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Article Title

CHARACTERIZING PRE-SEASON TRAINING HABITS OF COMPETITIVE MASTERS-AGED CROSS-COUNTRY SKIERS

Abstract

CHARACTERIZING PRE-SEASON TRAINING HABITS OF COMPETITIVE MASTERS-AGED CROSS-COUNTRY SKIERS

T.K. Vetrone, E.C. Ranta, & D.P. Heil, FACSM. Movement Science \ Human Performance Lab, Montana State University, Bozeman, MT

Introduction: The training habits of Masters-aged cross-country skiers (i.e., those 40+ years of age) have been overlooked in the research literature. The primary purpose of this study was to characterize the pre-season training habits of Masters-aged cross-country skiers using self-report training logs in order to develop more specific guidelines to improve future training practices. Methods: Masters cross-country skiers (24 men: (Mean±SD) 57 ± 8 yrs., 40-73 yrs.; 19 women: 55 ± 7 yrs., 40-69 yrs.) were recruited from the Pacific Northwest region. Over one 14-day data collection period (September-October, 2013), subjects were instructed to self-record all activity bouts in a spreadsheet-based training log. Activity bouts were classified into one of four categories by degree of cross-country ski training specificity: C1 = activities of daily living (ADL) and lowest specificity; C2 = low specificity (e.g., yoga); C3 = moderate specificity (e.g., running, cycling); C4 = highest specificity (e.g., roller skiing). Total time within each activity bout was recorded into self-assessed intensity zones: Z0 = minimal intensity; Z1 = low to moderate intensity; Z2 = high and race pace intensity; Z3 = above race pace intensity. Total time recorded in each category and training zone was evaluated using a two-factor RM ANOVA and Sheffe’s post-hoc test (0.05 alpha). Results: Total time self-reported within the logs was 12.4±2.1 hrs/wk. Total time (T) within C3 activities (TC3= 8.5±1.1 hrs/wk) was significantly higher (P<0.001) than all other categories (1.5±0.4, 0.9±0.4, 0.6±0.4 hrs/wk for TC1, TC2, and TC4, respectively,). In addition, total time (T) in Z1 (TZ1= 6.3±0.9 hrs/wk) was significantly higher (P<0.001) than other zone values (2.6±0.7, 2.4±0.4, 1.1±0.2 hrs/wk for TZ0, TZ2, and TZ3, respectively). Conclusion: These skiers tended to self-select low-moderate intensity training (Zone 1) that was predominantly low impact and moderate in specificity (Category 3) to cross country skiing. These preferences may reflect an avoidance of traditional high impact training (e.g., running), as well as high risk activities (e.g., roller skiing), while the Zone 1 preference may simply reflect a dominance of base training. These results indicate that the observed training habits differ from what is known to be optimal for elite and junior skiers (i.e. polarized training models) and may in fact be the optimal training to avoid high risk or high impact activities.

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