Career-Span Analyses of Track Performance: Longitudinal Data Present a More Optimistic View of Age-Related Performance Decline

Sport scientists (Starkes, Weir, Singh, Hodges, & Kerr, 1999; Starkes, Weir, & Young, 2003) have suggested that prolonged training is critical for the maintenance of athletic performance even in the face of predicted age-related decline. This study used polynomial regression analyses to examine the relationship between age and running performance in the 1500 and 10,000 metre events. We compared the age and career-longitudinal performances for 15 male Canadian Masters athletes with a cross-sectional sample of performances at different ages. We hypothesized that the 30 years of uninterrupted training characteristic of this longitudinal sample would moderate the patterns of age-related decline (retention hypothesis); alternatively, the cross-sectional data were expected to demonstrate pronounced age-related decline (quadratic hypothesis). Investigators performed multimodel regression analyses on the age and performance data. Based on the absence (for longitudinal data) or presence (for the cross-sectional data) of significant quadratic components in second-order polynomial models, the authors found support for their respective hypotheses. The longitudinal data showed that running performance declined with age in a more linear fashion than did cross-sectional data. Graphical trends showed that the moderation of age-related decline appeared greater for the longitudinal 10 km performances than for the 1500m event.