Predictive variables for half-Ironman triathlon performance. 2014

Nicole Gilinsky, and Keely R Hawkins, and Theresa N Tokar, and Jamie A Cooper
College of Education, Texas Tech University, USA.

OBJECTIVE To examine the relationship between training, anthropometric characteristics, tapering, and time performance for a half-Ironman distance race. METHODS Cross sectional study in triathletes. METHODS Data were obtained for 209 participants (155 males; 54 females) competing in a half-Ironman triathlon. Participants provided information regarding triathlon experience, training, race preparation, and tapering. Participants were divided into three groups based on finish time for analysis. RESULTS Males in the fastest group weighed less and had lower body fat percentage compared to males in the slower groups (p ≤ 0.01). Athletes in the fastest group had completed more half-Ironman races and took fewer rest days during training compared to athletes in the slower groups (p<0.01). The average time spent training was 13.9 ± 5.4 h per week, and this did not differ between groups. The faster group of athletes set lower race time goals (p<0.01) and placed greater importance on achieving goal time (p=0.04). Eighty-one percent reported performing a taper with a decrease in training volume of 58.5 ± 34.7% and a decrease in training intensity of 44.9 ± 40.8%. However, there were no differences in taper variables between the three groups. Age, previous best half-Ironman time, goal time, and goal importance predicted 58% of variance in finish time. CONCLUSIONS The fastest group of triathletes exhibited differences in anthropometrics, race experience, and goal-setting compared to slower athletes. There were no differences in total training hours or tapering between groups. The best predictors of race performance were age, previous best half-Ironman time, goal time, and importance of reaching this goal.

UI MeSH Term Description Entries
D008297 Male Males
D008875 Middle Aged An adult aged 45 - 64 years. Middle Age
D010807 Physical Endurance The time span between the beginning of physical activity by an individual and the termination because of exhaustion. Endurance, Physical,Physical Stamina,Stamina, Physical
D003430 Cross-Sectional Studies Studies in which the presence or absence of disease or other health-related variables are determined in each member of the study population or in a representative sample at one particular time. This contrasts with LONGITUDINAL STUDIES which are followed over a period of time. Disease Frequency Surveys,Prevalence Studies,Analysis, Cross-Sectional,Cross Sectional Analysis,Cross-Sectional Survey,Surveys, Disease Frequency,Analyses, Cross Sectional,Analyses, Cross-Sectional,Analysis, Cross Sectional,Cross Sectional Analyses,Cross Sectional Studies,Cross Sectional Survey,Cross-Sectional Analyses,Cross-Sectional Analysis,Cross-Sectional Study,Cross-Sectional Surveys,Disease Frequency Survey,Prevalence Study,Studies, Cross-Sectional,Studies, Prevalence,Study, Cross-Sectional,Study, Prevalence,Survey, Cross-Sectional,Survey, Disease Frequency,Surveys, Cross-Sectional
D005260 Female Females
D006801 Humans Members of the species Homo sapiens. Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D000293 Adolescent A person 13 to 18 years of age. Adolescence,Youth,Adolescents,Adolescents, Female,Adolescents, Male,Teenagers,Teens,Adolescent, Female,Adolescent, Male,Female Adolescent,Female Adolescents,Male Adolescent,Male Adolescents,Teen,Teenager,Youths
D000328 Adult A person having attained full growth or maturity. Adults are of 19 through 44 years of age. For a person between 19 and 24 years of age, YOUNG ADULT is available. Adults
D000368 Aged A person 65 years of age or older. For a person older than 79 years, AGED, 80 AND OVER is available. Elderly
D000886 Anthropometry The technique that deals with the measurement of the size, weight, and proportions of the human or other primate body.

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