Body Composition

Body Composition History  440BC Hippocrates  Ancient Chinese scholars  980AD  Late 1900’s 1 Body Composition Lean Build vs. Non-Lean Build Aesthetic and weight dependent Sports       Cross-country Track Swimming Body builders Wrestling/Boxing Dance/Ballet Non-weight dependent Sports        Tennis Volleyball Basketball Soccer Hockey Lacrosse Field events from Track and Field 2 Analyzing Body Composition and Assessing Weight  Physical measurements: Important for assessment of progress to achieve peak performance. -Height -Weight -Somatotype -Girth -Body Composition Height & Weight  Height (stature) & weight (body mass) -optimal weight is relative to height  For accurate measurements: -measurement boards -calibrated scales 3 Somatotype (Body Build)  Endomorph -stocky, gain fat easily  Mesomorph -muscular, do not gain large amounts of fat  Ectomorph -minor, small amounts of fat and muscle Girth  Circumference of different body parts -waist, hips, calves, thighs, arms, chest.  Helps track changes in body size 4 Tools To Assess Body Composition  Near-infrared interactance (NIR) Biolectrical impedance (BIA)  Skinfold thickness   Body plethysmography (Bod Pod) Hydrostatic (underwater) weighing  Dual-energy X-ray absorptiometry (DEXA or DXA)  Tools To Assess Body Composition 5 Weight Maintenance     Athletes can face unwanted weight gain/weight loss Focus on a time in the pass when weight was maintained Periodization Change of training and competition season  May  increase or decrease nutrient needs Injuries and Off Season Weight Reduction Identify an Appropriate Weight Range  Evaluate Current Dietary and Exercise Practices  Establish Energy and Macronutrient Requirements  Devise a Dietary Plan for Achieving Goals on Established Needs  Educate the Athlete; Review the Dietary Plan, Monitor Status  6 Weight Gain Gaining body weight requires consistent excess energy intake  Gain lean weight or muscle mass  Increase Carbohydrates, Proteins, and Fats  Similar five steps from Weight Reduction  Four steps to achieving optimal performance weight 1. Assessment 2. Goal Setting 3. Action Plan 4. Evaluation and Reassessment 7 Gain Muscle, Lose Excess Fat  In order to do this recommendations are:  Aerobic activity  Resistance Training  keeps fat off and increases muscle mass  Aerobic workouts and weight training along with proper nutrition enables an athlete to get their desired body composition More Protein?  Do athletes need excess protein to build muscle? Do not need excessive amounts of protein No benefits from excess protein  Lower carbohydrate intake  Excessive caloric intake  Greater fluid losses  Higher food costs 8 HET Articles 9 Body composition assessment in athletes with spinal cord injury: comparison of field methods with dual-energy X-ray absorptiometry  Mojtahedi, M., Valentine, R., & Evans, E. (2009). Body composition assessment in athletes with spinal cord injury: comparison of field methods with dual-energy X-ray absorptiometry. Spinal Cord, 47(9), 698-704. Purpose  Purpose of the study was to compare estimates of body fat % from SKF and BIA with the DXA estimates in athletes who have spinal chord injury. 10 Methods (Participants)  16 Caucasian athletes with SCI 8 women & 8 men  12 wheelchair basketball & 4 wheelchair racing programs.  11 complete SCI & 5 incomplete SCI  Methods (Procedures) No alcohol  No exercise 16hr before testing  Empty bladder  Women: during days 7-14 from start of last menstrual period  Anthropometric & BIA measured during morning after 12 hr fasting  11 Methods (Procedures cont.) Anthropometry  SKF  BIA  Compared to DXA  Statistical analyses  Results/Conclusions Men taller & weighed more than Women  Women had greater %Fat than men  %Body Fat for the BIA equations were closer to DXA %Body Fat than SKF estimates for both men and women  Believe neither measurements accurately estimate %Body Fat  12 Relationship between body composition, leg strength, anaerobic power, and on-ice skating performance in division I men’s hockey athletes Potteiger, J.A., Smith, D.L., Maier, M.L. & Foster, T.S. (2010). Relationship between body composition, leg strength, anaerobic power, and on-ice skating performance in division I men’s hockey athletes. Journal of Strength and Conditioning Research, 24(7), 1755-1762. Purpose  To examine relationships between laboratory tests and on-ice skating performance in division I men’s hockey athletes. 13 Methods       21 men (age 20.7 ± 1.6 years Assessed body comp., isokinetic force production in quadriceps and hamstring muscles, and anaerobic muscle power (AMP) Air displacement plethysmography (% body fat) Wingate 30-second cycle ergometer test (AMP) On-ice skating performance measured during 6 timed 89-m sprints  Subjects wore full hockey equipment Results:  %Fat 11.9 ± 4.6  Avg. skating times were moderately correlated to %Fat  Greater %Fat => slower skating speeds  Faster speeds correlated with Wingate Fatigue index  Conclusions:  Laboratory testing of select variables can predict skating performance in ice hockey athletes.  Info used to develop targeted and effective strength and conditioning programs to improve skating speed 14 Dietary Intake and Body Composition of Prepubescent Female Aesthetic Athletes Soric,M., MisigojDurakovic, M., & Pedisic, Z. (2008). Dietary intake and body composition of prepubescent female aesthetic athletes. Journal of Sports Nutrition and Exercise Metabolism,8, 343-354. Purpose  To assess energy and nutrient intakes in prepubescent athletes practicing different aesthetic sport disciplines as well as to assess possible differences that there might be between these groups of athletes. 15 Methods     39 female athletes (9 artistic gymnasts, 14 rhythmic gymnasts, 16 ballet dancers). Actively training for at least 5 years Age 9-13 (median 11) National level competition  Control – 15 premenarcheal females Age 10-12 (median 11) No history of participation in competitive sports Recruited from a public school in Zagreb  No dieting was reported    Methods Cont.  Anthropometry -Height, weight and 2 skinfold thickness sites measured (triceps and calves). -Taken by skilled tech. before morning training.  Food Intake -Quantitative Food Frequency Questionnaire -7 day diet record -qFFQ readministered after 30 days -Diet analysis includes: food, beverage, supplement 16 Results/Conclusions Rhythmic gymnasts: sig. taller, no difference in weight or BMI than artistic gymnasts.  Significant diff. in body fat % between artistic gymnasts and ballet dancers. (12.4% + 1.8% to 17.4% + 4.7%)  No difference between artistic & rhythmic gymnasts  Results/Conclusions    Energy & Macronutrients -No significant difference in energy intake -Difference in macronutrient contribution to total energy intake. Higher CHO, lower fat. Artistic gymnasts: 57% + 6% , 29% + 5% Rhythmic gymnasts: 48% + 6%, 36% + 5% Ballet dancers: 51% + 4%, 34% + 3% Controls: 51% + 5%, 34% + 4% No difference in intake of minerals/vitamins -Sodium above upper limit, potassium & calcium below adequate intake, all other minerals/vitamins higher than current daily recs. Hydration inadequate in all except controls. 17 Sport and training influence bone and body composition in women collegiate athletes  Carbuhn, A.F., Fernandez, T.E., Bragg, A.F., Green, J.S. , & Crouse, S.f. . (2010). Sport and training influence bone and body composition in women collegiate athletes. Journal of Strength & Conditioning Research (Lippincott Williams & Wilkins), 24(7), 1710-1717. Purpose  This is a novel descriptive study to characterize off-season, preseason, and postseason bone and body composition measures in women collegiate athletes. 18 Methods    -Athletes from five sports (softball, basketball, volleyball, swimming, track jumpers) -Analyzed their total body mass, lean mass, fat mass, percent body fat, bone mineral density, arm, leg, pelvis, and spine BMD during three different parts of the season. -They were analyzed during the off-season, preseason, and post season. Results       Significant off-season to preseason or postseason changes in %BF, LM, and BMD within each sport were as follows, respectively: Softball, -7, +4, +1%; Basketball, -11, +4, +1%; Volleyball, unchanged, unchanged, +2%; Swimming, unchanged, +2.5%, unchanged; Track jumpers and sprinters, -7, +3.5, +1%. 19 11/22/10 Results Cont.      Comparisons among athletes in each sport showed bone measurements of swimmers averaged 4-19% lower than that of athletes in any other sport, Track jumpers and sprinters, %BF and FM averaged 36 and 43% lower compared with other sports at all seasonal periods. Athletes playing basketball and volleyball were most similar Softball athletes' values fell between all other athletes. These data serve as sport-specific reference values for comparisons at in-season and off-season training periods among women collegiate athletes in various sports. Body Mass Index as a Predictor of Percent Fat in College Athletes and Nonathletes  Ode, J. , Pivarnik, J. , Reeves, M. , & Knous, J. (2007). Body mass index as a predictor of percent fat in college athletes and nonathletes. Medicine & Science in Sports & Exercise, 39(3), 403-409. 20 Purpose  The purpose of this study was to evaluate the relationship of Body Mass Index (BMI) and percent body fat focusing on the college athlete and the college nonathlete  Why?  there have been some misclassifications in the college athlete populations when athletes are given BMI that state they are overweight when they actually have healthy body fat percentage 21 Methods/Materials  Total of 440 participants  213 college aged nonathletes (78 male/ 135 male)  226 varsity college athletes (149 male/ 77 female)     Males: football, basketball, hockey and wresting Females: basketball, crew, and softball 3 male groups and 2 female groups    undergraduate kinesiology majors in an exercise physiology class male athletes, male nonathletes, and linemen female athletes and female nonathletes Calculated BMI and calculated their percent fat with the BOD POD   BMI: reading greater or equal to 25 kg per meter was defined as overweight. PERCENT FAT: A score of 20% fat for males and 33% fat for females was deemed overfat Results      Male Athletes  67% of the participant’s BMI scores said they were overweight but they were in the normal fat percentage range  Small proportion of participants were given normal BMI scores when they were actually deemed overfat Male Nonathletes  25% of the participant’s BMI scores said they were overweight but they were in the normal fat percentage range Linemen  No linemen had a BMI lower than 25– all deemed overweight based on this number  only one was less than 20% body fat Female Athletes  31% of the participant’s BMI results said they were overweight but they were in the normal fat percentage range Female Nonathlete  only 7% of the participant’s BMI scores said they were overweight but they were in the normal fat percentage range  44% of the participants were given normal BMI scores when they were actually deemed overfat 22 Conclusion    “BMI should be used cautiously when classifying fatness in college athletes and nonathletes. Our results support the need for different BMI classifications of overweight in these populations” (Ode, Pivarnik, Reeves, & Knous, 2007, p. 403). Athletes have a greater muscle mass than the general population and therefore the BMI system often misclassifies them as overweight. Coaches, athletes, trainers, and registered dietitians  BMI has been found unreliable for athletes 23