In this study, we compared the growth, maturity status, functional capacity, sport-specific skill, and goal orientation of 159 male soccer players, aged 11-12 (n = 87) and 13-14 years (n = 72) years, ...who at follow-up 2 years later discontinued participation (dropout), continued at the same standard (club) or moved to a higher level (elite). Age group-specific multivariate analysis of variance was used for comparisons. Among 11- to 12-year-old players at baseline, a gradient of elite > club > dropout was suggested for size and function, although differences were not consistently significant. Elite players performed significantly better in only two of the four skills, dribbling and ball control. A gradient of elite > club > dropout was more clearly defined among 13- to 14-year-old players at baseline. Elite players were older chronologically and skeletally, larger in body size and performed better in functional capacities and three skill tests than club players and dropouts. Baseline task and ego orientation did not differ among dropouts and club and elite players at follow-up in either age group. The results suggest an important role for growth and maturity status, functional capacities, and sport-specific skills as factors in attrition, persistence, and moving up in youth soccer.
Objectives. Training for sport is associated with the development of bone minerals, and the need for reference data based on athletes is often indicated. The purpose of this study was to develop a ...reference for bone mineral density (BMD) and content (BMC) specific for youth athletes of both sexes participating in several sports. Methods DEXA (dual energy X-ray absorptiometry) was used for total body measurements of bone minerals in 1385 athletes 11 to 20 years, 1019 males and 366 females. The athletes were training in several sports at Hungarian academies. Reference values for total bone mineral density and bone mineral content, and also BMD excluding the head (total body less head, TBLH) were developed using the LMS chartmaker pro version 2.3. Results. The centile distributions for BMD and BMC of the athletes differed significantly from those of the age- and sex-specific references for the general population. The youth athletes had higher BMD and BMC than those of the reference for the general population. Conclusion. The potential utility of the DEXA reference for male and female youth athletes may assist in monitoring changes in the BMC and BMD associated with normal growth and maturation, and perhaps more importantly, may be useful in monitoring changes specific to different phases of sport-specific training protocols.
The purpose of the study was to evaluate the cross-sectional relationship between BMI and a physical fitness index (PFI) based on four indicators of fitness in a national sample of Taiwanese youth.
...Height, weight, and four measures of physical fitness (sit-ups completed in 60 s, standing long jump, sit and reach, and 800- or 1600-m run/walk) were measured in a national sample of 102,765 Taiwanese youth 9-18 yr of age: 50,940 girls and 51,825 boys. BMI was calculated for each subject. Within each sex-specific half-year age group, students were classified into five BMI categories based on national percentiles: very low, BMI < 5th percentile; low, BMI >or= 5th but < 15th percentiles; normal, BMI >or= 15th but < 85th percentiles; high, BMI >or= 85th but < 95th percentiles; and very high, BMI >or= 95th percentiles. Z-scores based on sex- and age-specific means and standard deviations were calculated, and the sum of z-scores for the four fitness tests was used as a PFI. Differences in PFI between BMI categories within each sex-specific half-year age group were compared with ANOVA with Bonferroni adjustments. Sex-specific regressions of PFI on BMI, using a nonlinear quadratic model, were done in four broader age categories.
Relationships between BMI and PFI are nonlinear and vary with age from late childhood through adolescence. With increasing age during adolescence, the relationship becomes parabolic, and the peaks of the parabola are sharper in adolescent boys than girls.
PFI declines in a curvilinear manner with increasing BMI among youth 9-18 yr of age, but the slope of the relationship varies with age.
The objective of this study is to evaluate the concordance of predicted maturity status classifications (pre-, circa-, or post-peak height velocity (PHV)) relative to observed age at PHV in youth ...soccer players.
Longitudinal height records for 124 male soccer players were extracted from academy records spanning the 2000 to 2022 seasons. Age at PHV for each player was estimated with the Superimposition by Translation and Rotation model. Players were classified as pre-, circa-, or post-PHV using both ±1- and ±0.5-yr criteria to define the circa-PHV interval. Maturity status was estimated with several prediction protocols: maturity offset (Mirwald, Moore-1, Moore-2), maturity ratio (Fransen), and percentage of predicted adult height (PAH%) using the Khamis-Roche and Tanner-Whitehouse 2 equations using several bands: 85% to 96%, 88% to 96%, 88% to 93%, and 90% to 93% for the circa-PHV interval, and visual evaluation of individual growth curves alone or with PAH% based on Khamis-Roche and Tanner-Whitehouse 2. Concordance of maturity status classifications based on complete growth curves and predicted estimates of maturity status was addressed with percentage agreement and Cohen's kappa.
Visual evaluation of the growth curves had the highest concordance (≈80%) with maturity status classifications (pre-, circa-, post-PHV) based on longitudinal data for individual players. Predicted maturity offset with the Mirwald, Moore-1, and Fransen equations misclassified about one-third to one-half of the players, whereas concordance based on PAH% varied with the band used, but not with the method of height prediction.
Visual assessment of the individual growth curves by an experienced assessor provides an accurate estimate of maturity status relative to PHV. Maturity offset prediction equations misclassify the majority of players, whereas PAH% provides a reasonably valid alternative.
The impact, positive or negative, of youth sport specialisation (YSS) on short-term and long-term performance is not fully understood; however, the desire to maximise performance goals is generally ...considered the primary reason children and adolescents specialise at a young age. We performed a systematic review of original research to establish the association of YSS and task-focused or career-focused performance outcomes.
Systematic review.
Databases searched include PubMed, EMBASE, Cochrane, CINAHL and SPORTDiscus.
We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines to identify peer-reviewed research articles published in English between 1 January 1990 and 31 December 2018 that reported original findings on the association of YSS and performance outcomes. Studies without an explicit measure of sport specialisation, for example, volume measures without measuring sport specialisation, were excluded.
Twenty-two articles were included in the final review; 15 addressed career performance outcomes and 7 considered task performance outcomes. All identified studies were cross-sectional or retrospective in design. The proportion of elite athletes who specialised early ranged between 7% and 85%, depending on sport and definition of specialisation. Elite athletes often specialised between the ages of 14 and 15 compared with their non-elite or semi-elite peers who typically specialised prior to 13 years. In addition, neuromuscular control, anterior reach asymmetry and physical task outcomes did not differ by specialisation status.
The volume and methodological rigour of published research in this field are limited. Our review suggests that YSS is not required to achieve success at elite levels. YSS also does not appear to improve task-related performance (eg, anterior reach, neuromuscular control) outcomes for specialised athletes when compared with non-specialised athletes during childhood and adolescence.
OBJECTIVE: To determine whether the U.S. Centers for Disease Control and Prevention (CDC; CDC Reference) or International Obesity Task Force (IOTF; IOTF Reference) BMI cut-off points for classifying ...adiposity status in children are more effective at predicting future health risk. RESEARCH METHODS AND PROCEDURES: The sample (N = 1709) included 4- to 15-year-old (at baseline) boys and girls from the Bogalusa Heart Study. Overweight and obesity status were determined using both the CDC Reference and IOTF Reference BMI cut-off points at baseline. The ability of childhood overweight and obesity, determined from the two BMI classification systems, to predict obesity and metabolic disorders in young adulthood (after a 13- to 24-year follow-up) was then compared. RESULTS: Independently of the classification system employed to determine adiposity based on childhood BMI, the odds of being obese and having all of the metabolic disorders in young adulthood were significantly (p < 0.05) higher in the overweight and obese groups by comparison with the nonoverweight groups. Childhood overweight and obesity, determined by both the CDC Reference and IOTF Reference, had a low sensitivity and a high specificity for predicting obesity and metabolic disorders in young adulthood. Overweight and obesity as determined by the CDC Reference were slightly more sensitive and slightly less specific than the corresponding values based on the IOTF Reference. DISCUSSION: Overweight and obesity during childhood, as determined by both the CDC and IOTF BMI cut-off points, are strong predictors of obesity and coronary heart disease risk factors in young adulthood. The differences in the predictive capacity of the CDC Reference and IOTF Reference are, however, minimal.
Interrelationships among skeletal maturity status, body size, ventilator thresholds (VT) and peak oxygen uptake (VO2peak) were considered in 47 adolescent male soccer players aged 12.5-15.4 years. ...Body mass, stature, and the triceps and subscapular skinfolds were measured. The latter were used to estimate fat mass and fat-free mass. Skeletal age was assessed with the Fels method. VO2peak and VO2 at the first (VT1) and second (VT2) ventilatory thresholds were determined during an incremental maximal exercise test on a motorized treadmill. Ratio standards and allometric models were used in the analysis. Scaling exponents suggested linearity for all combinations between size descriptors and physiological variables, except between log-transformed values of VT1 and body mass (mL·kg-0.801·min, 95%CI: 0.649 to 0.952). Early maturing players attained greater values than players classified as "on-time" in skeletal maturity for the three ventilatory parameters expressed in absolute terms (d ranged from 0.65 to 0.71). The differences were attenuated after normalizing for mass descriptors using ratio standards and scaled variables (d ranged from 0.00 to 0.31). The results suggested significant variability between maturity groups when moving from VT1 to maximal metabolic conditions expressed by unit of stature (VT1: t = -2.413, p = 0.02, d = 0.60; VT2: t = -2.488, p = 0.02, d = 0.65; VO2peak: t = -2.475, p = 0.02, d = 0.65). Skeletal maturity status and associated variation in overall body size affects VT1, VT2 and VO2peak. The observed scaling of ventilatory outputs for body size may be related to the better running economy and smaller body size of average maturing athletes.
Equations predicting age at peak height velocity (APHV) are often used to assess somatic maturity and to adjust training load accordingly. However, information on the intra-individual accuracy of ...APHV in youth athletes is not available.
The purpose of this study is to assess the accuracy of predication equations for the estimation of APHV in individual youth male football players.
Body dimensions were measured at least every three months in 17 elite youth male football players (11.9 ± 0.8 years at baseline) from the 2008-2009 through the 2011-2012 seasons. APHV was predicted at each observation with four suggested equations. Predicted APHV was compared to the player's observed APHV using one-sample-t-tests and equivalence-tests. Longitudinal stability was assessed by comparing the linear coefficient of the deviation to zero.
Predicted APHV was equivalent to the observed APHV in none of the players. A difference with a large effect size (Cohen's d > 0.8) was noted in 87% of the predictions. Moreover, predictions were not stable over time in 71% of the cases.
None of the evaluated prediction equations is accurate for estimating APHV in individual players nor are predictions stable over time, which limits their utility for adjusting training programmes.
Evaluate the relationship between body mass index and physical fitness in a cross-sectional sample of Brazilian youth.
Participants were 3849 adolescents (2027 girls) aged 10–17 years. Weight and ...height were measured; body mass index was calculated. Physical fitness was evaluated with a multistage 20m shuttle run (cardiovascular endurance), standing long jump (power), and push-ups (upper body strength). Participants were grouped by sex into four age groups: 10–11, 12–13, 14–15, and 16–17 years. Sex-specific ANOVA was used to evaluate differences in each physical fitness item among weight status categories by age group. Relationships between body mass index and each physical fitness item were evaluated with quadratic regression models by age group within each sex.
The physical fitness of thin and normal youth was, with few exceptions, significantly better than the physical fitness of overweight and obese youth in each age group by sex. On the other hand, physical fitness performances did not consistently differ, on average, between thin and normal weight and between overweight and obese youths. Results of the quadratic regressions indicated a curvilinear (parabolic) relationship between body mass index and each physical fitness item in most age groups. Better performances were attained by adolescents in the mid-range of the body mass index distribution, while performances of youth at the low and high ends of the body mass index distribution were lower.
Relationships between the body mass index and physical fitness were generally nonlinear (parabolic) in youth 10–17 years.
Avaliar a relação entre o índice de massa corporal e a aptidão física em uma amostra transversal de jovens brasileiros.
Os participantes foram 3.849 adolescentes (2.027 meninas) entre 10-17 anos. Foram medidos o peso e a estatura e foi calculado o índice de massa corporal. A aptidão física foi avaliada com: a corrida vaivém de 20 metros de vários estágios (resistência cardiovascular), impulsão horizontal (energia) e flexões (força superior do corpo). Os participantes foram agrupados por sexo em quatro faixas etárias: 10-11, 12-13, 14-15 e 16-17 anos. A Anova específica para sexo foi usada para avaliar as diferenças em cada item de aptidão física entre as categorias de status do peso por faixa etária. As relações entre o índice de massa corporal e cada item de aptidão física foram avaliadas com os modelos de regressão quadrática por faixa etária com relação ao sexo.
A aptidão física de jovens magros e normais foi, com poucas exceções,significativamente melhor do que a aptidão física de jovens com sobrepeso e obesos em cada faixa etária por sexo. Por outro lado, os desempenhos na aptidão física não diferiram de forma consistente, em média, entre jovens magros e com peso normal e entre jovens com sobrepeso e obesos. Os resultados das regressões quadráticas indicaram uma relação curvilínea (parabólica) entre o índice de massa corporal e cada item de aptidão física na maior parte das faixas etárias. Os melhores desempenhos foram obtidos pelos adolescentes na faixa intermediária da distribuição do índice de massa corporal, ao passo que os desempenhos dos jovens nas extremidades inferiores e superiores da distribuição do índice de massa corporal foram menores.
As relações entre o índice de massa corporal e a aptidão física foram, em geral, não lineares (parabólica) nos jovens entre 10-17 anos.
Abstract Objective To examine 45-year trends in time use and physical activity energy expenditure (PAEE) in a nationally representative sample of US mothers. Participants and Methods We quantified ...time allocation to physical activity (PA), sedentary behaviors (SED), and PAEE from 1965 to 2010 in mothers with older children (MOC) (>5 to ≤18 years) and mothers with younger children (MYC) (≤5 years). Physical activity was the sum of time allocated to housework, child care, laundry, food preparation, postmeal cleanup, and exercise. Sedentary behavior was the sum of time spent in a vehicle and using screen-based media. Physical activity energy expenditure was calculated using body weights from national surveys and metabolic equivalents. Results From 1965 to 2010, the time allocated to PA decreased by 11.1 h/wk (from 32.0 to 20.9 h/wk ) in MOC and by 13.9 h/wk (from 43.6 to 29.7 h/wk ) in MYC. The time spent in SED increased by 7.0 h/wk in MOC (from 17.7 to 24.7 h/wk) and increased by 5.7 h/wk in MYC (from 17.0 to 22.7 h/wk ). Physical activity energy expenditure decreased by 1237.6 kcal/wk (176.8 kcal/d) in MOC (from 5835.3 to 4597.7 kcal/wk), and in MYC, PAEE decreased by 1572.5 kcal/wk (224.6 kcal/d), from 7690.5 to 6118.0 kcal/wk. Conclusion There was a significant reallocation of time by mothers from PA (eg, housework) to SED (eg, watching television) between 1965 and 2010. Given the essential role of PA for health and the potential for the intergenerational transmission of obesity and obesogenic behaviors, these results suggest that maternal inactivity may be an important target for the primary prevention of chronic noncommunicable diseases and obesity.
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