life athletic performance can be used to predict late-life mortality and ageing in elite male athletes. A rise in wearable technologies provides an exciting opportunity to test this link in wider populations who now have activity data like that of elite athletes at their fingertips.’

According to the study, ‘The long-term predictive value of early life athletic patterns remains an exciting result drawn from a unique large cohort with an extraordinary follow-up time, extensive standardised physical measurements, and a high level of data accuracy and completeness. Early-life declines in athletic performance allow late-life mortality to be predicted better than age alone and have comparable predictive power to early-life BMI and height.’

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.

Analysis of these results ruled out some potential causes for these mortality rate differences. As almost half of the baseball sample size pre-dated 1947, when non-white players were excluded from major league baseball, the study was able to explore whether race and racism shortened players careers and lifespans. While racism likely plays a role in shortening careers and lives, effects observed in the study could not be explained by racism alone: considerable effect sizes were observed in both segregated and non-segregated leagues.

Whilst 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 this link is translatable to the wider population.