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THE JOURNAL OF SPORTS MEDICINE AND PHYSICAL FITNESS
A Journal on Applied Physiology, Biomechanics, Preventive Medicine,
Sports Medicine and Traumatology, Sports Psychology
Indexed/Abstracted in: Chemical Abstracts, CINAHL, Current Contents/Clinical Medicine, EMBASE, PubMed/MEDLINE, Science Citation Index Expanded (SciSearch), Scopus
Impact Factor 1,111
The Journal of Sports Medicine and Physical Fitness 2001 June;41(2):170-6
Marathon finishers and non-finishers characteristics. A preamble to success
Yeung S. S., Yeung E. W., Wong T. W. *
From the Department of Rehabilitation Sciences The Hong Kong Polytechnic University Hung Hom, Kowloon, Hong Kong
* Department of Accident and Emergency Pamela Youde Nethersole Eastern Hospital 3 Lok Man Road, Chai Wan, Hong Kong
Background. To investigate if the characteristics and training profiles of runners are significant indicators to predict a successful completion of a marathon.
Methods. Experimental design: comparative investigation between two groups of runners at a marathon race. Setting: participants of the study came from the 1998 Standard Chartered New Airport International Marathon in Hong Kong. Participants: 113 runners were investigated, of which 58 runners dropped out at the first 10 km of the race, while the other 55 were those that consulted for physiothearpy service after the marathon. Measures: using questionnaire, the characteristics and the training profiles of these runners were obtained. These included weekly training distance, longest and shortest training distance per session in one week; warm-up and stretching exercise with the training sessions, number of marathons previously finished and the runners’ opinion of optimal training mileage to complete a marathon.
Results. Independent t-tests with Bonferroni adjustment were used to investigate the difference between the two groups, the results showed significant difference in the weekly training distance (p=0.00), longest and shortest training distance per week (p=0.00), and personal opinion on optimal weekly training distance for a marathon (p=0.00). Logistic regression modeling was then employed to determine variables that best predict the likelihood of completing a marathon.
Conclusions. The findings indicate that the non-finishers are poorly prepared and the results also identify that the longest mileage covered per training session is the best predictor for a successful completion of a marathon with an odds of 1.21.