Validation of maturity offset in a longitudinal sample of Polish girls

Abstract

This study attempted to validate an anthropometric equation for predicting age at peak height velocity (PHV) in 198 Polish girls followed longitudinally from 8 to 18 years. Maturity offset (years before or after PHV) was predicted from chronological age, mass, stature, sitting height and estimated leg length at each observation; predicted age at PHV was the difference between age and maturity offset. Actual age at PHV for each girl was derived with Preece–Baines Model 1. Predicted ages at PHV increased from 8 to16 years and varied relative to time before and after actual age at PHV. Predicted and actual ages at PHV did not differ at 9 years, but predicted overestimated actual age at PHV from 10 to 16 years. Girls of contrasting maturity status differed in predicted age at PHV from 8 to 14 years. In conclusion, predicted age at PHV is dependent upon age at prediction and individual differences in actual age at PHV, which limits its utility as an indicator of maturity timing in general and in sport talent programmes. It may have limited applicability as a categorical variable (pre-, post-PHV) among average maturing girls during the interval of the growth spurt, ~11.0–13.0 years.     

Growth and body composition in Brazilian female rhythmic gymnastics athletes

Abstract

The aim was to analyse the physical growth and body composition of rhythmic gymnastics athletes relative to their level of somatic maturation. This was a cross-sectional study of 136 athletes on 23 teams from Brazil. Mass, standing height and sitting height were measured. Fat-free and fat masses, body fat percentages and ages of the predicted peak height velocity (PHV) were calculated. The z scores for mass were negative during all ages according to both WHO and Brazilian references, and that for standing height were also negative for all ages according to WHO reference but only until 12 years old according to Brazilian reference. The mean age of the predicted PHV was 12.1 years. The mean mass, standing and sitting heights, body fat percentage, fat-free mass and fat mass increased significantly until 4 to 5 years after the age of the PHV. Menarche was reached in only 26% of these athletes and mean age was 13.2 years. The mass was below the national reference standards, and the standing height was below only for the international reference, but they also had late recovery of mass and standing height during puberty. In conclusion, these athletes had a potential to gain mass and standing height several years after PHV, indicating late maturation.     

Developmental changes and predictability of static strength in individuals of different maturity: A 30-year longitudinal study

Abstract

This longitudinal study analyses the development and predictability of static strength and their interactions with maturation in youth. Of 515 children followed annually from age 6 to 18 years, 59 males and 60 females were measured again at age 35. Early, average, and late maturity groups were established. Body height and mass were assessed. Static strength was measured using handgrip dynamometry. Pearson correlations were used as tracking coefficients. From 6 to 12 years of age, no static strength differences were found to exist between the maturity groups of both sexes. Static strength is significantly higher in early than in average and late maturing boys (age 13–16). In girls, a dose–response effect exists (age 11–14). Adult static strength predictability is low in early maturing boys and late maturing girls. It is moderate to high (50–76%) in the other maturity groups up to age 14. Predictors for adult static strength are childhood and adolescent handgrip dynamometry (in females only), medicine ball throw, sit-up, hockey ball throw, and 25-m sprint. Handgrip is a fair predictor of adult static strength at most ages in early and average maturing females; in average maturing males, it is a predictor at age 11. Other indicators of strength (e.g. hockey ball throw) are predictors in males.     

Anthropometric,physiological and maturational characteristics in selected elite and non-elite male adolescent basketball players

Abstract

We investigated the anthropometric, physiological and maturation characteristics of young players (13–14 years old) associated with being successful in basketball. Body parameters were measured (stature, total body mass, skinfolds and lengths) and physiological capacities were assessed by endurance, sprint (20 m), jump and dribbling tests. Chronological age (CA) was recorded and maturity estimated using predicted age at peak height velocity (APHV). Anthropometric analysis indicated that elite players were taller, heavier and had a higher percentage of muscle. Further, physiological testing showed that these elite players perform better in jump, endurance, speed and agility tests (especially in the agility and ball tests). In addition, these skills are correlated with point average during the regular season. More basketball players born in the first semester of the year are selected and there is a predominance of early-maturing boys among those selected for the elite team. Those who are more mature have advantages in anthropometric characteristics and physiological test results. In conclusion, around puberty, physical and physiological parameters associated with maturity and CA are important in determining the success of basketball players. These findings should be taken into account by trainers and coaches, to avoid artificial bias in their selection choices.     

Age and maturity related differences in motor coordination among male elite youth soccer players

This study investigated differences in generic and soccer specific motor coordination, as well as speed and agility depending on age and maturity in elite youth soccer players (U10-U15, N = 619). Measurements included body height, body weight and sitting height to estimate age at peak height velocity (APHV); three Körperkoordinationstest für Kinder subtests (i.e. jumping sideways (JS), moving sideways (MS), balancing backwards (BB)) to assess generic motor coordination; the UGent dribbling test for soccer specific motor coordination; a 5m/30m sprint and T-test for speed and agility, respectively. Age specific z-scores of the predicted APHV identified players as earlier, on time or later maturing. (M)ANOVA analyses showed significant age by maturity interaction effects for the speed and agility test cluster, revealing maturity related differences in U14 and U15 players. Next to an overall higher performance with age for all test clusters (η² 0.080–0.468), earlier maturing players outperformed their later maturing peers in 5m/30m sprinting. The opposite was seen for JS and BB. So, players’ maturity status should be taken into account to adequately value performance in talent identification. Also, the focus on characteristics that appear to be minimally biased by an earlier maturational timing (i.e. motor coordination) should be increased.     

Height,mass and skeletal maturity of elite Portuguese soccer players aged 11–16 years

Height, mass and skeletal maturity (Fels method) were assessed in 135 elite youth soccer players aged 10.7-16.5 years (only two boys were ?11.0 years). Sample sizes, years of training and current weekly training volume by two-year age groups were: 11-12 years ( n = 63), 2.6 - 1.0 years and 4.1 - 1.7 h; 13-14 years ( n = 29), 3.1 - 1.6 years and 4.5 - 1.7 h; 15-16 years ( n = 43), 4.7 - 2.4 years and 6.1 - 2.0 h. The oldest age group included membersof the national youth team.Heights and masses were compared to US reference values,and skeletal age and chronological age were contrasted. The players were also classified as late, average ('on time') and early maturers on the basis of differences between skeletal and chronological age, with the average category including boys with skeletal ages within - 1 year of chronological age. The mean heights and masses of 11- to 12-year-old soccer players equalled the US reference values, while those of players aged 13-14 and 15-16 years were slightly above the reference values. The mean skeletal age approximated mean chronological age in players aged 11-12 years (12.4 - 1.3 and 12.3 - 0.5 years, respectively), while mean skeletal age was in advance of mean chronological age in the two older groups (14.3 - 1.2 and 13.6 - 0.7 years, respectively, in 13- to 14-year-olds; 16.7 - 1.0 and 15.8 - 0.4 years, respectively, in 15- to 16-year-olds). Seven boys in the oldest age group were already skeletally mature and were not included when calculating differences between skeletal and chronological age. The proportion of late maturing boys in this sample of elite soccer players decreased with increasing chronological age. Among 11- to 12-year-old players, the percentages of late and early maturing boys were equal at 21% ( n = 13). Among 13- to 14-year-old players, the percentages of late and early maturing boys were 7% ( n = 2) and 38% ( n = 11) respectively, while among players aged 15-16 years the percentages of late and early maturing boys were 2% ( n = 1) and 65% ( n = 28) respectively. The results of this comparative analysis suggest that the sport of soccer systematically excludes late maturing boys and favours average and early maturing boys as chronological age and sport specialization increase. It is also possible that late maturing boys selectively drop-out of soccer as age and sport specialization increase.     

Height, mass and skeletal maturity of elite Portuguese soccer players aged 11-16 years

Height, mass and skeletal maturity (Fels method) were assessed in 135 elite youth soccer players aged 10.7-16.5 years (only two boys were < 11.0 years). Sample sizes, years of training and current weekly training volume by two-year age groups were: 11-12 years (n = 63), 2.6 +/- 1.0 years and 4.1 +/- 1.7 h; 13-14 years (n = 29), 3.1 +/- 1.6 years and 4.5 +/- 1.7 h; 15-16 years (n = 43), 4.7 +/- 2.4 years and 6.1 +/- 2.0 h. The oldest age group included members of the national youth team. Heights and masses were compared to US reference values, and skeletal age and chronological age were contrasted. The players were also classified as late, average ('on time') and early maturers on the basis of differences between skeletal and chronological age, with the average category including boys with skeletal ages within +/- 1 year of chronological age. The mean heights and masses of 11- to 12-year-old soccer players equalled the US reference values, while those of players aged 13-14 and 15-16 years were slightly above the reference values. The mean skeletal age approximated mean chronological age in players aged 11-12 years (12.4 +/- 1.3 and 12.3 +/- 0.5 years, respectively), while mean skeletal age was in advance of mean chronological age in the two older groups (14.3 +/- 1.2 and 13.6 +/- 0.7 years, respectively, in 13- to 14-year-olds; 16.7 +/- 1.0 and 15.8 +/- 0.4 years, respectively, in 15- to 16-year-olds). Seven boys in the oldest age group were already skeletally mature and were not included when calculating differences between skeletal and chronological age. The proportion of late maturing boys in this sample of elite soccer players decreased with increasing chronological age. Among 11- to 12-year-old players, the percentages of late and early maturing boys were equal at 21% (n = 13). Among 13- to 14-year-old players, the percentages of late and early maturing boys were 7% (n = 2) and 38% (n = 11) respectively, while among players aged 15-16 years the percentages of late and early maturing boys were 2% (n = 1) and 65% (n = 28) respectively. The results of this comparative analysis suggest that the sport of soccer systematically excludes late maturing boys and favours average and early maturing boys as chronological age and sport specialization increase. It is also possible that late maturing boys selectively drop-out of soccer as age and sport specialization increase.     

Growth and maturity status of elite British junior tennis players

Growth and maturation impact the selection, development and progression of youth athletes. Individual differences in the growth and maturity may afford a performance advantage, clouding coaches and practitioners’ perceptions regarding current ability and future potential. This may result in the exclusion of talented, yet less physically gifted athletes. Participants were 91 male (n = 47) and female (n = 44) elite British Junior tennis players, 8–17 years of age (12.5 ± 1.9 years). Height and body mass were measured and compared to growth charts; hand-wrist radiographs were taken. Skeletal age (SA) was estimated with the Fels method and contrasted to chronological age (CA). Mean height and body mass of individual players ranged between the 50th and 90th centiles for age and sex. Females were advanced in SA relative to CA (0.3–0.89 years.) from 8 years. Males were average to delayed in maturation from 8 to 12 years, but advanced in SA from 14 to 16 years (0.75–1.23 years). Individual differences in growth and maturation appear to contribute towards the selection of elite junior tennis players, with a bias towards males and females who are advanced in maturation and comparatively tall and heavy for their age. This has important implications for talent identification and development.     

Gross Motor Competence and Peak Height Velocity in 10- to 14-Year-Old Canadian Youth: A Longitudinal Study

The objective of this study was to evaluate gross motor competence and growth spurt in Canadian youth. Eighty-two children (38 boys, 44 girls) were assessed over a time period of five years. Growth rate was measured quarterly; motor competence was evaluated once per year using the Bruininks-Oseretsky Test of Motor Proficiency. Peak height velocity (PHV) occurred at a significantly younger age in the girls (11.3 ± 0.4 years) than the boys (13.4 ± 0.3 years; p < .001), and growth rate during PHV was significantly greater in the boys than the girls (2.8 ± 1.3 vs. 2.0 ± 0.7 cm/quarter; p = .003). Gross motor competence outcomes were significantly above the North American normative scores (p < .05) over the measured time period. After the occurrence of PHV, strength, strength/agility, and gross motor skill significantly decreased in girls (p < .01), and running speed/agility significantly decreased in boys (p < .05). This finding emphasizes that motor competence in pre-adolescent children may suddenly decrease after their growth spurt.     

Relative age and maturation selection biases in academy football

ABSTRACT

This study examined the simultaneous effects of relative age and biological maturity status upon player selection in an English professional soccer academy. A total of 202 players from the U9 to U16 age groups, over an eight-year period (total of 566 observations), had their relative age (birth quarter) and biological maturity (categorised as late, on-time or early maturing based upon the Khamis-Roche method of percentage of predicted adult height at time of observation) recorded. Players born in the first birth quarter of the year (54.8%) were over-represented across all age groups. A selection bias towards players advanced in maturity status for chronological age emerged in U12 players and increased with age; 0% of players in the U15 and U16 age group were categorised as late maturing. A clear maturity selection bias for early maturing players was, however, only apparent when the least conservative criterion for estimating maturity status was applied (53.8% early and 1.9% late maturing in the U16 age group). Professional football academies need to recognise relative age and maturation as independent constructs that exist and operate independently. Thus, separate strategies should perhaps be designed to address the respective selection biases, to better identify, retain and develop players.     

Evaluating the Prediction of Maximal Heart Rate in Children and Adolescents

In this study, we compared measured maximal heart rate (HRmax) to two different HRmax prediction equations [220 — age and 208 — 0.7(age)] in 52 children ages 7-17 years. We determined the relationship of chronological age, maturational age, and resting HR to measured HRmax and assessed seated resting HR and HRmax during a graded exercise test. Maturational age was calculated as the maturity offset in years from the estimated age at peak height velocity. Measured HRmax was 201 ± 10 bpm, whereas predicted HRmax ranged from 199 to 208 bpm. Measured HRmax and the predicted value from the 208 — 0.7(age) prediction were similar but lower (p < .05) than the 220 — age prediction. Absolute differences between measured and predicted HRmax were 8 ± 5 and 10 ± 8 bpm for the 208 — 0.7 (age) and 220 — age equations, respectively, and were greater than zero (p < .05). Regression equations using resting HR and maturity offset or chronological age significantly predicted HRmax, although the R2 < .30 and the standard error of estimation (8.2-8.5) limits the accuracy. The 208 — 0.7(age) equation can closely predict mean HRmax in children, but individual variation is still apparent.     

Prized Performers,but Frequently Overlooked Students: The Involvement of Black Athletes in Intercollegiate Sports on Predominantly White University Campuses, 1890-1972

This review assembles pedometry literature focused on youth, with particular attention to expected values for habitual, school day, physical education class, recess, lunch break, out-of-school, weekend, and vacation activity. From 31 studies published since 1999, we constructed a youth habitual activity step-curve that indicates: (a) from ages 6 to 18 years, boys typically take more steps per day than girls; (b) for both sexes the youngest age groups appear to take fewer steps per day than those immediately older; and (c) from a young age, boys decline more in steps per day to become more consistent with girls at older ages. Additional studies revealed that boys take approximately 42–49% of daily steps during the school day; girls take 41–47%. Steps taken during physical education class contribute to total steps per day by 8.7–23.7% in boys and 11.4–17.2% in girls. Recess represents 8–11% and lunch break represents 15–16% of total steps per day. After-school activity contributes approximately 47–56% of total steps per day for boys and 47–59% for girls. Weekdays range from approximately 12,000 to 16,000 steps per day in boys and 10,000 to 14,000 steps per day in girls. The corresponding values for weekend days are 12,000–13,000 steps per day in boys and 10,000–12,000 steps per day in girls.     

Evaluating the prediction of maximal heart rate in children and adolescents

In this study, we compared measured maximal heart rate (HRmax) to two different HRmax prediction equations [22 - age and 208 - 0.7(age)] in 52 children ages 7-17 years. We determined the relationship of chronological age, maturational age, and resting HR to measured HRmax and assessed seated resting HR and HRmax during a graded exercise test. Maturational age was calculated as the maturity offset in years from the estimated age at peak height velocity. Measured HRmax was 201 +/- 10 bpm, whereas predicted HRmax ranged from 199 to 208 bpm. Measured HRmax and the predicted value from the 208 - 0.7(age) prediction were similar but lower (p < .05) than the 220 - age prediction. Absolute differences between measured and predicted HRmax were 8 +/- 5 and 10 +/- 8 bpm for the 208 - 0.7 (age) and 220 - age equations, respectively, and were greater than zero (p < .05). Regression equations using resting HR and maturity offset or chronological age significantly predicted HRmax, although the R2 < .30 and the standard error of estimation (8.2-8.5) limits the accuracy. The 208 - 0.7(age) equation can closely predict mean HRmax in children, but individual variation is still apparent.     

Prediction of adult height in girls: The Beunen-Malina-Freitas method

Abstract

The purpose of this study was to validate and cross-validate the Beunen-Malina-Freitas method for non-invasive prediction of adult height in girls. A sample of 420 girls aged 10–15 years from the Madeira Growth Study were measured at yearly intervals and then 8 years later. Anthropometric dimensions (lengths, breadths, circumferences, and skinfolds) were measured; skeletal age was assessed using the Tanner-Whitehouse 3 method and menarcheal status (present or absent) was recorded. Adult height was measured and predicted using stepwise, forward, and maximum R ² regression techniques. Multiple correlations, mean differences, standard errors of prediction, and error boundaries were calculated. A sample of the Leuven Longitudinal Twin Study was used to cross-validate the regressions. Age-specific coefficients of determination (R ²) between predicted and measured adult height varied between 0.57 and 0.96, while standard errors of prediction varied between 1.1 and 3.9 cm. The cross-validation confirmed the validity of the Beunen-Malina-Freitas method in girls aged 12–15 years, but at lower ages the cross-validation was less consistent. We conclude that the Beunen-Malina-Freitas method is valid for the prediction of adult height in girls aged 12–15 years. It is applicable to European populations or populations of European ancestry.     

Determination of thigh volume in youth with anthropometry and DXA: Agreement between estimates

Abstract

This study examined the agreement between estimates of thigh volume (TV) with anthropometry and dual-energy x-ray absorptiometry (DXA) in healthy school children. Participants (n=168, 83 boys and 85 girls) were school children 10.0–13.9 years of age. In addition to body mass, height and sitting height, anthropometric dimensions included those needed to estimate TV using the equation of Jones & Pearson. Total TV was also estimated with DXA. Agreement between protocols was examined using linear least products regression (Deming regressions). Stepwise regression of log-transformed variables identified variables that best predicted TV estimated by DXA. The regression models were then internally validated using the predicted residual sum of squares method. Correlation between estimates of TV was 0.846 (95%CI: 0.796–0.884, S_y·x=0.152L). It was possible to obtain an anthropometry-based model to improve the prediction of TVs in youth. The total volume by DXA was best predicted by adding body mass and sum of skinfolds to volume estimated with the equation of Jones & Pearson (R=0.972; 95%CI: 0.962–0.979; R ²=0.945).     

The 1991 C. H. McCloy Research Lecture: Unraveling the Mystery of the Response Complexity Effect in Skilled Movements

Abstract

From the records in three track-and-field events (standing broad jump, softball throw, and six-second run), the ages, the heights, and the weights were obtained from 882 boys and 900 girls ranging in ages from 9 to 17 years. The relationship between ability in athletics (as measured by the records in the three track-and-field events) and the variables of age, height, and weight was, for the boys and for the girls, found to be nonlinear.     

Isokinetic Torque in Boys and Girls Ages 7 to 13: Effect of Age,Height, and Weight

The purpose of this study was to investigate torque differences between 28 boys and 28 girls, ages 7 to 13 years, for the knee and elbow flexor and extensors at 30°/second and 120°/second using an isokinetic procedure (Cybex II). In addition, the relationships of these torque levels to size and age were determined. The results revealed significant (p < .05) sex differences for the knee flexor and extensor torque values at 120°/second independent of body weight. That is, the boys generated 29.2 and 39.5 foot pounds vs. the girl's 26.2 and 35.4 foot pounds for knee flexion and extension, respectively. Similarly, torque differences (p < .05) between boys and girls were present for elbow extension at 120°/second when adjusting for differences in height. When examining the flexion/extension ratios, it is apparent that increases in body size (height, weight) and age had a significant effect on the ratio at 120°/second but not at 30°/second.     

Identifying profiles of actual and perceived motor competence among adolescents: associations with motivation,physical activity,and sports participation

The present study identified adolescents’ motor competence (MC)-based profiles (e.g., high actual and low perceived MC), and accordingly investigated differences in motivation for physical education (PE), physical activity (PA) levels, and sports participation between profiles by using regression analyses. Actual MC was measured with the Körperkoordinationstest für Kinder. Adolescents (n = 215; 66.0% boys; mean age = 13.64 ± .58 years) completed validated questionnaires to assess perceived MC, motivation for PE, PA-levels, and sports participation. Actual and perceived MC were only moderately correlated and cluster analyses identified four groups. Two groups of overestimators (low – overestimation, average – overestimation) were identified (51%), who particularly displayed better motivation for PE when compared to their peers who accurately estimated themselves (low – accurate, average – accurate). Moreover, adolescents with low actual MC, but high perceived MC were significantly more active than adolescents with low actual MC who accurately estimated themselves. Results pointed in the same direction for organised sports participation. Underestimators were not found in the current sample, which is positive as underestimation might negatively influence adolescents’ motivation to achieve and persist in PA and sports. In conclusion, results emphasise that developing perceived MC, especially among adolescents with low levels of actual MC, seems crucial to stimulate motivation for PE, and engagement in PA and sports.     

Vertical Jump and Leg Power Norms for Young Adults

Medical students and their spouses (N= 724) served as participants to create norm-referenced vertical jump values for active, healthy people ages 21–30. All tests were conducted and measured by thesameindividual during a campus fitness evaluation using a Vertec^TM apparatus.Jumpheightwas measured to the nearest 0.5 in.Meanjump height was similar throughout this age range within each gender. Mean jump scores, for men were 21–25 years = 22.2±3.5; 26–30 years = 21.9±3.3; and for women were 21–25 years = 14.1±2.5; 26–30 years = 14.0±2.4. From jump data, power and peak power were calculated. In this group of active individuals in their 20s, no decline in vertical jump success or power outputwas found between 21–25 and 26–30 year old groups.A table of norm-referenced values, based on percentiles,was developed that will be useful in comparing normal, active individuals in this age group to select individuals for whom leg power is an important performance measure.     

Biological maturity and primary school children's physical activity: Influence of different physical activity assessment instruments

Abstract

Biological maturation may attenuate hypothesized sex differences in children's physical activity but overall the evidence for this is equivocal. In this study, we investigated how the selection of different physical activity assessment instruments affects the detected relationship between biological maturation and late primary school children's physical activity. Altogether, 175 children (97 girls, 78 boys) aged 10.6±0.3 years completed the PAQ-C self-report questionnaire and wore ActiGraph GT1M accelerometers for 5 consecutive days. Maturity status was predicted by estimating attainment of age at peak height velocity. Following initial exploration of sex differences in PAQ-C (t-test) and multiple ActiGraph outcome variables (MANOVA), the influence of maturity status was controlled using ANCOVA and MANCOVA. Unadjusted analyses revealed that boys were significantly more active than girls according to the PAQ-C (P<0.0001, d=0.52) and ActiGraph (P<0.0001, d=0.36–0.72). After controlling for maturity status, the differences in PAQ-C scores increased (P=0.001, d=0.64), but the significant differences disappeared for the ActiGraph data (P=0.36, d=0.17–0.33). The detected relationship between maturity status and late primary school children's physical activity is dependent on the physical activity assessment tool employed, reflecting the different aspects of physical activity captured by the respective measures.