BACKGROUND Although agility is an important quality in basketball, factors associated with basketball specific pre-planned-agility (change-of-direction-speed, CODS) and non-planned-agility (reactive agility, RA) are rarely investigated. The aim of this study was to evaluate relationship between anthropometric and motor indices with basketball-specific CODS and RA in male basketball players of high performance level. METHODS We tested 88 high-level male basketball players (height: 194.62±8.09 cm; body mass: 89.13±10.81 kg; age: 21.12±3.47 years). The sample was randomly divided into validation (N.=44) and cross-validation (N.=44) subsamples. The study variables included: broad-jump, countermovement-jump, reactive-strength-index, visual-reaction-time, body height, body mass, and body fat percentage (predictors); as well as basketball-specific CODS and RA (criteria). Univariate associations were assessed by Pearson's correlation coefficients. Multivariate relationships between the predictors and the criteria were assessed with multiple regression analysis for the validation subsample, which was then cross-validated. RESULTS The established multiple regression models were successfully cross-validated for CODS (R2=0.40 and 0.36; P=0.01) and RA (R2=0.38 and 0.41; P=0.01, for validation and cross-validation subsample, respectively). The broad-jump (i.e., horizontal displacement) is important predictor of CODS (Beta=-0.41; P=0.01); anthropometrics and body build are specifically associated with RA (Beta=0.51, -0.61 and 0.41 for body height, body mass and body fat percentage, respectively; all P<0.05), while reactive-strength-index is directly related both to CODS (Beta=-0.41, P=0.02), and RA (Beta=-0.40, P=0.03). CONCLUSIONS While basketball players are differentially oriented toward specific game duties, specific capacities should be developed in order to meet specific sport requirements.

Abstract Pojskic, H, Sisic, N, Separovic, V, and Sekulic, D. Association between conditioning capacities and shooting performance in professional basketball players: an analysis of stationary and dynamic shooting skills. J Strength Cond Res 32(7): 1981–1992, 2018—Little is known about the influence of conditioning capacities on shooting performance in basketball. The aim of this study was to examine the relationship between different conditioning capacities and shooting performance in professional basketball players. In this investigation, we examined 38 males (all perimeter players; height: 185.5 ± 6.73 cm; mass: 78.66 ± 10.35 kg). Conditioning capacities were evaluated by tests of muscular strength, aerobic endurance, jumping and throwing capacities, sprinting speed, preplanned agility, anaerobic endurance, and fatigue resistance. Shooting performance was evaluated using game statistics, as well as 6 tests of shooting performance performed in controlled settings: (a) 3 tests of static (i.e., nonfatigued) shooting performance (standardized execution of 1- [S1], 2- [S2] and 3-point shots [S3] in stationary conditions), and (b) 3 tests of dynamic (i.e., fatigued) shooting performance (standardized execution of 1- [D1], 2- (D2), and 3-point shots [D3] in dynamic conditions). All 3 dynamic shooting tests and the S1 test were significantly (p ⩽ 0.05) correlated with corresponding game statistics. Multiple regression indicated that conditioning capacities were significantly related to D1 (R2 = 0.36; p = 0.03), D2 (R2 = 0.44; p = 0.03), S3 (R2 = 0.41; p = 0.02), and D3 (R2 = 0.39; p = 0.03) tests. Players with a higher fatigue resistance achieved better results on the D1 test (&bgr; = −0.37, p = 0.03). Preplanned agility (&bgr; = −0.33, p = 0.04), countermovement jump (&bgr; = 0.42, p = 0.03), and fatigue resistance (&bgr; = −0.37, p = 0.02) were significant predictors of D2 performance. The countermovement jump (&bgr; = 0.39, p = 0.04), medicine ball toss (&bgr; = 0.34, p = 0.04), and anaerobic endurance (&bgr; = 0.46, p = 0.04) predicted the results of D3 performance. Jumping, throwing, and anaerobic endurance capacities were good determinants of the skill of dynamic shooting over a long distance. These findings emphasize the importance of explosive power and anaerobic capacity as determinants of shooting performance in high-level basketball players.

The importance of jumping ability in basketball is well known, but there is an evident lack of studies that have examined different jumping testing protocols in basketball players at advanced levels. The aim of this study was to assess the applicability of different tests of jumping capacity in identifying differences between (i) playing position and (ii) competitive levels of professional players. Participants were 110 male professional basketball players (height: 194.92±8.09 cm; body mass: 89.33±10.91 kg; 21.58±3.92 years of age; Guards, 49; Forwards, 22; Centres, 39) who competed in the first (n = 58) and second division (n = 52). The variables included anthropometrics and jumping test performance. Jumping performances were evaluated by the standing broad jump (SBJ), countermovement jump (CMJ), reactive strength index (RSI), repeated reactive strength ability (RRSA) and four running vertical jumps: maximal jump with (i) take-off from the dominant leg and (ii) non-dominant leg, lay-up shot jump with take-off from the (iii) dominant leg and (iv) non-dominant leg. First-division players were taller (ES: 0.76, 95%CI: 0.35-1.16, moderate differences), heavier (0.69, 0.29-1.10), had higher maximal reach height (0.67, 0.26-1.07, moderate differences), and had lower body fat % (-0.87, -1.27-0.45, moderate differences) than second-division players. The playing positions differed significantly in three of four running jump achievements, RSI and RRSA, with Centres being least successful. The first-division players were superior to second-division players in SBJ (0.63, 0.23-1.03; 0.87, 0.26-1.43; 0.76, 0.11-1.63, all moderate differences, for total sample, Guards, and Forwards, respectively). Running vertical jumps and repeated jumping capacity can be used as valid measures of position-specific jumping ability in basketball. The differences between playing levels in vertical jumping achievement can be observed by assessing vertical jump scores together with differences in anthropometric indices between levels.

Objective Sport and scholastic factors are known to be associated with cigarette smoking in adolescence, but little is known about the causality of this association. The aim of this study was to prospectively explore the relationships of different sport and scholastic factors with smoking prevalence initiation in older adolescents from Bosnia and Herzegovina. Methods In this 2-year prospective cohort study, there were 872 adolescent participants (16 years at baseline; 46% females). The study consisted of baseline tests at the beginning of the third year (September 2013) and follow-up at the end of the fourth year of high school (late May to early June 2015). The independent variables were scholastic and sport-related factors. The dependent variables were (1) smoking at baseline, (2) smoking at follow-up and (3) smoking initiation over the course of the study. Logistic regressions controlling for age, gender and socioeconomic status were applied to define the relationships between independent and dependent variables. Results School absence at the baseline study was a significant predictor of smoking initiation during the course of the study (OR 1.4, 95% CI 1.1 to 1.8). Those who reported quitting sports at baseline showed an increased risk of smoking at the end of the study (OR 1.4, 95% CI 1.1 to 2.0) and of smoking initiation (OR 1.8, 95% CI 1.3 to 2.0). Adolescents who reported lower competitive achievements in sport were at a higher risk of (1) smoking at baseline (OR 1.5, 95% CI 1.1 to 2.1), (2) smoking at follow-up (OR 1.5, 95% CI 1.1 to 2.1) and (3) smoking initiation (OR 1.6, 95% CI 1.1 to 2.6). Conclusions In developing accurate antismoking public health policies for older adolescents, the most vulnerable groups should be targeted. The results showed that most participants initiated smoking before 16 years of age. Therefore, further investigations should evaluate the predictors of smoking in younger ages.

This prospective cohort study aimed to define gender-specific relationships that exist between participation in sports and smoking among older adolescents. The sample comprised 414 adolescents (270 females) from Bosnia and Herzegovina who were 16–17 years old at the baseline. The participants were tested over four occasions (T1, T2, T3 and T4), each divided by six months. The first test (T1) was performed at the beginning of the participants’ 3rd grade of high-school, while the last test (T4) was done at the end of their high-school education. A previously validated structured questionnaire was used to define participants’ involvement in sports and the prevalence of cigarette smoking. Although the odds ratio (OR) varied between time points, sports participation was found to be generally protective against cigarette smoking in males (T1: OR=3.83; 95%CI:1.89-7.09, T2: OR=1.31; 95%CI:0.76-2.67, T3: OR=2.72; 95%CI:1.35-5.50, T4: OR=1.41; 95%CI:0.71-2.81) and females (T1: OR=1.32; 95%CI:0.72-2.44, T2: OR=2.64; 95%CI:1.076.32, T3: OR=2.02; 95%CI:0.89-4.56, T4: OR=2.07; 95%CI:1.13-3.77). Trends over time revealed that smoking initiation preceded adolescent males quitting sports. No such association was evident for adolescent females.

Substance use and misuse (SUM) in adolescence is a significant public health problem and the extent to which adolescents exhibit SUM behaviors differs across ethnicity. This study aimed to explore the ethnicity-specific and gender-specific associations among sports factors, familial factors, and personal satisfaction with physical appearance (i.e., covariates) and SUM in a sample of adolescents from Federation of Bosnia and Herzegovina. In this cross-sectional study the participants were 1742 adolescents (17–18 years of age) from Bosnia and Herzegovina who were in their last year of high school education (high school seniors). The sample comprised 772 Croatian (558 females) and 970 Bosniak (485 females) adolescents. Variables were collected using a previously developed and validated questionnaire that included questions on SUM (alcohol drinking, cigarette smoking, and consumption of other drugs), sport factors, parental education, socioeconomic status, and satisfaction with physical appearance and body weight. The consumption of cigarettes remains high (37% of adolescents smoke cigarettes), with a higher prevalence among Croatians. Harmful drinking is also alarming (evidenced in 28.4% of adolescents). The consumption of illicit drugs remains low with 5.7% of adolescents who consume drugs, with a higher prevalence among Bosniaks. A higher likelihood of engaging in SUM is found among children who quit sports (for smoking and drinking), boys who perceive themselves to be good looking (for smoking), and girls who are not satisfied with their body weight (for smoking). Higher maternal education is systematically found to be associated with greater SUM in Bosniak girls. Information on the associations presented herein could be discretely disseminated as a part of regular school administrative functions. The results warrant future prospective studies that more precisely identify the causality among certain variables.

BACKGROUND In basketball, anthropometric status is an important factor when identifying and selecting talents, while agility is one of the most vital motor performances. The aim of this investigation was to evaluate the influence of anthropometric variables and power capacities on different preplanned agility performances. METHODS The participants were 92 high-level, junior-age basketball players (16-17 years of age; 187.6±8.72 cm in body height, 78.40±12.26 kg in body mass), randomly divided into a validation and cross-validation subsample. The predictors set consisted of 16 anthropometric variables, three tests of power-capacities (Sargent-jump, broad-jump and medicine-ball-throw) as predictors. The criteria were three tests of agility: a T-Shape-Test; a Zig-Zag-Test, and a test of running with a 180-degree turn (T180). Forward stepwise multiple regressions were calculated for validation subsamples and then cross-validated. Cross validation included correlations between observed and predicted scores, dependent samples t-test between predicted and observed scores; and Bland Altman graphics. RESULTS Analysis of the variance identified centres being advanced in most of the anthropometric indices, and medicine-ball-throw (all at P<0.05); with no significant between-position-differences for other studied motor performances. Multiple regression models originally calculated for the validation subsample were then cross-validated, and confirmed for Zig-zag-Test (R of 0.71 and 0.72 for the validation and cross-validation subsample, respectively). Anthropometrics were not strongly related to agility performance, but leg length is found to be negatively associated with performance in basketball-specific agility. Power capacities are confirmed to be an important factor in agility. CONCLUSIONS The results highlighted the importance of sport-specific tests when studying pre-planned agility performance in basketball. The improvement in power capacities will probably result in an improvement in agility in basketball athletes, while anthropometric indices should be used in order to identify those athletes who can achieve superior agility performance.

Objective The community of residence (ie, urban vs rural) is one of the known factors of influence on substance use and misuse (SUM). The aim of this study was to explore the community-specific prevalence of SUM and the associations that exist between scholastic, familial, sports and sociodemographic factors with SUM in adolescents from Bosnia and Herzegovina. Methods In this cross-sectional study, which was completed between November and December 2014, the participants were 957 adolescents (aged 17 to 18 years) from Bosnia and Herzegovina (485; 50.6% females). The independent variables were sociodemographic, academic, sport and familial factors. The dependent variables consisted of questions on cigarette smoking and alcohol consumption. We have calculated differences between groups of participants (gender, community), while the logistic regressions were applied to define associations between the independent and dependent variables. Results In the urban community, cigarette smoking is more prevalent in girls (OR=2.05; 95% CI 1.27 to 3.35), while harmful drinking is more prevalent in boys (OR=2.07; 95% CI 1.59 to 2.73). When data are weighted by gender and community, harmful drinking is more prevalent in urban boys (OR=1.97; 95% CI 1.31 to 2.95), cigarette smoking is more frequent in rural boys (OR=1.61; 95% CI 1.04 to 2.39), and urban girls misuse substances to a greater extent than rural girls (OR=1.70; 95% CI 1.16 to 2.51,OR=2.85; 95% CI 1.88 to 4.31,OR=2.78; 95% CI 1.67 to 4.61 for cigarette smoking, harmful drinking and simultaneous smoking-drinking, respectively). Academic failure is strongly associated with a higher likelihood of SUM. The associations between parental factors and SUM are more evident in urban youth. Sports factors are specifically correlated with SUM for urban girls. Conclusions Living in an urban environment should be considered as a higher risk factor for SUM in girls. Parental variables are more strongly associated with SUM among urban youth, most probably because of the higher parental involvement in children’ personal lives in urban communities (ie, college plans, for example). Specific indicators should be monitored in the prevention of SUM.