Enhancing a Somatic Maturity Prediction Model

Moore, Sarah A.; McKay, Heather; Macdonald, Heather M.; Nettlefold, Lindsay; Baxter-Jones, Adam D.G.; Cameron, Noël; Brasher, Penelope M. A.

doi:10.1249/mss.0000000000000588

Cited by 446 publications

(479 citation statements)

References 23 publications

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“…The study also used a validated estimator of somatic maturity (i.e. years from PHV [maturity offset]), which has recently been revalidated [38], rather than relying on self-reported stage of sexual maturation. However, the study also possesses limitations.…”

Section: Discussionmentioning

confidence: 99%

Progressive skeletal benefits of physical activity when young as assessed at the midshaft humerus in male baseball players

et al. 2017

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Purpose: The current study explored physical activity-induced bone adaptation at different stages of somatic maturity by comparing side-to-side differences in midshaft humerus properties between male throwing athletes and controls. Throwers present an internally controlled model, while inclusion of control subjects removes normal arm dominance influences. Methods: Throwing athletes (n=90) and controls (n=51) were categorized into maturity groups (PRE, PERI, POST-EARLY, POST-MID and POST-LATE) based on estimated years from peak height velocity (<−2, −2-to-2, 2-to-4, 4-to-10 and >10 years). Side-to-side percent differences in midshaft humerus cortical volumetric bone mineral density (Ct.vBMD) and bone mineral content (Ct.BMC), total (Tt.Ar), medullary (Me.Ar) and cortical (Ct.Ar) area, average cortical thickness (Ct.Th), and polar Strength Strain Index (SSIP) was assessed. Results: Significant interactions between physical activity and maturity on side-to-side differences in Ct.BMC, Tt.Ar, Ct.Ar, Me.Ar, Ct.Th and SSIP resulted from: 1) greater throwing-to-nonthrowing arm differences than dominant-to-nondominant arm differences in controls (all p<0.05), and; 2) throwing-to-nonthrowing arm differences in throwers being progressively greater across maturity groups (all p<0.05). Regional analyses revealed greatest adaptation in medial and lateral sectors, particularly in the three POST maturity groups. Years throwing predicted 59% of the variance of the variance in throwing-to-nonthrowing arm difference in SSIP (p<0.001). Conclusion: These data suggest physical activity has skeletal benefits beginning prior to and continuing beyond somatic maturation, and that a longer duration of exposure to physical activity has cumulative skeletal benefits. Thus, physical activity should be encouraged at the earliest age possible and be continued into early adulthood to optimize skeletal benefits.

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Section: Discussionmentioning

confidence: 99%

Progressive skeletal benefits of physical activity when young as assessed at the midshaft humerus in male baseball players

et al. 2017

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“…BMI z-scores were assigned [32] and age and sex specific BMI cut points established children as normal weight or overweight/obese (those who were underweight were grouped into the normal weight category) [33]. Gender-specific equations were used to predict children′s age from peak height velocity (APHV), as a proxy measure of biological maturation [34]. Waist circumference was measured to the nearest 0.1 cm using an anthropometric tape measure, and the percentage of waist circumference-to-height ratio (%WHtR) was calculated as a measure of central adiposity [35].…”

Section: Methodsmentioning

confidence: 99%

Predictors of Segmented School Day Physical Activity and Sedentary Time in Children from a Northwest England Low-Income Community

Taylor

Curry

Knowles

et al. 2017

IJERPH

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Background: Schools have been identified as important settings for health promotion through physical activity participation, particularly as children are insufficiently active for health. The aim of this study was to investigate the child and school-level influences on children′s physical activity levels and sedentary time during school hours in a sample of children from a low-income community; Methods: One hundred and eighty-six children (110 boys) aged 9–10 years wore accelerometers for 7 days, with 169 meeting the inclusion criteria of 16 h∙day−1 for a minimum of three week days. Multilevel prediction models were constructed to identify significant predictors of sedentary time, light, and moderate to vigorous physical activity during school hour segments. Child-level predictors (sex, weight status, maturity offset, cardiorespiratory fitness, physical activity self-efficacy, physical activity enjoyment) and school-level predictors (number on roll, playground area, provision score) were entered into the models; Results: Maturity offset, fitness, weight status, waist circumference-to-height ratio, sedentary time, moderate to vigorous physical activity, number of children on roll and playground area significantly predicted physical activity and sedentary time; Conclusions: Research should move towards considering context-specific physical activity and its correlates to better inform intervention strategies.

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“…This appears to be useful near the time of actual PHV in average maturing boys within a narrow CA range, 13.00–14.99 years,21 32 which limits its utility with male athletes who tend to mature early 19. The protocol appears to overestimate age at PHV in girls more than in boys,22 31 which may limit its use.…”

Section: Assessment Of Maturity Status and Timingmentioning

confidence: 99%

Biological maturation of youth athletes: assessment and implications

Malina¹,

et al. 2015

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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).

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Enhancing a Somatic Maturity Prediction Model

Abstract: Our equations provided good fits in external samples and provide an alternative to commonly used models. Original prediction equations were simplified with no meaningful increase in estimation error.

Cited by 446 publications

References 23 publications

Progressive skeletal benefits of physical activity when young as assessed at the midshaft humerus in male baseball players

Progressive skeletal benefits of physical activity when young as assessed at the midshaft humerus in male baseball players

Predictors of Segmented School Day Physical Activity and Sedentary Time in Children from a Northwest England Low-Income Community

Biological maturation of youth athletes: assessment and implications

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