Table 1. Study characteristics of the included articles. Author Study region Included age groups [mean age] Type of sports Net sample size[athletic sample, if this is subgroup] Kind of athletes Method of data collection Statistical method Aerenhouts et al. 2008 Belgium 12-18 Track and field 60 (51.7% male) Competitive athletes Questionnaire, 7 day food record Bivariate analyses Aleixandre et al. 2005 unspecified 13-19 [15.67] unspecified 1,378 (43.7% male) [NN; NN% male] unspecified unspecified Linear modeling Assanelli et al. 1991 North Italy 17-19 unspecified 696 (100% male) [330; 100% male] Members of sports teams Questionnaire Logistic regression analyses Bachner-Melman et al. 2006aa unspecified 18.9 Dancing, gymnastics, acrobatic, artistic (synchronized) swimming 458 (0% male) [111; 0% male] unspecified Questionnaire ANCOVA Baumert et al. 1998 Georgia, USA Grades 9-12 unspecified 4,036 (58% male) Students who have participated in organized sports, outside of gym class Questionnaire Multiple linear regression Beals 2002 USA 14-17 [15.8] Volleyball 23 (0% male) Nationally ranked athletes Questionnaire, anthropometric measurements, 3 day food records, blood analyses Univariate analyses Bergen-Cico & Short 1992 New York State, USA 11-16 [13.9] Cross-country 44 (0% male) unspecified Questionnaire, anthropometric measurements, 3 day food records, 24 hour activity record Univariate analyses Berning et al. 1991 California, USA 14-18 Swimming 43 (51.2% male) National athletes Dietary food records Bivariate analyses Castrucci et al. 2004 USA 13-19 unspecified 16,357 (45.7% male) [10,015; NN% male] Data for participation in organized sports were measured Questionnaire Logistic regression analyses Cavadini et al. 2000 Switzerland 9-19 unspecified 3,540 (49.8% male) [NN; NN% male] Non-athletic was defined as engaging in sports less than once a week Questionnaire, in subgroup: 3 day dietary record & interview with dietician Bivariate analyses Crissey & Crissey Honea 2006 USA 12-21 Cheerleading/dance team, softball/baseball, basketball, field hockey, football, ice hockey, soccer, swimming, tennis, track and field, volleyball, wrestling, other sports 7,214 (0% male) Students participating in school Questionnaire Logistic regression analyses Croll et al. 2006 Minnesota, USA 11-18 [14.9] Weight-related sports, power team sports 2,553 (52.9% male) [1,715; 57.5%] Hours of physical activity were considered Questionnaire, anthropometric measurements Bivariate Analyses Cupisti et al. 2002 Italy 14-18 [16.1] Gymnastics, tennis, fencing 119 (0% male) [60; 0% male] Elite national-level athletes Anthropometric measurements and 3-day food recalls; non-standardized questionnaires ANOVA Davis et al. 1997 Lousiana, USA [15.8] unspecified 1,200 (100% male) [990; 100% male] High school athletes Questionnaire Logistic regression analyses Dlin et al. 1991 Israel 14-18 Strength-, endurance-, mixed-, skill- and non-competitive sports 2,447 (100% male) [822; 100% male] Athletes undergoing routine testing at the Department of Sport Medicine at Wingate Institute Questionnaire Bivariate analyses Donato et al. 1994 Italy 17-19 unspecified 696 (100% male) [330; 100% male] Adolescents being in sports teams Questionnaire Logistic regression analyses Donato et al. 1997 Italy Grades 9 - 13 unspecified 1,462 (NN% male) [425; NN% male] Sporting activity was defined as being engaged in out-of-school programs Questionnaire Logistic regression analyses DuRant et al. 1995 USA Grades 9 - 12 Strength training 12,267 (48.8% male) [8,245; NN% male] Strength training was measured Questionnaire Logistic regression analyses Elliot et al. 2007 USA rades 9 - 12 unspecified 7,544 (0% male) [3,847; 0% male] Participating in team sport Questionnaire Logistic regression analyses Escobedo et al. 1993 USA Grades 9 - 12 unspecified 11,248 (NN% male) [4,568; NN% male] Subjects participating in junior sports team during last 12 months Questionnaire Logistic regression analyses Ewing 1998 USA 14-21 unspecified 1,458 (53.3% male) [675; 58.7% male] Subjects participating in high school sports Questionnaire Logistic regression analyses Ferrand et al. 2005 France [Synchronized swimmers: 15.4;Other athletes: 16.5;Non-athletes: 16.3] Synchronized swimming, basketball, handball, volleyball, soccer 132 (0% male) [82; 0% male] Subgroup of national athletes Questionnaire; anthropometric measurements Multivariate analyses, regression analyses Forman et al. 1995 Chicago and Northwest Indiana, USA 13-19 Cross country, football, soccer, basketball, gymnastics, hockey, swimming, wrestling, baseball, tennis, track 1,117 (100% male) High school students participating at least in one interscholastic sport Questionnaire Bivariate analyses French et al. 1994 USA Grades 7 - 10 “Leisure sports” (swimming, skating, golfing, sailing, canoeing, running), “conditioning sports” (running, sit-ups, weight lifting), and “atypical sports” (aerobics, gymnastics, dance, softball) 1494 (47.4% male) [NN; NN% male] unspecified Questionnaire Principal component analyses Grossbard et al. 2007b West Coast of the USA [18.4] unspecified 1,360 (40% male) [335; NN% male] Intramural athletes among first-year college students Questionnaire Linear models Haase & Prapavessis 2001 New Zealand [Group 1: 18.21; Group 2: 18.73; Group 3: 18.97] Group 1: aerobics and diving; Group 2: lightweight rowing; Group 3: soccer 251 (0% male) [198; 0% male] National or international competitors Questionnaires ANOVA Hoffmann 2006 USA Grades 10 - 12 Softball, football, basketball, baseball, swimming, other individual and team sports 9,893 (45.4% male) [NN; NN% male] Subjects participating in sport as an extracurricular activity Questionnaire Multilevel regression analyses Irving et al. 2002 Minnesota, USA 11-18 [14.9] unspecified 4,746 (50.2% male) [NN; NN% male] Hours of physical activity were considered Questionnaire Logistic regression analyses Jerry-Szpak & Brown 1994 USA [15] Football, field hockey, track and field, gymnastics 75 (44% male) Subjects spent at least 20 hours a week participating in organized sports Repeated questionnaires and interviews with coaches Bivariate analyses Jonnalagadda et al. 2004c USA [15.5] Figure skating 49 (46.9% male) [26; 0% male] Elite figure skaters Questionnaires, body measurements Bivariate analyses Karvonen et al. 1995 Finland 16 & 18 unspecified T1: 3,667; T2: 3,175; T3: 2,936 (100% male) Leisure time physical activity organized by sport clubs Questionnaire Bivariate analyses Kiningham & Gorenflo 2001 Michigan, USA [16] Wrestling 2,532 (NN% male) High school competing athletes Questionnaire Bivariate analyses Kokkevi et al. 2008 Bulgaria, Croatia, Cyprus, Greece, Slovak Republic, UK [16] unspecified unspecified Students doing exercise on almost every day Questionnaire Logistic regression analyses Lindholm et al. 1995 Sweden Athletes: 13-16 [14.8]Non-athletes: 14-15 [14.8] Gymnastics 44 (0% male) [22; 0% male) Elite athletes Anthropometric measurements, food recording Bivariate analyses Lorente et al. 2004 France [18.3] Individual and team sports 816 (46.2% male) [621; NN% male] Formal and informal sporting practice was measured Questionnaire Logistic regression analyses Mays & Thompson 2009 USA Grades 9 - 12 unspecified 13,956 (NN% male) [NN; NN% male] Sport participation was measured Questionnaire Logistic regression analyses Mays et al. 2010a USA [14.4(males: 14.5, females: 14.3)] unspecified 8,721 (43.7% male) [NN; NN% male] Sport involvement was measured Questionnaire Growth models Mays et al. 2010b Georgia, USA “≤14 years - ≥ 17 years” (Mays et al. 2010, p. 236) Individual and team sports 378 (75.9% male) Students engaging in school-based sports Questionnaire Regression analyses McHale et al. 2005 Worcester, MA, USA Seventh-grade students (91% were 12 or 13 years old) Football, baseball, softball, basketball, soccer, other team sport 423 (51% male) [271; 62% male] Students taking part in an organized sport during the previous year Interview & questionnaire Multivariate Analysis of Variance (MANOVA) Melia et al. 1996 Canada 11-18 unspecified 16,169 (NN%male) [NN; NN% male] Involvement in competitive sports was measured Questionnaire Bivariate analyses Melnick et al. 2001 USA [16.08 for females, 16.22 for males] unspecified 16,251 (54.8% male) [9,363; 63.8% male] Students participating in sports teams at school and/or outside of school Questionnaire Logistic regression analyses Miller et al. 2002ad USA “14 and younger to 18 and older” (Miller et al. 2002b, p. 389) unspecified 504 (71.4% male) Students who played on a sports team in the past year Questionnaire Regression analyses Miller et al. 2002b USA “14 and younger to 18 and older” (Miller et al. 2002a, p. 476) unspecified 16,181 (54.6% male) [9,685; 61.5% male] Students who played on a sports team in the past year Questionnaire Logistic regression analyses Miller et al. 2005 USA 14-18 unspecified 16,183 (NN% male) [NN; NN% male] Activity in sports team and strength conditioning activity were measured Questionnaire Logistic regression analyses Moore & Werch 2005 Florida, USA [13.39] Basketball, rollerblading, skateboarding, surfing, tennis, dance, cheerleading, gymnastics, football, swimming, wrestling 981 (42.6% male) [772; NN% male] Out-of-school sports and school-sponsored sports were measured Questionnaire ANOVA, logistic regression analyses Moulton et al. 2000 USA Grades 7 - 12 unspecified 455 (42.0% male) [210; NN% male] Athletic participation was measured Questionnaire ANOVA Papaioannou et al. 2004 Greece 11, 13 & 16 unspecified 5,991 (49.2% male) [NN; NN% male] Sport behavior and involvement in organized sports were measured Questionnaire Logistic regression analyses Pate et al. 2000 Columbia, USA 9th through 12th grade students (≤16 to >16) unspecified 7,821 (59,5% male) [6,400; 37.2% male] Students participating in sports teams, run by the school and/or outside of school in the past year Questionnaire Multiple logistic regression analyses Peretti-Watel et al. 2002 France 14-19 unspecified 10,807 (47.9% male) Students with different intensity of sporting activity Questionnaire Multinomial logistic regression Peretti-Watel et al. 2003 South-Eastern France 16-24 [18.3] Individual, team and sliding sport 458 (65.3% male) Elite-student-athletes Questionnaire Logistic regression analyses Peretti-Watel et al. 2004a South-Eastern France 16-24 [18.3] unspecified 458 (65.3% male) Elite student-athletes Questionnaire Cluster analyses and logistic regression analyses Peretti-Watel et al. 2004b South-Eastern France 16-24 [18.3] unspecified 458 (65.3% male) Elite-student-athletes Questionnaire Cluster Analysis, ANOVA Peretti-Watel & Lorente 2004 France 18 unspecified 12,512 (29.0% male) [NN; NN% male] Formal and informal sport practice were measured in hours per week Questionnaire Logistic regression analyses Pernick et al. 2006 California, USA 13-18 [15.7] Track and field, cross-country running, tennis, volleyball, basketball, softball, soccer, swimming, lacrosse, field hockey 453 (0% male) High-school athletes Questionnaire ANCOVA Rainey et al. 1996 South Carolina, USA Grades 9-12 unspecified 7,846 (48.6% male) [3,960; 60.9% male] Different levels of activity were measured Questionnaire Linear models, logistic regression analyses Rhea 1999 USA 13-19 [15.5] Volleyball, basketball, cross-country, track and field, swimming, tennis, softball 1,034 (0% male) [571; 0% male] High school athletes with at least 3 years of competitive experience Questionnaire MANCOVA Ruiz et al. 2005e Spain [Team I: 14.0; Team II: 15.0;Team III: 16.6] Soccer unspecified (100% male) Athletes that trained three times per week Food diaries & questionnaire ANOVA Sabo et al. 2002 USA [Athletes: 16.17; Non-athletes: 16.32] unspecified 8,057 (100% male) [5,973; 100% male] Sport participation was measured Questionnaire Logistic regression analyses Scott et al. 1996 Nebraska, USA Grades 7 - 12 unspecified 4,722 (45.2% male) [3,183; 49.9% male] Sport participation was measured Questionnaire Bivariate analyses Sherwood et al. 2002 Connecticut, USA Grades 7, 9 & 11 Weight-related sports 5,174 (0% male) [1.164; 0% male] Sport participation was measured Questionnaire Logistic regression analyses Slater et al. 2003 Singapore “<15 to >35” (Slater et al. 2003, p. 323) 30 different sports 160 (53.1% male) Athletes competing at a national level Questionnaire ANOVA Soric et al. 2008 Croatia Athletes: 9-13 [11]Non-athletes: 10-12 [11] Artistics, rhythmic gymnastics, ballet 54 (0% male) [39; 0% male] Competitive athletes Questionnaire, anthropometric measurements ANOVA Sundgot-Borgen 1996 Norway 13-20 Rhythmic gymnastics 24 (0% male) [12; 0% male] National athletes Questionnaire, interview, clinical examination, 4 day food records Bivariate analyses Taliaferro et al. 2010 USA Grades 9 - 12 unspecified T1: 15,273 (48.7% male) T5: 14,028 (49.8% male) [NN; NN% male] Participation in one or more sports teams during last 12 months Questionnaire Logistic regression analyses Taub & Blinde 1992 Midwestern, USA [Athletes: 16.2Non-athletes: 15.9] Volleyball, basketball, track/cross-country, tennis, softball 212 (0% male) [100; 0% male] Participation in one or more sport was measured Questionnaire Bivariate analyses Terney & McLain 1990 Chicago, USA Grades 9 - 12 Track, swimming, soccer, basketball, tennis, volleyball, gymnastics, softball, field hockey, badminton, baseball, football,wrestling, and others 2,113 (48.7% male) [1,436; 58.0% male] Sports participation was measured Questionnaire Bivariate analyses Turrisi et al. 2007 North-Western USA [18.8] unspecified 835 (36,6% male) [204; 52% male] Collegiate athletes Questionnaire Mediation analyses Vertalino et al. 2007 Minnesota, USA [14.9] Weight-related sports 4,746 (50.2% male) Participation in weight-related sports was measured Questionnaire Multiple logistic regression analyses Walsh et al. 2000 California, USA 13-19 Baseball 1,226 (100% male) High school athletes Questionnaire Logistic regression analyses Wetherhill & Fromme 2007 USA [18.4] unspecified 2,138 (39.6% male) [NN; NN% male] Participants spending ten or more hours per week in competitive athletics Internet-based survey Linear Modeling Wichstrom & Pedersen 2001 Norway 14-25 [17.33] unspecified 8,877 (46.2% male) [NN; NN% male] Participating in strength or competitive sports Questionnaire Logistic regression analyses Ziegler et al. 1998a USA 11-16 [13.7] Figure skating 21 (0% male) Competitive athletes Anthropometric measurements, questionnaire, 3 day food records Bivariate analyses Ziegler et al. 1998b USA [males: 16females: 14] Figure skating 34 (44.1% male) Nationally ranked athletes 4 day food records, questionnaire, blood analyses Bivariate analyses Ziegler et al. 1998c USA 12-23[females: 15.9, males: 17.8] Figure skating 39 (48.7% male) Nationally ranked junior athletes Questionnaires, recording of food intakes, blood analyses Bivariate analyses Ziegler, Nelson et al. 1999 USA 11-18 Figure skating 41 (51.2% male) Elite athletes Anthropometric measurements, blood analyses, 4 day food records Bivariate analyses Ziegler et al. 2001 USA 12-28[overall: 17males: 18females: 16] Figure skating 161 (49.7% male) Elite athletes Anthropometric measurements, 3 day food records, blood analyses Multivariate regression analyses Ziegler et al. 2002 New England, USA 14-16 Figure skating 18 (0% male) Competitive athletes Questionnaire, anthropometric measurements, 3 day food records, blood analyses Bivariate analyses and range tests Ziegler et al. 2005 USA 14-23 [17.0] Synchronized skating 123 (0% males) Competitive athletes Questionnaire, anthropometric measurements, 3 day food records Bivariate analyses only the athlete group AA was considered in this review as the mean age of the athlete group NAA was greater than 18 (mean age: 21.4) only study I was considered in this review as the mean age of the participants in study II was greater than 18 (mean age: 21.2) only female athletes were considered in this review because the male athletes had a mean age of 19.0. only steroid users were analyzed only teams I to III were considered in this review as the mean age of team IV was greater than 18 (mean age: 20.9)