Modelling Height in Adolescence: A Comparison of Methods for Estimating the Age at Peak Height Velocity.

Simpkin, Andrew; Sayers, Adrian; Goldstein, Hyman; Gilthorpe, Mark S.; Heron, Jon; Tilling, Kate

doi:10.1093/ije/dyv096.163

Cited by 12 publications

(15 citation statements)

References 30 publications

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“…The results show that the SITAR growth curve model works well with growth in puberty, because it explicitly estimates these two parameters in individuals, along with a third parameter representing their mean size. Simpkin et al compared several alternative growth curve models for height in puberty, and they also concluded that SITAR was useful in providing unbiased estimates of age at peak height velocity (Simpkin et al 2017). But that said, the more detailed ALSPAC analysis has brought to light the existence of a midgrowth spurt at around 9 years in the later-maturing boys.…”

Section: Study Findingsmentioning

confidence: 99%

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

Cole

2020

Annals of Human Biology

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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.

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Section: Study Findingsmentioning

confidence: 99%

“…A strength of SITAR is its ability to sort individuals by APV (Simpkin et al 2017). Thus it is easy to use the global model to split the ten thousand ALSPAC children into nine groups by sex, based on their timing random effects, and then analyse these local groups separately.…”

Section: Alspacmentioning

confidence: 99%

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

Cole

2020

Annals of Human Biology

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“…In the second stage of analysis, the individual random effects derived from the SITAR models were transformed to internal Z-scores, by sex, to allow for easier comparisons between outcomes with different units of measurement. Linear regression models were used to investigate variation in size, timing and intensity according to SEP group and date of birth in the R programming language and software environment for statistical computing (21) . Models were outcome (size, timing, intensity of each measure) and sex specific.…”

Section: Discussionmentioning

confidence: 99%

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

Mansukoski

Johnson

Brooke‐Wavell

et al. 2019

Public Health Nutr.

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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 (nobservations 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.

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“…Size, timing, and intensity are also estimated as fixed effects, so the random effects have mean zero (Cole et al, ). SITAR has been shown to provide an unbiased estimate of APV (Simpkin, Sayers, Gilthorpe, Heron, & Tilling, ). The SITAR formula is:

y_{it} = α_{i} + h ((), \frac{t - β_{i}}{\exp (- {normalγ}_{i})})

Where y it is height for subject i at age t , h ( t ) is a natural cubic spline curve of height vs age, and α i , β i , and γ i are subject‐specific random effects Cole et al ().…”

Section: Methodsmentioning

confidence: 99%

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

Mansukoski

Johnson

Brooke‐Wavell

et al. 2019

American J Hum Biol

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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.

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Modelling Height in Adolescence: A Comparison of Methods for Estimating the Age at Peak Height Velocity.

Cited by 12 publications

References 30 publications

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

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

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

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

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