Modelling height in adolescence: a comparison of methods for estimating the age at peak height velocity

Cross-sectional associations between physical activity and sedentary time with cardiovascular health in children from the ALSPAC study using compositional data analysis

This study adopted a compositional framework to cross-sectionally examine the associations between physical activity (PA) and sedentary time (ST) with vascular structure and function and clustered cardiovascular disease (CVD) risk factors in 4277 children (2,226 girls), aged 10.6±0.2 years. Cardiovascular outcomes included flow mediated dilation, distensibility coefficient, pulse wave velocity and a clustered CVD risk factor score. Time spent in light PA (LPA) and moderate to vigorous PA (MVPA) and ST were determined using accelerometers. Multiple linear regression analyses were adjusted for key covariates with LPA, MVPA and ST entered as compositional exposure variables. Neither LPA, MVPA or ST were significantly associated with the vascular outcomes. The proportion of time spent in MVPA and ST were inversely (unstandardised b=-0.126; P=0.001) and positively (b=0.136; P=0.016) associated with clustered CVD risk in the whole group analysis, respectively. MVPA was negatively associated with clustered CVD risk in boys (b=-0.144; P=0.011) and girls (b=-0.110; P=0.032). Only girls had a positive association between ST and clustered CVD risk (b=0.199; P=0.005). Although no associations were observed for PA and ST with vascular outcomes, these data provide further support for interventions that promote MVPA and minimise ST for reducing risk factors for CVD in children.

Height Growth Modeling in Ethiopian Children and Adolescents Aged 7-20 Years: A Prospective Cohort Study

Background: Modeling physical growth plays a vital role in examining and defining growth trajectories related to public health and well-being. Aim: The primary objective of this study was to model height growth in Ethiopian children and adolescents aged 7-20 years to estimate the growth variations across the Ethiopian regions. Methods: A total of 891 children and adolescents aged 7.5-20 years were included in the study. To estimate growth spurts within and between study subjects over time, the SITAR and PB1 models were fitted to the height growth measurements gathered in four survey rounds to. Results: Boys experienced puberty 2.6 years later than girls did, while the mean peak height velocity was estimated to be 5.5 cm/year in boys and 6.3 cm/year in girls. The mean adult height in boys was estimated to be 174.6 cm, while in girls, it was estimated to be 162.2 cm. Both girls (p < 0.005) and boys (p < 0.008) in Amhara and Tigrai regions were significantly shorter compared to their counterparts in Addis Ababa. However, there was no significant height difference between girls and boys in former SNNPRS region, Oromia region, and Addis Ababa. Height at peak velocity strongly correlated with the rate of change during the pubertal period. The rate of change in both boys and girls during the prepubertal and pubertal growth stages was inversely correlated with the adult height. Conclusions: Children who had rapid rate of change during the prepubertal and pubertal periods attained adulthood later in life. There was a significantly different height growth in children and adolescents across the regions of Ethiopia.

Advancing Pediatric Growth Assessment with Machine Learning: Overcoming Challenges in Early Diagnosis and Monitoring

BACKGROUND

Pediatric growth assessment is crucial for early diagnosis and intervention in growth disorders. Traditional methods often lack accuracy and real-time decision-making capabilities This study explores the application of machine learning (ML), particularly logistic regression, to improve diagnostic precision and timeliness in pediatric growth assessment. Logistic regression is a reliable and easily interpretable model for detecting growth abnormalities in children. Unlike complex machine learning models, it offers parsimony in transparency, efficiency, and reproducibility, making it ideal for clinical settings where explainable, data-driven decisions are essential.

METHODS

A logistic regression model was developed using R to analyze biometric and demographic data from a cross-sectional dataset, including real-world data from public institucions. The study employed a bibliometric analysis to identify key trends and incorporated data preprocessing techniques such as cleaning, imputation, and feature selection to enhance model performance. Performance metrics, including accuracy, sensitivity, and the Receiver Operating Characteristic (ROC) curve, were utilized for evaluation.

RESULTS

The logistic regression model demonstrated an accuracy of 94.65% and a sensitivity of 91.03%, significantly improving the identification of growth anomalies compared to conventional assessment methods. The model's ROC curve showed an area under the curve (AUC) of 0.96, indicating excellent predictive capability. Findings highlight ML's potential in automating pediatric growth monitoring and supporting clinical decision-making, as it can be very simple and highly interpretable in clinical practice.

CONCLUSIONS

ML, particularly logistic regression, offers a promising tool for pediatric healthcare by enhancing diagnostic precision and operational efficiency. Despite these advancements, challenges remain regarding data quality, clinical integration, and privacy concerns. Future research should focus on expanding dataset diversity, improving model interpretability, and conducting external validation to facilitate broader clinical adoption.

Age at peak height velocity in Polish adolescents: Effect of socioeconomic factors

Age at peak height velocity (APHV) is an indicator of maturity timing which is applicable to both sexes, and which is influenced by environmental factors. The objective of this study was to assess variation in APHV associated with several indicators of socioeconomic status (SES) in a longitudinal sample of Polish adolescents. The sample included 739 boys born in 1983 and followed annually from 12 to 16 years, and 597 girls born in 1985 and followed annually from 9 to 13 years. The height records were fitted with the SITAR model to estimate APHV. SES was estimated using principal component analysis of indicators of familial status based on parental education, family size, living conditions and household possessions. Statistical analyses included analysis of variance (one-way for general SES and three-way for parental education and family size) and Tukey post-hoc tests for unequal samples. General SES (p <.001) and family size (p < .05) significantly influenced APHV among boys, while only maternal education (p < .05) significantly influenced APHV among girls. Among youth from families of higher SES, as defined by the respective indicators, APHV was attained significantly earlier, on average, than in peers from families of lower SES. Overall, the results showed a sex-dependent effect of SES on APHV, and highlighted the influence of favorable socioeconomic conditions for optimal growth and maturation during adolescence.

Estimating Maturity Status in Elite Youth Soccer Players: Evaluation of Methods

PURPOSE

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.

METHODS

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.

RESULTS

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.

CONCLUSIONS

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.

Novel signals and polygenic score for height are associated with pubertal growth traits in Southwestern American Indians

Most genetic variants associated with adult height have been identified through large genome-wide association studies (GWASs) in European-ancestry cohorts. However, it is unclear how these variants influence linear growth during adolescence. This study uses anthropometric and genotypic data from a longitudinal study conducted in an American Indian community in Arizona between 1965-2007. Growth parameters (i.e. height, velocity, and timing of growth spurt) were derived from the Preece-Baines growth model, a parametric growth curve fitted to longitudinal height data, in 787 participants with height measurements spanning the whole period of growth. Heritability estimates suggested that genetic factors could explain 25% to 71% of the variance of pubertal growth traits. We performed a GWAS of growth parameters, testing their associations with 5 077 595 imputed or directly genotyped variants. Six variants associated with height at peak velocity (P < 5 × 10-8, adjusted for sex, birth year and principal components). Implicated genes include NUDT3, previously associated with adult height, and PACSIN1. Two novel variants associated with duration of growth spurt (P < 5 × 10-8) in LOC105375344, an uncharacterized gene with unknown function. We finally examined the association of growth parameters with a polygenic score for height derived from 9557 single nucleotide polymorphisms (SNPs) identified in the GIANT meta-analysis for which genotypic data were available for the American Indian study population. Height polygenic score was correlated with the magnitude and velocity of height growth that occurred before and at the peak of the adolescent growth spurt, indicating overlapping genetic architecture, with no influence on the timing of adolescent growth.

Longitudinal Meta-Analysis of Peak Height Velocity in Young Female Athletes

Growth patterns and biological milestones in youth sports are key to interpreting the development of young athletes. However, there is no analysis of longitudinal meta-analysis describing the growth of young female athletes. This longitudinal meta-analysis estimated growth curves and age at peak height velocity (PHV) in young female athletes based on anthropometric data from longitudinal studies found in the literature. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, studies with repeated measurements in young female athletes were identified from searches of four databases (MEDLINE, Web of Science, SCOPUS, and SPORTDiscus) without date restrictions through August 2023. We adapted our bias assessment criteria using the Cochrane risk of bias tool for randomized controlled trials as a reference. Bayesian multilevel modeling was used to perform a longitudinal meta-analysis to extract stature growth curves and age at PHV. Fourteen studies met our eligibility criteria. Twenty-one independent samples could be included in the analysis. Conditional on the data and models, the predicted mean age at PHV for female athletes was 11.18 years (90% CI: 8.62; 12.94). When studies were aggregated by sport in the models, the models could not capture sport-specific growth curves for stature and estimate a corresponding age at PHV. We provide the first longitudinal meta-analytic summary of pubertal growth and derive age at PHV in young female athletes. The meta-analysis predicted that age at PHV occurs at similar ages to those in the general pediatric population. The data pool was limited in sports and geographic distribution, emphasizing the need to promote longitudinal research in females across different youth sports contexts.

Trans-ancestral genome-wide association study of longitudinal pubertal height growth and shared heritability with adult health outcomes

BACKGROUND

Pubertal growth patterns correlate with future health outcomes. However, the genetic mechanisms mediating growth trajectories remain largely unknown. Here, we modeled longitudinal height growth with Super-Imposition by Translation And Rotation (SITAR) growth curve analysis on ~ 56,000 trans-ancestry samples with repeated height measurements from age 5 years to adulthood. We performed genetic analysis on six phenotypes representing the magnitude, timing, and intensity of the pubertal growth spurt. To investigate the lifelong impact of genetic variants associated with pubertal growth trajectories, we performed genetic correlation analyses and phenome-wide association studies in the Penn Medicine BioBank and the UK Biobank.

RESULTS

Large-scale growth modeling enables an unprecedented view of adolescent growth across contemporary and 20th-century pediatric cohorts. We identify 26 genome-wide significant loci and leverage trans-ancestry data to perform fine-mapping. Our data reveals genetic relationships between pediatric height growth and health across the life course, with different growth trajectories correlated with different outcomes. For instance, a faster tempo of pubertal growth correlates with higher bone mineral density, HOMA-IR, fasting insulin, type 2 diabetes, and lung cancer, whereas being taller at early puberty, taller across puberty, and having quicker pubertal growth were associated with higher risk for atrial fibrillation.

CONCLUSION

We report novel genetic associations with the tempo of pubertal growth and find that genetic determinants of growth are correlated with reproductive, glycemic, respiratory, and cardiac traits in adulthood. These results aid in identifying specific growth trajectories impacting lifelong health and show that there may not be a single "optimal" pubertal growth pattern.

Preece-Baines 1 model validation for cross-sectional data in male soccer players according to maturity status

AIM

The aim of the present study was to compare the Preece-Baines 1 (PB1) model fit between longitudinal and cross-sectional data in male soccer players and to adjust the height growth curve by maturity status.

METHODS

A final sample of 57 male Portuguese soccer players from professional soccer academies was included. Longitudinal height records were measured between 8 and 17 times in each subject from 2-8 years to 14-17 years. Additionally, longitudinal height records were used as cross-sectional data along with 1087 cross-sectional height records taken from 602 Portuguese soccer players. Skeletal age was estimated by Tanner-Whitehouse III method from a left hand-wrist radiograph. Age at peak height velocity (PHV) was estimated by PB1 model for longitudinal and cross-sectional data and by maturity status.

RESULTS

No significant differences were found between all the longitudinal estimates of 57 players and the random cross-sectional samples for, S1 parameter and for growth velocity at PHV, at TO, and for age at PHV. The age at PHV in early, on-time, and late maturers were 12.26, 12.9, and 13.58 years, respectively.

CONCLUSION

PB1 adjusted the height growth of Portuguese male soccer players from cross-sectional data, obtaining an estimate PHV very similar to that found from longitudinal data. A maturity time difference of ≈0.6 years was found between the age at PHV of on-time, early, and on-time and late maturity state.

A Longitudinal Study of the Physical Characteristics, Muscle-Tendon Structure Properties, and Skeletal Age in Preadolescent Boys

OBJECTIVES

The purpose of this study was to examine longitudinal growth changes in physical characteristics, muscle-tendon structure properties, and skeletal age in preadolescent boys and to compare the relationship between the changes in physical characteristics and muscle-tendon properties and the changes in chronological and skeletal ages.

METHODS

Fourteen prepubescent boys (10.9 ± 1.1 years old at the onset of the study) participated in this study over two years (yearly). Maximal muscle strength and maximal strain of tendon structure during ramp isometric contraction and muscle and tendon thickness for knee extensors and plantar flexors were measured. In addition, skeletal age was assessed using Tanner-Whitehouse three method.

RESULTS

Changes in height, thigh length, and lower leg length were highly correlated with changes in skeletal age but not chronological age. However, changes in the morphological and mechanical properties of muscle and tendon structure were not significantly associated with changes in chronological and skeletal ages.

CONCLUSION

The present preliminary results suggest that longitudinal growth changes in the long-axis of the body are highly correlated with skeletal age change, whereas those in the muscle-tendon structure properties were not.

Cross-sectional data accurately model longitudinal growth in the craniofacial skeleton

Dense, longitudinal sampling represents the ideal for studying biological growth. However, longitudinal samples are not typically possible, due to limits of time, prohibitive cost, or health concerns of repeat radiologic imaging. In contrast, cross-sectional samples have few such drawbacks, but it is not known how well estimates of growth milestones can be obtained from cross-sectional samples. The Craniofacial Growth Consortium Study (CGCS) contains longitudinal growth data for approximately 2000 individuals. Single samples from the CGCS for individuals representing cross-sectional data were used to test the ability to predict growth parameters in linear trait measurements separately by sex. Testing across a range of cross-sectional sample sizes from 5 to the full sample, we found that means from repeated samples were able to approximate growth rates determined from the full longitudinal CGCS sample, with mean absolute differences below 1 mm at cross-sectional sample sizes greater than ~ 200 individuals. Our results show that growth parameters and milestones can be accurately estimated from cross-sectional data compared to population-level estimates from complete longitudinal data, underscoring the utility of such datasets in growth modeling. This method can be applied to other forms of growth (e.g., stature) and to cases in which repeated radiographs are not feasible (e.g., cone-beam CT).

Adolescent Growth Spurt and Type 2 Diabetes Risk in Southwestern American Indians

Early puberty onset is associated with higher risk of diabetes, but most studies have not accounted for childhood factors that may confound the association. Using data from a study conducted in an Indigenous community in Arizona (1965-2007), we examined associations of timing and velocity of the adolescent growth spurt with type 2 diabetes, and whether these associations are mediated by childhood body mass index and insulinemia. Adolescent growth parameters were derived from the Preece-Baines growth model, a parametric growth curve fitted to longitudinal height data, for 861 participants with height measurements spanning the whole period of growth. In males, older age at take-off, age at peak velocity, and age at maturation were associated with decreased prevalence of diabetes (odds ratio (OR) = 0.43 per year, 95% confidence interval (CI): 0.27, 0.69; OR = 0.50, 95% CI: 0.35, 0.72; OR = 0.58, 95% CI: 0.41, 0.83, respectively), while higher velocity at take-off was associated with increased risk (OR = 3.47 per cm/year, 95% CI: 1.87, 6.42) adjusting for age, birth year, and maternal diabetes. Similar results were observed with incident diabetes. Our findings suggest that an early and accelerated adolescent growth spurt is a risk factor for diabetes, at least in males. These associations are only partially explained by measures of adiposity and insulinemia.

Skeletal maturation in male elite youth athletes from the Middle East

OBJECTIVES

To examine the timing and intensity of skeletal maturation of the radius-ulna-short (RUS) bones in elite youth Arab athletes.

METHODS

We compared SuperImposition by Translation And Rotation (SITAR) models with different spline degrees of freedom and transformation expressions to summarize 492 longitudinal measurements for individual RUS bones scores assessed from 99 male academy student-athletes (chronological age range, 11.4 to 18 years; annual screening range, four to seven visits).

RESULTS

The SITAR model with 5 degrees of freedom and untransformed chronological age was superior to the other models. The mean growth curve increased with age and showed a mid-pubertal double-kink at a RUS score of ~600 bone score units (au). The SITAR model revealed a first peak in the skeletal maturation velocity curve of ~206 au·year-1 occurred at ~13.5 years. The mean age at the second and largest peak occurred at 15.1 years (95% confidence interval [CI], 14.9 to 15.3 years), with the respective estimated peak skeletal ossification rate of 334 au·year-1 (95% CI, 290 to 377 au·year-1 ). The mean age at peak height velocity was 13.5 years (95% CI, 13.3 to 13.7 years), with peak height velocity of 10 cm·year-1 (95% CI, 9.6 to 10.4 cm·year-1 ).

CONCLUSION

Application of the SITAR method confirmed two peaks in the skeletal maturation velocity curve, with the second and largest rate of ossification occurring at a relatively later timing of ~1.5 years than the height growth spurt. Knowledge of the RUS bones timing and intensity can be important to advance strategies for athlete performance development purposes.

The Percentage of Mature Height as a Morphometric Index of Somatic Growth: A Formal Scrutiny of Conventional Simple Ratio Scaling Assumptions

PURPOSE

To assess conventional assumptions that underpin the percentage of mature height index as the simple ratio of screening height (numerator) divided by actual or predicted adult height (denominator).

METHODS

We examined cross-sectional data from 99 academy youth soccer players (chronological age range, 11.5 to 17.7 y) skeletally immature at the screening time and with adult height measurements available at follow-up.

RESULTS

The y-intercept value of -60 cm (95% confidence interval, -115 to -6 cm) from linear regression between screening height and adult height indicated the failure to meet the zero y-intercept assumption. The correlation coefficient between present height and adult height of .64 (95% confidence interval, .50 to .74) was not equal to the ratio of coefficient of variations between these variables (CVx/CVy = 0.46) suggesting Tanner's special circumstance was violated. The non-zero correlation between the ratio and the denominator of .21 (95% confidence interval, .01 to .39) indicated that the percentage of mature height was biased low for players with generally shorter adult height, and vice versa.

CONCLUSION

For the first time, we have demonstrated that the percentage of mature height is an inconsistent statistic for determining the extent of completed growth, leading to potentially biased inferences for research and applied purposes.

Puberty Timing and Sex-Specific Trajectories of Systolic Blood Pressure: a Prospective Cohort Study

BACKGROUND

Sex differences in systolic blood pressure (SBP) emerge during adolescence but the role of puberty is not well understood. We examined sex-specific changes in SBP preceding and following puberty and examined the impact of puberty timing on SBP trajectories in females and males.

METHODS

Trajectories of SBP before and after puberty and by timing of puberty in females and males in a contemporary birth cohort study were analyzed. Repeated measures of height from age 5 to 20 years were used to identify puberty timing (age at peak height velocity). SBP was measured on ten occasions from 3 to 24 years (N participants, 4062; repeated SBP measures, 29 172). Analyses were performed using linear spline multilevel models based on time before and after puberty and were adjusted for parental factors and early childhood factors.

RESULTS

Mean age at peak height velocity was 11.7 years (SD, 0.8) for females and 13.6 years (SD, 0.9) for males. Males had faster rates of increase in SBP before puberty leading to 10.19 mm Hg (95% CI, 6.80-13.57) higher mean SBP at puberty which remained similar at 24 years (mean difference, 11.43 mm Hg [95% CI, 7.22-15.63]). Puberty timing was associated with small transient differences in SBP trajectories postpuberty in both sexes and small differences at 24 years in females only.

CONCLUSIONS

A large proportion of the higher SBP observed in males compared with females in early adulthood is accrued before puberty. Interventions targeting puberty timing are unlikely to influence SBP in early adulthood.

Pubertal growth in osteogenesis imperfecta caused by pathogenic variants in COL1A1/COL1A2

PURPOSE

Short stature is common in osteogenesis imperfecta (OI) and is usually severe in OI types III and IV. The characteristics of pubertal growth in OI have not been studied in detail.

METHODS

We assessed 82 individuals with OI caused by pathogenic variants in COL1A1 or COL1A2 who had annual height data between 6 and 16 years of age at a minimum. Height velocity curves were fitted to each individual's height data to describe the pubertal growth spurt.

RESULTS

Curve fitting was successful in 30 of the 33 individuals with OI type I (91%), in 23 of the 32 individuals with OI type IV (72%), and in 4 of the 17 participants with OI type III (24%). Pubertal growth spurt could be identified in most individuals with OI types I and IV, but rarely in OI type III. The timing of the pubertal growth spurt was similar between OI types I and IV in both sexes. However, height velocity was consistently higher in OI type I, leading to a widening height gap between OI types I and IV.

CONCLUSION

A pubertal growth spurt was present in most individuals with OI types I and IV, but rarely in OI type III.

Using linear and natural cubic splines, SITAR, and latent trajectory models to characterise nonlinear longitudinal growth trajectories in cohort studies

BACKGROUND

Longitudinal data analysis can improve our understanding of the influences on health trajectories across the life-course. There are a variety of statistical models which can be used, and their fitting and interpretation can be complex, particularly where there is a nonlinear trajectory. Our aim was to provide an accessible guide along with applied examples to using four sophisticated modelling procedures for describing nonlinear growth trajectories.

METHODS

This expository paper provides an illustrative guide to summarising nonlinear growth trajectories for repeatedly measured continuous outcomes using (i) linear spline and (ii) natural cubic spline linear mixed-effects (LME) models, (iii) Super Imposition by Translation and Rotation (SITAR) nonlinear mixed effects models, and (iv) latent trajectory models. The underlying model for each approach, their similarities and differences, and their advantages and disadvantages are described. Their application and correct interpretation of their results is illustrated by analysing repeated bone mass measures to characterise bone growth patterns and their sex differences in three cohort studies from the UK, USA, and Canada comprising 8500 individuals and 37,000 measurements from ages 5-40 years. Recommendations for choosing a modelling approach are provided along with a discussion and signposting on further modelling extensions for analysing trajectory exposures and outcomes, and multiple cohorts.

RESULTS

Linear and natural cubic spline LME models and SITAR provided similar summary of the mean bone growth trajectory and growth velocity, and the sex differences in growth patterns. Growth velocity (in grams/year) peaked during adolescence, and peaked earlier in females than males e.g., mean age at peak bone mineral content accrual from multicohort SITAR models was 12.2 years in females and 13.9 years in males. Latent trajectory models (with trajectory shapes estimated using a natural cubic spline) identified up to four subgroups of individuals with distinct trajectories throughout adolescence.

CONCLUSIONS

LME models with linear and natural cubic splines, SITAR, and latent trajectory models are useful for describing nonlinear growth trajectories, and these methods can be adapted for other complex traits. Choice of method depends on the research aims, complexity of the trajectory, and available data. Scripts and synthetic datasets are provided for readers to replicate trajectory modelling and visualisation using the R statistical computing software.

Timing of puberty and school performance: A population-based study

OBJECTIVE

To determine whether the timing of puberty associates with school performance.

METHODS

Growth data on 13,183 children born between 1997 and 2002, were collected from child health clinics and school healthcare and school performance data from school records. Age at peak height velocity (PHV) marked pubertal timing. The relationships between age at PHV and average grades in mathematics, native language, English, and physical education from school years 6 (end of elementary school; age 11-12 years), 7 (start of middle school; 12-13 years), and 9 (end of middle school; 14-15 years) were modeled using generalized estimating equations and linear mixed models, adjusted for the month of birth and annual income and education levels in school catchment areas.

RESULTS

The mean (SD) age at PHV was 13.54 (1.17) years in boys and 11.43 (1.18) years in girls. In girls, age at PHV was associated with grades in mathematics (β=0.041-0.062, p<0.005) and physical education (β=0.077-0.107, p<0.001) across the study years, and in school year 9, also with grades in English (β=-0.047, 95%CI -0.072 to -0.021, p<0.001). Among boys, only the grades in physical education were related to age at PHV across the study years (β=0.026-0.073, p<0.01) and in middle school the grades in mathematics decreased dramatically.

CONCLUSIONS

In both sexes, the timing of puberty was associated with the grades in physical education, and in girls, with academic achievement. The decrease in boys' mathematics grades and sex difference in academic achievement were unexplained by the timing of puberty.

Tanner-Whitehouse and Modified Bayley-Pinneau Adult Height Predictions in Elite Youth Soccer Players from the Middle East

PURPOSE

To provide the first scrutiny of adult height prediction protocols based on automated Greulich-Pyle and Tanner-Whitehouse (TW) skeletal ages applied to elite youth soccer players from the Middle East.

METHODS

We examined the application of modified Bayley-Pinneau (BoneXpert®), TW-II, and TW-III protocols using mixed-longitudinal data available for 103 subjects (chronological age range, 19.4 to 27.9 yr) previously enrolled as academy student-athletes (annual screening range, one to six visits). Random-effects generalized additive models quantified the presence of systematic mean differences between actual versus predicted adult height. Effects were deemed practically equivalent based on the location of the confidence interval (95% CI) against a realistic difference value of Δ = ± 1 cm. Each model pooled residual standard deviation described the actual precision of height predictions and was used to calculate a 95% prediction interval.

RESULTS

The BoneXpert® method overpredicted adult height systematically at chronological ages in the range of approximately 13.5 to 14.5 yr (95% CI range, -1.9 to -1 cm) and Greulich-Pyle skeletal ages between 13.5 and 15 yr (95% CI range, -3.1 to -1 cm). Effects based on TW-II were practically equivalent across the chronological and skeletal age measurement ranges, with this protocol yielding adult height predictions with a precision (standard deviation) of approximately ±2.6 cm. The mean TW-III effects indicated systematic adult height overpredictions until the attainment of 14.5 and 15 yr of chronological age (95% CI range, -3.8 to -1.1 cm) and TW-III skeletal age (95% CI range: -5.2 to -2.3 cm), respectively.

CONCLUSIONS

Tanner-Whitehouse-II adult height prediction method provided more consistent estimates and can be considered the method of choice for talent development purposes in youth soccer players from the Middle East.

Determining the timing of pubertal onset via a multicohort analysis of growth

Objective

Growth-based determination of pubertal onset timing would be cheap and practical. We aimed to determine this timing based on pubertal growth markers. Secondary aims were to estimate the differences in growth between cohorts and identify the role of overweight in onset timing.

Design

This multicohort study includes data from three Finnish cohorts—the Type 1 Diabetes Prediction and Prevention (DIPP, N = 2,825) Study, the Special Turku Coronary Risk Factor Intervention Project (STRIP, N = 711), and the Boy cohort (N = 66). Children were monitored for growth and Tanner staging (except in DIPP).

Methods

The growth data were analyzed using a Super-Imposition by Translation And Rotation growth curve model, and pubertal onset analyses were run using a time-to-pubertal onset model.

Results

The time-to-pubertal onset model used age at peak height velocity (aPHV), peak height velocity (PHV), and overweight status as covariates, with interaction between aPHV and overweight status for girls, and succeeded in determining the onset timing. Cross-validation showed a good agreement (71.0% for girls, 77.0% for boys) between the observed and predicted onset timings. Children in STRIP were taller overall (girls: 1.7 [95% CI: 0.9, 2.5] cm, boys: 1.0 [0.3, 2.2] cm) and had higher PHV values (girls: 0.13 [0.02, 0.25] cm/year, boys: 0.35 [0.21, 0.49] cm/year) than those in DIPP. Boys in the Boy cohort were taller (2.3 [0.3, 4.2] cm) compared with DIPP. Overweight girls showed pubertal onset at 1.0 [0.7, 1.4] year earlier compared with other girls. In boys, there was no such difference.

Conclusions

The novel modeling approach provides an opportunity to evaluate the Tanner breast/genital stage–based pubertal onset timing in cohort studies including longitudinal data on growth but lacking pubertal follow-up.

Prospective associations of mid-childhood plasma per- and polyfluoroalkyl substances and pubertal timing

BACKGROUND

Exposure to per- and polyfluoroalkyl substances (PFAS) may disrupt pubertal timing. Higher PFAS plasma concentrations have been associated with later pubertal timing in girls, but cross-sectional findings may be explained by reverse causation.

OBJECTIVES

To assess prospective associations between PFAS plasma concentrations in mid-childhood and markers of pubertal timing in male and female adolescents.

METHODS

We studied 640 children in Project Viva, a Boston-area prospective cohort. We examined associations of plasma concentrations of 6 PFAS measured at mean 7.9 (SD 0.8) years (2007-2010) with markers of pubertal timing. Parents reported a 5-item pubertal development score at early adolescence (mean 13.1 (SD 0.8) years) and reported age at menarche annually. We calculated age at peak height velocity using research and clinical measures of height. We used sex-specific linear and Cox proportional hazards regression to estimate associations of single PFAS with outcomes, and we used Bayesian Kernel Machine Regression (BKMR) to estimate associations of the PFAS mixture with outcomes.

RESULTS

Plasma concentrations were highest for perfluorooctane sulfonate (PFOS) [median (IQR) 6.4(5.6) ng/mL], followed by perfluorooctanoate (PFOA) [4.4(3.0) ng/mL]. In early adolescence, girls were further along in puberty than boys [pubertal development score mean (SD) 2.9 (0.7) for girls and 2.2(0.7) for boys; age at peak height velocity mean (SD) 11.2y (1.0) for girls and 13.1y (1.0) for boys]. PFAS was associated with later markers of pubertal timing in girls only. For example, each doubling of PFOA was associated with lower pubertal development score (-0.18 units; 95% CI: -0.30, -0.06) and older age at peak height velocity (0.23 years; 95% CI: 0.06, 0.40)]. We observed similar associations for PFOS, perfluorodecanoate (PFDA), and the PFAS mixture. PFAS plasma concentrations were not associated with age at menarche or markers of pubertal timing in boys.

DISCUSSION

Higher PFAS plasma concentrations in mid-childhood were associated with later onset of puberty in girls.

Craniofacial growth and SITAR growth curve analysis

BACKGROUND

SITAR (SuperImposition by Translation And Rotation) is a shape invariant growth curve model that effectively summarizes somatic growth in puberty.

AIM

To apply the SITAR model to longitudinal mandibular growth data to clarify its suitability to facial growth analysis.

SUBJECTS AND METHODS

2D-cephalometric data on two mandibular measurements (AP: articulare-pogonion; CP: condylion-pogonion) were selected from the Denver Growth Study, consisting of longitudinal records (age range: 7.9-19.0 years) of females (sample size N: 21; number of radiographs n: 154) and males (N: 18; n: 137). The SITAR mixed effects model estimated, for each measurement and gender separately, a mean growth curve versus chronological age, along with mean age at peak velocity (APV) and peak velocity (PV), plus subject-specific random effects for PV and mean size. The models were also fitted versus Greulich-Pyle bone age.

RESULTS

In males, mean APV occurred at 14.6 years (AP) and 14.4 years (CP), with mean PV 3.1 mm/year (AP) and 3.3 mm/year (CP). In females, APV occurred at 11.6 years (AP and CP), with mean PV 2.3 mm/year (AP) and 2.4 mm/year (CP). The models explained 95-96 per cent of the cross-sectional variance for males and 92-93 per cent for females. The random effects demonstrated standard deviations (SDs) in size of 5.6 mm for males and 3.9 mm for females, and SDs for PV between 0.3 and 0.5 mm/year. The bone age results were similar.

CONCLUSION

The SITAR model is a useful tool to analyse epidemiological craniofacial growth based on cephalometric data and provides an array of information on pubertal mandibular growth and its variance in a concise manner.

Puberty timing and markers of cardiovascular structure and function at 25 years: a prospective cohort study

BACKGROUND

Whether earlier onset of puberty is associated with higher cardiovascular risk in early adulthood is not well understood. Our objective was to examine the association between puberty timing and markers of cardiovascular structure and function at age 25 years.

METHODS

We conducted a prospective birth cohort study using data from the Avon Longitudinal Study of Parents and Children (ALSPAC). Participants were born between April 1, 1991, and December 31, 1992. Exposure of interest was age at peak height velocity (aPHV), an objective and validated growth-based measure of puberty onset. Outcome measures included cardiovascular structure and function at age 25 years: carotid intima-media thickness (CIMT), left ventricular mass index (LVMI) and relative wall thickness (RWT), pulse wave velocity (PWV) and systolic blood pressure (SBP). Multiple imputation was used to impute missing data on covariates and outcomes. Linear regression was used to examine the association between aPHV and each measure of cardiac structure and function, adjusting for maternal age, gestational age, household social class, maternal education, mother's partner's education, breastfeeding, parity, birthweight, maternal body mass index, maternal marital status, maternal prenatal smoking status and height and fat mass at age 9. All analyses were stratified by sex.

RESULTS

A total of 2752-4571 participants were included in the imputed analyses. A 1-year older aPHV was not strongly associated with markers of cardiac structure and function in males and females at 25 years and most results spanned the null value. In adjusted analyses, a 1-year older aPHV was associated with 0.003 mm (95% confidence interval (CI) 0.00001, 0.006) and 0.0008 mm (95% CI - 0.002, 0.003) higher CIMT; 0.02 m/s (95% CI - 0.05, 0.09) and 0.02 m/s (95% CI - 0.04, 0.09) higher PWV; and 0.003 mmHg (95% CI - 0.60, 0.60) and 0.13 mmHg (95% CI - 0.44, 0.70) higher SBP, among males and females, respectively. A 1-year older aPHV was associated with - 0.55 g/m2.7 (95% CI - 0.03, - 1.08) and - 0.89 g/m2.7 (95% CI - 0.45, - 1.34) lower LVMI and - 0.001 (95% CI - 0.006, 0.002) and - 0.002 (95% CI - 0.006, 0.002) lower RWT among males and females.

CONCLUSIONS

Earlier puberty is unlikely to have a major impact on pre-clinical cardiovascular risk in early adulthood.

Prediction of maturity offset and age at peak height velocity in a longitudinal series of boys and girls

BACKGROUND

Predicted maturity offset, defined as time before peak height velocity (PHV) is increasingly used as an indicator of maturity status in studies of physical activity, fitness, and sport.

OBJECTIVE

To validate maturity offset prediction equations in longitudinal samples of boys and girls.

METHODS

The original and modified maturity offset prediction equations were applied to serial data for 266 boys (8-17 years) and 147 girls (8-16 years) from the Cracow Growth Study. Actual age at PHV for each youngster was estimated with the SITAR protocol. In addition to maturity offset, the difference between CA at prediction and maturity offset provided an estimate of predicted age at PHV.

RESULTS

Predicted maturity offset and age at PHV increased, on average, with CA at prediction. Variation in predictions was reduced compared to that in observed ages at offset and at PHV, and was more apparent with the modified equations. Relatively few predicted ages at PHV approximated observed age at PHV in early and late maturing youth of both sexes; predictions were later than observed among the former, and earlier than observed among the latter.

CONCLUSION

Predicted maturity offset and ages at PHV with the original and modified equations increase with CA at prediction, have reduced variation, and have major limitations with early and late maturing boys and girls.

Puberty timing and adiposity change across childhood and adolescence: disentangling cause and consequence

STUDY QUESTION

Is earlier puberty more likely a result of adiposity gain in childhood than a cause of adiposity gain in adulthood?

SUMMARY ANSWER

Pre-pubertal fat mass is associated with earlier puberty timing but puberty timing is not associated with post-pubertal fat mass change.

WHAT IS KNOWN ALREADY

Age at puberty onset has decreased substantially in the last several decades. Whether reducing childhood adiposity prevents earlier puberty and if early puberty prevention itself also has additional independent benefits for prevention of adult adiposity is not well understood.

STUDY DESIGN, SIZE, DURATION

Prospective birth cohort study of 4176 participants born in 1991/1992 with 18 232 repeated measures of fat mass from age 9 to 18 years.

PARTICIPANTS/MATERIALS, SETTING, METHODS

We used repeated measures of height from 5 to 20 years to identify puberty timing (age at peak height velocity, aPHV) and repeated measures of directly measured fat mass from age 9 to 18 years, from a contemporary UK birth cohort study to model fat mass trajectories by chronological age and by time before and after puberty onset. We then examined associations of these trajectories with puberty timing separately in females and males.

MAIN RESULTS AND THE ROLE OF CHANCE

In models by chronological age, a 1-year later aPHV was associated with 20.5% (95% confidence interval (CI): 18.6-22.4%) and 23.4% (95% (CI): 21.3-25.5%) lower fat mass in females and males, respectively, at 9 years. These differences were smaller at age 18 years: 7.8% (95% (CI): 5.9-9.6%) and 12.4% (95% (CI): 9.6-15.2%) lower fat mass in females and males per year later aPHV. Trajectories of fat mass by time before and after puberty provided strong evidence for an association of pre-pubertal fat mass with puberty timing, and little evidence of an association of puberty timing with post-pubertal fat mass change. The role of chance is likely to be small in this study given the large sample sizes available.

LIMITATIONS, REASONS FOR CAUTION

Participants included in our analyses were more socially advantaged than those excluded. The findings of this work may not apply to non-White populations and further work examining associations of puberty timing and fat mass in other ethnicities is required.

WIDER IMPLICATIONS OF THE FINDINGS

Previous research has relied on self-reported measures of puberty timing such as age of voice breaking in males, has lacked data on pre-and post-pubertal adiposity together and relied predominantly on indirect measures of adiposity such as BMI. This has led to conflicting results on the nature and direction of the association between puberty timing and adiposity in females and males. Our work provides important clarity on this, suggesting that prevention of adiposity in childhood is key for prevention of early puberty, adult adiposity and associated cardiovascular risk. In contrast, our findings suggest that prevention of early puberty without prevention of childhood adiposity would have little impact on prevention of adult adiposity.

STUDY FUNDING/COMPETING INTEREST(S)

The UK Medical Research Council and Wellcome (Grant ref: 102215/2/13/2) and the University of Bristol provide core support for Avon Longitudinal Study of Parents and Children (ALSPAC). L.M.O.K. is supported by a UK Medical Research Council Population Health Scientist fellowship (MR/M014509/1) and a Health Research Board (HRB) of Ireland Emerging Investigator Award (EIA-FA-2019-007 SCaRLeT). J.A.B. is supported by the Elizabeth Blackwell Institute for Health Research, University of Bristol and the Wellcome Trust Institutional Strategic Support Fund (204813/Z/16/Z). L.D.H. and A.F. are supported by Career Development Awards from the UK Medical Research Council (grants MR/M020894/1 and MR/M009351/1, respectively). All authors work in a unit that receives funds from the UK Medical Research Council (grant MC_UU_00011/3, MC_UU_00011/6). No competing interests to declare.

TRIAL REGISTRATION NUMBER

N/A.

Tanner's tempo of growth in adolescence: recent SITAR insights with the Harpenden Growth Study and ALSPAC

Background: James Tanner emphasised the “tempo” of growth, i.e. the adolescent spurt as summarised by its timing (age at peak velocity or APV) and intensity (peak velocity, PV).

Aim: The paper applies the SITAR growth curve model to pubertal growth data with the aim of clarifying the growth pattern across multiple measurements and the spectrum of APV and PV.

Subjects and methods: Data for 7–20 years on ten anthropometric measurements in 619 children from the Harpenden Growth Study, and on height in 10410 children from the ALSPAC study, were analysed using SITAR (SuperImposition by Translation And Rotation). SITAR models pubertal growth as a mean curve with APV and PV fitted as subject-specific random effects, and a random measurement intercept.

Results: Mean APV for Harpenden girls and boys averaged 12.0 and 13.9 years across the ten measurements. PV expressed as percent per year lay in the narrow range 4–8%. Splitting the ALSPAC subjects into 9 by 5 APV and PV groups and fitting separate SITAR models to each group confirmed SITAR’s good fit while highlighting the spectrum of growth patterns.

Conclusion: SITAR works well to summarise pubertal growth. The disappointment is that Tanner did not live to see it in action.

Adolescent growth and BMI and their associations with early childhood growth in an urban South African cohort

OBJECTIVES

The timing and magnitude of adolescent growth may be influenced by ethnicity and early life factors. We aimed to (a) characterize ethnic differences in the magnitude, timing, and intensity of adolescent growth in height, weight, and BMI; (b) assess the effect of early childhood growth on adolescent growth in black children.

METHODS

Data were from the Birth to Twenty Plus cohort (Bt20+) in Johannesburg, South Africa (n = 3273). Height, weight, and BMI were modeled with ethnic comparisons using the SuperImposition by Translation and Rotation for 2089 participants who had data from 7 to 23 years. Relative weight gain and relative linear growth between 0 and 24 months and 24 and 60 months were generated. Multiple regression analyses were used to assess associations between childhood and adolescent growth.

RESULTS

White children were 5 cm (SE: 0.7) taller than black children through adolescence. Black boys had a later timing of adolescent height (0.65 years ±0.12) than white boys, which in black girls was 0.24 years (0.11) earlier than in white girls. Black girls had faster BMI velocity than white girls. Among black children, birth weight and both relative weight gain 0 to 24 and relative linear growth between 3 and 24 months and 24 and 60 months were positively associated with the magnitude of adolescent growth and negatively associated with timing.

CONCLUSION

Sex dimorphism in ethnic differences in timing of adolescent height growth may reflect some yet unexplained drivers for rapid weight gain and obesity in black females but not black males. Rapid weight gain in early life may contribute to faster adiposity accrual in adolescence.

How can two biological variables have opposing secular trends, yet be positively related? A demonstration using timing of puberty and adult height

Timing of puberty and adult height have opposing secular trends yet are positively associated in individuals. We demonstrate this using data from a single sample and discuss possible statistical and epidemiological reasons behind it. The sample comprised 365 females from Fels Longitudinal Study born 1929-1992. We used Super-Imposition by Translation and Rotation (SITAR) to estimate individual age at peak height velocity (PHV) and PHV from serial height data (8149 observations between 5 and 24 years). General linear regression was used to investigate the association between height and age at PHV, and secular trends in height, age at PHV and PHV. Although adult height increased 0.42 (95% CI: 0.08, 0.77) cm per decade, and age at PHV decreased 1.14 (-3.74, 1.45) weeks per decade, adult height increased by 2.44 (1.78, 3.10) cm per year higher age at PHV. We found tentative evidence of the positive association between age at PHV and adult height strengthened 0.25 (-0.09, 0.59) cm each decade. Secular trends in related variables may differ if the between-individual and between-cohort associations are different. To understand if a secular trend in one variable has contributed to a trend in another, each needs to be modelled over time, together with the changing association between them.

Estimating peak height velocity in individuals: a comparison of statistical methods

BACKGROUND

Estimates pertaining to the timing of the adolescent growth spurt (e.g. peak height velocity; PHV), including age at peak height velocity (aPHV), play a critical role in the diagnosis, treatment, and management of skeletal growth and/or developmental disorders. Yet, distinct statistical methodologies often result in large estimate discrepancies.

AIM

The aim of the present study was to assess the advantages and disadvantages of three modelling methodologies for height as well as to determine how estimates derived from these methodologies may differ, particularly those that may be useful in paediatric clinical practice.

SUBJECTS AND METHODS

Height data from 686 individuals of the Fels Longitudinal Study were modelled using 5th order polynomials, natural cubic splines, and SuperImposition by Translation and Rotation (SITAR) to determine aPHV and PHV for all individuals together (i.e. population average) by sex and separately for each individual. Estimates within and between methodologies were calculated and compared.

RESULTS

In general, mean aPHV was earlier, and PHV was greater for individuals when compared to estimates from population average models. Significant differences between mean aPHV and PHV for individuals were observed in all three methodologies, with SITAR exhibiting the latest aPHV and largest PHV estimates.

CONCLUSION

Each statistical methodology has a number of advantages when used for specific purposes. For modelling growth in individuals, as one would in paediatric clinical practice, we recommend the use of the 5th order polynomial methodology due to its parameter flexibility.

Four decades of socio-economic inequality and secular change in the physical growth of Guatemalans

Objective:

To investigate changes in socio-economic inequalities in growth in height, weight, BMI and grip strength in children born during 1955–1993 in Guatemala, a period of marked socio-economic-political change.

Design:

We modelled longitudinal data on height, weight, BMI and hand grip strength using Super-Imposition by Translation and Rotation (SITAR). Internal Z-scores summarising growth size, timing and intensity (peak growth velocity, e.g. cm/year) were created to investigate inequalities by socio-economic position (SEP; measured by school attended). Interactions of SEP with date of birth were investigated to capture secular changes in inequalities.

Setting:

Urban and peri-urban schools in the region of Guatemala City, Guatemala.

Participants:

Participants were 40 484 children and adolescents aged 3–19 years of Ladino and Maya ancestry (n_observations 157 067).

Results:

The difference in height (SITAR size) between lowest and highest SEP decreased from −2·0 (95 % CI −2·2, −1·9) sd to −1·4 (95 % CI −1·5, −1·3) sd in males, and from −2·0 (95 % CI −2·1, −1·9) sd to −1·2 (95 % CI −1·3, −1·2) sd in females over the study period. Inequalities also reduced for weight, BMI and grip strength, due to greater secular increases in lowest-SEP groups. The puberty period was earlier and shorter in higher-SEP individuals (earlier SITAR timing and higher SITAR intensity). All SEP groups showed increases in BMI intensity over time.

Conclusions:

Inequality narrowed between the 1960s and 1990s. The lowest-SEP groups were still >1 sd shorter than the highest. Risks remain for reduced human capital and poorer population health for urban Guatemalans.

Parental Obesity and Offspring Pubertal Development: Project Viva

OBJECTIVE

To investigate the association of preconception parental obesity (body mass index [BMI] ≥30 kg/m²) with offspring pubertal development.

STUDY DESIGN

Among 1377 children from a prospective prebirth cohort in Boston, we examined markers of puberty (age at peak height velocity [PHV], age at menarche, self-reported pubertal development score), and adrenarche (pictograph Tanner pubic hair staging). We used multivariable regression models to examine associations of maternal and paternal obesity with offspring pubertal indices, and applied marginal structural models to estimate the controlled direct effect not mediated by offspring prepubertal BMI.

RESULTS

The prevalence of paternal obesity alone, maternal obesity alone, and biparental obesity were 10.5%, 10.1%, and 5%, respectively. After adjusting for demographic and socioeconomic factors, parental heights and maternal age at menarche, maternal obesity alone (vs neither parent with obesity) was associated with earlier age at PHV (β -0.30 years; 95% CI -0.57, -0.03) and higher early adolescent pubertal score (0.29 units; 0.10, 0.48) in boys, but not with pubertal or adrenarchal outcomes in girls. Paternal obesity alone was not associated with any outcomes in either boys or girls. Biparental obesity was associated with earlier age at PHV in boys and earlier menarche in girls. Using marginal structural models with stabilized inverse probability weighting, maternal obesity alone had significant controlled direct effects on age at PHV (-0.31 years; -0.62, 0.00) and on pubertal score (0.22 units; 0.00, 0.44) in boys, independent of prepubertal BMI.

CONCLUSION

Maternal, but not paternal, obesity is associated with earlier pubertal development in boys, and such association is independent of prepubertal BMI.

Life course associations of height, weight, fatness, grip strength, and all-cause mortality for high socioeconomic status Guatemalans

Objectives

The objective of this study was to investigate the association between physical growth in preadult life with five outcomes at ages 64 to 76: weight, body mass index (BMI), estimated body fat percentage, hand grip strength, and mortality.

Methods

Super‐imposition by translation and rotation (SITAR) growth curves of 40 484 Guatemalan individuals aged 3 to 19 years were modeled for the parameters of size, timing and intensity (peak growth velocity, eg, cm/year) of height, weight, BMI, and grip strength. Associations between the SITAR parameters and old age outcomes were tested using linear and binary logistic regression for a follow‐up sample of high socioeconomic status (SES) Guatemalans, of whom 50 were aged 64 to 76 years at re‐measurement and 45 died prior to the year 2017.

Results

SITAR models explained 69% to 98% of the variance in each outcome, with height the most precise. Individuals in the follow‐up sample who had a higher BMI before the age of 20 years had higher estimated body fat (B = 1.4 CI −0.02‐2.8) and BMI (B = 1.2, CI 0.2‐2.2) at the ages of 64 to 76 years. Those who grew slower in height but faster in weight and BMI before the age of 20 years had higher BMI and body fat later in life.

Conclusions

These findings highlight the importance of a life course perspective on health and mortality risk. Childhood exposures leading to variation in preadult growth may be key to better understanding health and mortality risks in old age.

Using SITAR (SuperImposition by Translation and Rotation) to estimate age at peak height velocity in Avon Longitudinal Study of Parents and Children

Puberty is a time of substantial biological and psychological changes. One of the hallmarks of puberty is a rapid growth spurt, however its timing varies between individuals. The impact of pubertal timing on later health outcomes has been of interest in life course epidemiology, however its measurement can be challenging. Age at peak height velocity (aPHV) offers an objective measure of pubertal timing without having to rely on physical examination or self-report. We describe the derivation of aPHV estimates in Avon Longitudinal Study of Parents and Children (ALSPAC) offspring, using Superimposition by Translation And Rotation (SITAR) mixed effects growth curve analysis. ALSPAC is a rich source of phenotypic and genotypic data and given the importance of pubertal timing for later health outcomes, these data offer an opportunity to explore the determinants and consequences of aPHV.

Using SITAR (SuperImposition by Translation and Rotation) to estimate age at peak height velocity in Avon Longitudinal Study of Parents and Children

Puberty is a time of substantial biological and psychological changes. One of the hallmarks of puberty is a rapid growth spurt, however its timing varies between individuals. The impact of pubertal timing on later health outcomes has been of interest in life course epidemiology, however its measurement can be challenging. Age at peak height velocity (aPHV) offers an objective measure of pubertal timing without having to rely on physical examination or self-report. We describe the derivation of aPHV estimates in Avon Longitudinal Study of Parents and Children (ALSPAC) offspring, using Superimposition by Translation And Rotation (SITAR) mixed effects growth curve analysis. ALSPAC is a rich source of phenotypic and genotypic data and given the importance of pubertal timing for later health outcomes, these data offer an opportunity to explore the determinants and consequences of aPHV.

New approaches to obtaining individual peak height velocity and age at peak height velocity from the SITAR model

OBJECTIVE

We compared three methods for estimating the individual peak height velocity (PHV) and age at peak height velocity (APHV) from the SuperImposition by Translation and Rotation (SITAR) model.

METHODS

We fitted the SITAR model using simulated data and heights of 12 girls from the Chard Growth Study and obtained individual PHVs and APHVs from three methods: the model method, the quadratic function method and the numerical method, which are available in our newly developed R package"iapvbs". The mean, interquartile range, range of biases in estimated APHV and PHV as well as the rates of warning and unreasonable cases, i.e. estimated APHVs being outside the range of age measurements, from the three methods were presented and compared.

RESULTS

When the growth curves of all individuals were well fitted by the SITAR model, all three methods estimated individual APHVs with similarly small biases, with a few unreasonable cases (0.16%) observed when the model method was used while more computation time required for the numerical method. When the growth curves of some individuals were not very well fitted, the model method generated more unreasonable individual APHV (8.15%) and more bias in PHV and APHV, compared to those estimated by the numerical method and quadratic function method. In line with the observations from the simulated data, the real data analysis demonstrated that the numerical method generated more reliable PHV and APHV for individuals with growth curve not well fitted by the SITAR model.

CONCLUSION

The performance of different methods estimating individual APHV depends largely on how well the growth curves are fitted by the SITAR model. The quadratic function method is more superior when growth curves of all individuals are well fitted by the SITAR model; otherwise, the numerical method should be adopted for getting most robust estimates of PHV and APHV. The model method generates unreasonable APHV estimates, particularly when the growth curves are not well fitted.

Optimal design for longitudinal studies to estimate pubertal height growth in individuals

BACKGROUND

The SITAR model expresses individual pubertal height growth in terms of mean size, peak height velocity (PHV) and age at PHV.

AIM

To use SITAR to identify the optimal time interval between measurements to summarise individual pubertal height growth.

SUBJECTS AND METHODS

Heights in 3172 boys aged 9-19 years from Christ's Hospital School measured on 128 679 occasions (a median of 42 heights per boy) were analysed using the SITAR (SuperImposition by Translation And Rotation) mixed effects growth curve model, which estimates a mean curve and three subject-specific random effects. Separate models were fitted to sub-sets of the data with measurement intervals of 2, 3, 4, 6, 12 and 24 months, and the different models were compared.

RESULTS

The models for intervals 2-12 months gave effectively identical results for the residual standard deviation (0.8 cm), mean spline curve (6 degrees of freedom) and random effects (correlations >0.9), showing there is no benefit in measuring height more often than annually. The model for 2-year intervals fitted slightly less well, but needed just four-to-five measurements per individual.

CONCLUSIONS

Height during puberty needs to be measured only annually and, with slightly lower precision, just four biennial measurements can be sufficient.