Login / Signup

Do "big guys" really die younger? An examination of height and lifespan in former professional basketball players.

Srdjan LemezNick WattieJoseph Baker
Published in: PloS one (2017)
While factors such as genetics may mediate the relationship between height and mortality, evidence suggests that larger body size may be an important risk indicator of reduced lifespan longevity in particular. This study critically examined this relationship in professional basketball players. We examined living and deceased players who have played in the National Basketball Association (debut between 1946-2010) and/or the American Basketball Association (1967-1976) using descriptive and Kaplan-Meier and Cox regression analyses. The cut-off date for death data collection was December 11, 2015. Overall, 3,901 living and deceased players were identified and had a mean height of 197.78 cm (± 9.29, Range: 160.02-231.14), and of those, 787 former players were identified as deceased with a mean height of 193.88 cm (± 8.83, Range: 167.6-228.6). Descriptive findings indicated that the tallest players (top 5%) died younger than the shortest players (bottom 5%) in all but one birth decade (1941-1950). Similarly, survival analyses showed a significant relationship between height and lifespan longevity when both dichotomizing [χ2 (1) = 13.04, p < .05] and trichotomizing [χ2 (2) = 18.05, p < .05] the predictor variable height per birth decade, where taller players had a significantly higher mortality risk compared to shorter players through median (HR: 1.30, 95% CI: 1.13-1.50, p < .05) and trichotomized tertile split (HR: 1.40, 95% CI: 1.18-1.68, p <. 05; tallest 33.3% compared to shortest 33.3%) analyses. The uniqueness of examining the height-longevity hypothesis in this relatively homogeneous sub-population should be considered when interpreting these results. Further understanding of the potential risks of early mortality can help generate discourse regarding potential at-risk cohorts of the athlete population.
Keyphrases
  • body mass index
  • cardiovascular events
  • type diabetes
  • big data
  • human health
  • cross sectional
  • machine learning