Growth, maturation, and development dominate the daily lives of children and adolescents for approximately the first 2 decades of life. Growth and maturation are biological processes, while ...development is largely a behavioral process. The 3 processes occur simultaneously and interact. They can be influenced by physical activity and also can influence activity, performance, and fitness. Allowing for these potential interactions, 10 questions on growth and maturation that have relevance to physical activity, performance, and fitness are presented. The questions are not mutually exclusive and address several broadly defined topical areas: exercise and growth, body weight status (body mass index, adiposity rebound, "unhealthy weight gain"), movement proficiency (hypothesized barrier, role in obesity), individual differences, tracking, maturity-associated variation in performance, and corresponding variation in physical activity. Central to the discussion of each is the need for a biocultural approach recognizing the interactions of biology and behavior as potential influences on the variables of interest.
Background
Predicted maturity offset and age at peak height velocity are increasingly used with youth athletes, although validation studies of the equations indicated major limitations. The equations ...have since been modified and simplified.
Objective
The objective of this study was to validate the new maturity offset prediction equations in independent longitudinal samples of boys and girls.
Methods
Two new equations for boys with chronological age and sitting height and chronological age and stature as predictors, and one equation for girls with chronological age and stature as predictors were evaluated in serial data from the Wrocław Growth Study, 193 boys (aged 8–18 years) and 198 girls (aged 8–16 years). Observed age at peak height velocity for each youth was estimated with the Preece–Baines Model 1. The original prediction equations were included for comparison. Predicted age at peak height velocity was the difference between chronological age at prediction and maturity offset.
Results
Predicted ages at peak height velocity with the new equations approximated observed ages at peak height velocity in average maturing boys near the time of peak height velocity; a corresponding window for average maturing girls was not apparent. Compared with observed age at peak height velocity, predicted ages at peak height velocity with the new and original equations were consistently later in early maturing youth and earlier in late maturing youth of both sexes. Predicted ages at peak height velocity with the new equations had reduced variation compared with the original equations and especially observed ages at peak height velocity. Intra-individual variation in predicted ages at peak height velocity with all equations was considerable.
Conclusion
The new equations are useful for average maturing boys close to the time of peak height velocity; there does not appear to be a clear window for average maturing girls. The new and original equations have major limitations with early and late maturing boys and girls.
Problems with accurate chronological age (CA) reporting occur on a more or less regular basis in youth sports. As a result, there is increasing discussion of age verification. Use of 'bone age' or ...skeletal age (SA) for the purpose of estimating or verifying CA has been used in medicolegal contexts for many years and also in youth sport competitions. This article reviews the concept of SA, and the three most commonly used methods of assessment. Variation in SA within CA groups among male soccer players and female artistic gymnasts is evaluated relative to the use of SA as a tool for verification of CA. Corresponding data for athletes in several other sports are also summarized. Among adolescent males, a significant number of athletes will be identified as older than a CA cutoff because of advanced skeletal maturation when they in fact have a valid CA. SA assessments of soccer players are comparable to MRI assessments of epiphyseal-diaphyseal union of the distal radius in under-17 soccer players. Both protocols indicate a relatively large number of false negatives among youth players aged 15-17 years. Among adolescent females, a significant number of age-eligible artistic gymnasts will be identified as younger than the CA cutoff because of later skeletal maturation when in fact they have a valid CA. There is also the possibility of false positives-identifying gymnasts as younger than the CA cutoff because of late skeletal maturation when they have a valid CA. The risk of false negatives and false positives implies that SA is not a valid indicator of CA.
Year-round training in a single sport beginning at a relatively young age is increasingly common among youth. Contributing factors include perceptions of Eastern European sport programs, a parent's ...desire to give his or her child an edge, labeling youth as talented at an early age, pursuit of scholarships and professional contracts, the sporting goods and services industry, and expertise research. The factors interact with the demands of sport systems. Limiting experiences to a single sport is not the best path to elite status. Risks of early specialization include social isolation, overdependence, burnout, and perhaps risk of overuse injury. Commitment to a single sport at an early age immerses a youngster in a complex world regulated by adults, which is a setting that facilitates manipulation - social, dietary, chemical, and commercial. Youth sport must be kept in perspective. Participants, including talented young athletes, are children and adolescents with the needs of children and adolescents.
This study attempted to validate an anthropometric equation for predicting age at peak height velocity (APHV) in 193 Polish boys followed longitudinally 8-18 years (1961-1972). Actual APHV was ...derived with Preece-Baines Model 1. Predicted APHV was estimated at each observation using chronological age (CA), stature, mass, sitting height and estimated leg length. Mean predicted APHV increased from 8 to 18 years. Actual APHV was underestimated at younger ages and overestimated at older ages. Mean differences between predicted and actual APHV were reasonably stable between 13 and 15 years. Predicted APHV underestimated actual APHV 3 years before, was almost identical with actual age 2 years before, and then overestimated actual age through 3 years after PHV. Predicted APHV did not differ among boys of contrasting maturity status 8-11 years, but diverged among groups 12-15 years. In conclusion, predicted APHV is influenced by CA and by early and late timing of actual PHV. Predicted APHV has applicability among average maturing boys 12-16 years in contrast to late and early maturing boys. Dependence upon age and individual differences in actual APHV limits utility of predicted APHV in research with male youth athletes and in talent programmes.
The search for talent is pervasive in youth sports. Selection/exclusion in many sports follows a maturity-related gradient largely during the interval of puberty and growth spurt. As such, there is ...emphasis on methods for assessing maturation. Commonly used methods for assessing status (skeletal age, secondary sex characteristics) and estimating timing (ages at peak height velocity (PHV) and menarche) in youth athletes and two relatively recent anthropometric (non-invasive) methods (status-percentage of predicted near adult height attained at observation, timing-predicted maturity offset/age at PHV) are described and evaluated. The latter methods need further validation with athletes. Currently available data on the maturity status and timing of youth athletes are subsequently summarised. Selection for sport and potential maturity-related correlates are then discussed in the context of talent development and associated models. Talent development from novice to elite is superimposed on a constantly changing base-the processes of physical growth, biological maturation and behavioural development, which occur simultaneously and interact with each other. The processes which are highly individualised also interact with the demands of a sport per se and with involved adults (coaches, trainers, administrators, parents/guardians).
Inter-individual differences in size, maturity status, function, and behavior among youth of the same chronological age (CA) have long been a concern in grouping for sport. Bio-banding is a recent ...attempt to accommodate maturity-associated variation among youth in sport. The historical basis of the concept of maturity-matching and its relevance to youth sport, and bio-banding as currently applied are reviewed. Maturity matching in sport has often been noted but has not been systematically applied. Bio-banding is a recent iteration of maturity matching for grouping youth athletes into 'bands' or groups based on characteristic(s) other than CA. The percentage of predicted young adult height at the time of observation is the estimate of maturity status of choice. Several applications of bio-banding in youth soccer have indicated positive responses from players and coaches. Bio-banding reduces, but does not eliminate, maturity-associated variation. The potential utility of bio-banding for appropriate training loads, injury prevention, and fitness assessment merits closer attention, specifically during the interval of pubertal growth. The currently used height prediction equation requires further evaluation.
The health, fitness and other advantages of youth sports participation are well recognised. However, there are considerable challenges for all stakeholders involved-especially youth athletes-in ...trying to maintain inclusive, sustainable and enjoyable participation and success for all levels of individual athletic achievement. In an effort to advance a more unified, evidence-informed approach to youth athlete development, the IOC critically evaluated the current state of science and practice of youth athlete development and presented recommendations for developing healthy, resilient and capable youth athletes, while providing opportunities for all levels of sport participation and success. The IOC further challenges all youth and other sport governing bodies to embrace and implement these recommended guiding principles.
The contributions of height, weight and skeletal age (SA) to strength and motor performances of male soccer players 9-12 (n = 60) and 13-16 (n = 52) years were estimated. SA was assessed with the ...Fels method, and was expressed as the standardized residual of the regression of SA on chronological age CA (SAsr). Static strength (right + left grip), speed (5 m, 20 m sprints), acceleration (10 to 20 m), agility (figure-of-eight run), explosive strength (vertical jump) and endurance (yo-yo intermittent shuttle run, 13-16 years only) were measured. Hierarchical multiple regression was used. The interaction of SAsr with body size (height and height x weight interaction) explained most of the variance in strength in both age groups, 9-12 years (51.6%) and 13-16 years (56.7%), and in speed (31.4%, 38.7%), acceleration (39.6%), and explosive strength (32.6%) among players 13-16 years. In contrast, SAsr alone explained limited amounts of variance in strength, speed, acceleration and vertical jump among players 9-12 years (1.4-4.5%) and 13-16 years (0-0.5%). Results for agility varied with CA group, while SAsr per se was the primary contributor to endurance among players 13-16 years (18.5% of the variance). Although the influence of body size and skeletal maturity status on performances was significant, the explained variance differed among tasks and between CA groups, and suggested a role for other factors affecting performances of the soccer players.
Hindus and Muslims represent the two largest religions in India, and also differ in nutritional status, health-related habits and standard of living associated with economic disparities. In this ...context, the present study considered estimated secular changes in body size, proportions, and weight status among Hindu and Muslim Indian men. The data are from anthropological surveys in the 1970s which included measurements of height, weight and sitting height of 43,950 males 18-84 years (birth years 1891-1957). Leg length was estimated; the BMI and sitting height/height ratio were calculated. Heights of men 35 + years were adjusted for estimated height loss with age. Weight status was also classified relative to WHO criteria for the BMI. Anthropometric characteristics of the two groups were compared with MANCOVA with age and geographic region as covariates. Linear regression of height on year of birth was also used to estimate secular change in each group. Heights, weights, and BMIs tended to be, on average, greater among Muslim than Hindu men at most ages, while distributions by weight status between groups were negligible. Sitting height was greater among Muslim men but estimated leg length did not differ between groups; the sitting height/height ratio thus suggested proportionally shorter legs among Muslim men. Results of the regression analyses indicated negligible differences in secular change between groups across the total span of birth years but indicated a decline in adjusted heights of men in both groups born between 1891 through 1930s and little secular change among those born in the 1930s through 1957. The variation in heights, weights and BMIs between Muslim and Hindu men at most ages suggested variation in socio-economic status and dietary habits between the groups, whereas the negligible estimated secular changes in height between groups likely reflected economic, social, and nutritional conditions during the interval of British rule and the transition to independence.
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