Background: Disparities in health outcomes among racial groups warrant investigation, even among elite athletes. Therefore, understanding the impact of race upon post-medal survival in Brazilian Olympians becomes essential.
Objective: To compare post-medal survival between white and non-white Brazilian Olympic medalists from 1920 to 1992.
Methods: This study used publicly available data for a retrospective cohort study on all Brazilian Olympic medalists from 1920 to 1992 (males only). Athletes were classified into white and non-white groups using structured ethnicity determination. Kaplan-Meier analyses computed the restricted mean survival time (RMST) for each ethnic group. A Cox proportional hazards analysis assessed ethnicity-based survival differences, adjusting for medal-winning age and birth year (p<0.05).
Results: Among 123 athletes (73.9% white), the mean age of medal achievement was 25.03±4.8 years. During the study, 18.7% of white and 37.5% of non-white athletes died (p=0.031). White athletes had a mean age at death of 75.10±18.01 years, while non-white athletes had an age of 67.13±14.90 years (p=0.109). The RMST for white athletes was 51.59 (95% CI 49.79-53.39) years, while for non-white athletes, it was 45.026 (95% CI 41.31-48.74) years, resulting in a ΔRMST of 6.56 (95% CI 2.43-10.70; p=0.0018). Multivariate analysis showed that non-white athletes had a higher mortality risk than did white athletes (HR 5.58; 95% CI, 2.18-14.31).
Conclusion: Following their first medal, white Brazilian Olympians typically enjoy a six-year longer lifespan than their non-white counterparts, illustrating a marked mortality gap and health disparities among healthy individuals in Brazil.
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http://dx.doi.org/10.36660/abc.20230524 | DOI Listing |
J Phys Act Health
January 2025
Department of Demography and Geodemography, Faculty of Science, Charles University, Prague, Czechia.
Objective: To determine the disparities in length of live and age-specific probabilities of death of US Olympians by sex, performance level, and age at debut at the Olympics.
Methods: We apply parametric models of mortality to estimate probabilities of death by age. The best performing model (Gompertz model) is then used to calculate life tables for subpopulations of Olympians.
Sensors (Basel)
November 2024
Department of Environmental and Bioscience, School of Business, Innovation and Sustainability, Halmstad University, 30118 Halmstad, Sweden.
Exp Physiol
November 2024
Division of Natural Sciences, Pepperdine University, Malibu, California, USA.
Less than 7% of the world's population live at an altitude above 1500 m. Yet, as many as 67% of medalists in the 2020 men's and women's Olympic marathon, and 100% of medalists in the 2020 men's and women's Olympic 5000 m track race may have been born or raised above this otherwise rare threshold. As a possible explanation, research spanning nearly a quarter of a century demonstrates that indigenous highlanders exhibit pulmonary adaptations distinct from their lowland counterparts.
View Article and Find Full Text PDFInt J Mol Sci
November 2024
Szentágothai Research Center, University of Pécs, 7622 Pécs, Hungary.
Competitive athletes are often exposed to extreme physiological loading, resulting in over excessive mechanotransduction during their acute intensive training sessions and competitions. Individual differences in their genetics often affect how they cope with these challenges, as reflected in their high performances. Olympic Medalists are prohibited from providing atypical values in the Hematological Module of the Athlete Biological Passport.
View Article and Find Full Text PDFSports (Basel)
August 2024
Faculty of Kinesiology, University of Split, N. Tesle 6, 21000 Split, Croatia.
This research aimed to propose a new methodological approach for analyzing relative age effect (RAE) in different sports or samples named "Relative age effect overall scale" (RAEOS). The sample consisted of 1455 male and female young athletes who competed in four different sports (basketball, = 159; handball, = 215; swimming, = 981; taekwondo, = 100) at the Youth Olympic Games (YOG) in Buenos Aires in 2018. To construct the new model, the sample was classified into four unified quartiles of a specific range depending on the sport (swimming: 48-month range, taekwondo: 24-month range, and basketball and handball: 36-month range).
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