title: Career-span analyses of track performance: longitudinal data present a more optimistic view of age-related performance decline.
abstract: 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.
authors.affiliation: Department of Kinesiology, McMaster University, Hamilton, ON, Canada. youngb2@mcmaster.ca
authors.forename: Bradley W
authors.initials: BW
authors.lastname: Young
authors.forename: Janet L
authors.initials: JL
authors.lastname: Starkes
mesh_terms: D000328:Adult; D000368:Aged; D000375:Aging; D003430:Cross-Sectional Studies; D006801:Humans; D008297:Male; D008875:Middle Aged; D008954:Models, Biological; D010806:Physical Education and Training; D012044:Regression Analysis; D012420:Running; D013647:Task Performance and Analysis; D014142:Track and Field