Wichmann, Therese2023-02-162023-02-162019-12https://hdl.handle.net/11299/252483University of Minnesota M.S. thesis. December 2019. Major: Kinesiology. Advisor: Donald Dengel. 1 computer file (PDF); xii, 85 pages.PURPOSE: Longitudinal assessment of football player body composition would identify developmental and structural changes in respect to position demands, however no study has examined changes by season and age. The purpose of this study was to examine longitudinal body composition changes by position, categorized by season and age, using dual X-ray absorptiometry (DXA) in NCAA Division I football players. METHODS: Seven hundred and forty-two collegiate male football athletes aged 17-24 years (X̅age= 19.9±1.3 yrs) participated in this study. Following height and body mass measurement, each athlete completed a DXA scan to assess percent body fat (%BF), fat mass (FM), lean soft tissue mass (LM), bone mineral density (BMD), and visceral adipose tissue mass (VAT) using a GE Lunar iDXA (General Electric Medical Systems, Madison, Wisconsin, USA). DXA scans were analyzed by the same technician using enCoreTM software (platform version 16.2, General Electric Medical Systems, Madison, WI, USA), and body mass distribution ratios of total upper mass to lean leg mass ratio (TULLR), lean upper mass to lean leg mass ratio (LULLR), upper total mass to legs total mass ratio (ULR), and gynoid lean mass to leg lean mass ratio (GLR) were calculated. Athletes were categorized into Linemen (offensive and defensive linemen), Big Skill (quarterbacks, linebackers, and tight ends), Skill (running backs, defensive backs, and wide receivers), or Special Teams (punters, kickers, and long snappers). One scan per athlete was used in Pre-Season (June-September), In-Season (October-November), Post-Season (December-February), and Spring Season (March-May). Separate repeated one-way analysis of variance (ANOVA) with linear mixed-effects models assessed total and regional body composition differences across age, position groups, and seasons. TukeyHSD post hoc tests were used to determine significant differences among position groups, while adjusting for multiple comparisons (p<0.05). Prediction equations for %BF, LM, FM, and VAT mass were computed using linear mixed-effects models. RESULTS: Linemen had the greatest %BF, FM, VAT, LM, and BMD (p<0.05) compared to other groups for each season and age. From Pre-Season to Post-Season, %BF, FM, LM, ULR, and GLR decreased for each position group (p<0.05). From Post-Season to Spring Season, %BF and VAT decreased while LM, LULLR, and GLR increased within each position group (p<0.05). %BF, FM, VAT, LM, TULLR, LULLR, and GLR increased, while ULR decreased, with player age in all position groups (p<0.05). Prediction equations and graphs for %BF, LM, FM, and VAT were computed. Each position group experienced small to moderate increases as age progressed. CONCLUSION: The results of this study indicate that body composition significantly worsened from Pre-Season to Post-Season and improved from the Pre-Season and Post-Season to the Spring Season. In addition, players increased %BF, FM, VAT, and LM as they progressed through their college career. These findings allow coaches to understand how body composition fluctuates by season and age given player position group. Future studies are needed to determine how player year of eligibility, nutrition, and position-specific workouts influence body composition by season and age.enBody CompositionDual X-ray AbsorptiometryPrediction EquationThesis or Dissertation