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BACKGROUND The QEPS-growth-model, developed and validated in GrowUp-Gothenburg cohorts, used for developing growth references and investigating healthy/pathological growth, lacks external validation from other longitudinal cohorts of healthy individuals. AIM To investigate if the QEPS-model can fit the longitudinal Edinburgh growth study of another design than GrowUp-Gothenburg cohorts, and to compare growth patterns in the individuals born in mid-1970s in North-Western Europe. METHODS Longitudinal growth data were obtained from the Edinburgh and the GrowUp1974Gothenburg cohorts. The QEPS-model was used to describe length/height from birth to adult height with confidence interval, and the multivariable regression model for estimating the contribution of the different QEPS-functions to adult height. RESULTS The QEPS-model fitted the Edinburgh cohort well, with high accuracy, and low confidence intervals indicating high precision. Despite 3 cm shorter stature (less QE-function growth) in Scottish children, the growth patterns of the cohorts were similar, especially for specific pubertal growth. The contribution to adult height from different QEPS functions was similar. CONCLUSION The QEPS-model is validated for the first time in a longitudinal study of healthy individuals of another design and found to fit with high accuracy and precision. The Scottish and Western-Swedish cohorts born in mid-1970s showed similar growth patterns for both sexes, especially pubertal growth. IMPACT For the first time, the QEPS height model was used and found to fit another longitudinal cohort of healthy individuals other than the Swedish longitudinal cohorts. With large numbers of individual measurements in each growth phase, the QEPS model calculates growth estimates with narrow confidence intervals (high precision) and high accuracy. The two different cohorts born in the mid-1970s from Scotland and Western Sweden have similar growth patterns, despite a 3 cm difference in adult height.

AIM To update the Swedish references for weight, weight-for-height and body mass index (BMI) considering the secular trend for height but not including that for weight. METHODS Longitudinal measures of height and weight were obtained (0-18 years) from 1418 (698 girls) healthy children from the GrowUp 1990 Gothenburg cohort born at term to non-smoking mothers and Nordic parents. A total of 145 individuals with extreme BMI value vs GrowUp 1974 BMI SDS reference were excluded (0-2 years: ±4SDS, 2

Objectives Despite inter-individual variations in pubertal timing, growth references are conventionally constructed relative to chronological age (C-age). Thus, they are based on reference populations containing a mix of prepubertal and pubertal individuals, making them of limited use for detecting abnormal growth during adolescence. Recently we developed new types of height and weight references, with growth aligned to age at onset of the pubertal growth spurt (P-age). Here, we aim to develop a corresponding reference for pubertal BMI. Methods The QEPS-height and weight models were used to define a corresponding QEPS-BMI model. QEPS-BMI was modified by the same individual, constitutional weight–height-factor (WHF) as computed for QEPS-weight. QEPS-BMI functions were computed with QEPS weight and height functions fitted on longitudinal measurements from 1418 individuals (698 girls) from GrowUp1990Gothenburg cohort. These individual BMI functions were used to develop BMI references aligned for height at AgeP5; when 5% of specific puberty-related (P-function) height had been attained. Pubertal timing, stature at pubertal onset, and childhood BMI, were investigated in subgroups of children from the cohort GrowUp1974Gothenburg using the new references. Results References (median, standard deviation score (SDS)) were generated for total BMI (QEPS-functions), for ongoing prepubertal growth (QE-function) vs C-age, and for total BMI and separated into BMI specific to puberty (P-function) and BMI gain from ongoing basic growth (QES-functions), allowing individual growth to be aligned based on P-age. Growth in basic BMI was greater than average for children categorized as tall and/or with high-BMI at puberty-start. In children categorized as short at puberty-start, P-function-related-BMI was greater than average. Conclusions Use of these new pubertal BMI references will make it possible for the first time to consider individual variations owing to pubertal timing when evaluating BMI. This will improve the detection of abnormal changes in body composition when used in combination with pubertal height and weight references also abnormal growth. Other benefits in the clinic will include improved growth monitoring during treatment for children who are overweight/obese or underweight. Furthermore, in research settings these new references represent a novel tool for exploring human growth.

Aim We aimed to develop up‐to‐date references with standard deviation scores (SDS) for prepubertal and total height. Methods Longitudinal length/height measures from 1572 healthy children (51.5% boys) born at term in 1989‐1991 to non‐smoking mothers and Nordic parents were obtained from the GrowUp 1990 Gothenburg cohort. A total height SDS reference from birth to adult height was constructed from Quadratic‐Exponential‐Pubertal‐Stop (QEPS) function estimated heights based on individual growth curves. A prepubertal height SDS reference, showing growth trajectory in the absence of puberty, was constructed using the QE functions. Results The total height reference showed taller prepubertal mean heights (for boys 1‐2 cm; for girls 0.5‐1.0 cm) with a narrower normal within ± 2SDS range vs the GrowUp 1974 Gothenburg reference. Adult height was increased by + 0.9 cm for women (168.6 cm) and by + 1.6 cm for men (182.0 cm). Height in children growing at −2SDS (the cut‐off used for referrals) differed up to 2 cm vs the GrowUp 1974 Gothenburg reference, 3 cm vs Swedish 1981 references and World Health Organisation (WHO) 0‐5 years standard, and 6‐8 cm vs the WHO 5‐19 years reference. Conclusion Up‐to‐date total and prepubertal height references offer promise of improved growth monitoring compared with the references used in Sweden today.

Background Growth references are traditionally constructed relative to chronological age, despite inter-individual variations in pubertal timing. A new type of height reference was recently developed allowing growth to be aligned based on onset of pubertal height growth. We here aim to develop a corresponding reference for pubertal weight. Methods To model QEPS-weight, 3595 subjects (1779 girls) from GrowUp1974Gothenburg and GrowUp1990Gothenburg were used. The QEPS-height-model was transformed to a corresponding QEPS-weight-model; thereafter, QEPS-weight was modified by an individual, constitutional weight-height-factor. Longitudinal weight and length/height measurements from 1418 individuals (698 girls) from GrowUp1990Gothenburg were then used to create weight references aligned for height at pubertal onset (the age at 5% of P-function growth, AgeP5). GrowUp1974Gothenburg subgroups based on pubertal timing, stature at pubertal onset, and childhood body composition were assessed using the references. Results References (median, SDS) for total weight (QEPS-functions), weight specific to puberty (P-function), and weight gain in the absence of specific pubertal growth (basic weight, QES-functions), allowing alignment of individual growth based on age at pubertal onset. For both sexes, basic weight was greater than average for late maturing, tall and high-BMI subgroups. The P-function-related weight was greater than average in short and lower than average in tall children, in those with high BMI, and in girls but not boys with low BMI. Conclusions New pubertal weight references allow individual variations in pubertal timing to be taken into consideration when evaluating growth. When used together with the comparable pubertal height reference, this will improve growth monitoring in clinical practice for identifying abnormal growth and serve as a valuable research tool providing insight into human growth.

Over the past 150 years, humans have become taller, and puberty has begun earlier. It is unclear if these changes are continuing in Sweden, and how longitudinal growth patterns are involved. We aimed to evaluate the underlying changes in growth patterns from birth to adulthood by QEPS estimates in two Swedish cohorts born in 1974 and 1990. Growth characteristics of the longitudinal 1974 and 1990-birth cohorts (n = 4181) were compared using the QEPS model together with adult heights. There was more rapid fetal/infancy growth in girls/boys born in 1990 compared to 1974, as shown by a faster Etimescale and they were heavier at birth. The laterborn were taller also in childhood as shown by a higher Q-function. Girls born in 1990 had earlier and more pronounced growth during puberty than girls born in 1974. Individuals in the 1990 cohort attained greater adult heights than those in the 1974 cohort; 6 mm taller for females and 10 mm for males. A positive change in adult height was attributed to more growth during childhood in both sexes and during puberty for girls. The QEPS model proved to be effective detecting small changes of growth patterns, between two longitudinal growth cohorts born only 16 years apart.

Computerized mathematical models describing absolute and relative individual growth during puberty in both cm and standard deviation (SD)-scores are lacking. The present study aimed to fill this gap, by applying the QEPS-model that delineates mathematically the specific pubertal functions of the total growth curve. Study population used was the individual growth curves of the longitudinally followed cohort GrowUp1974 Gothenburg (n = 2280). The QEPS-model describes total height as (T)otal-function: a combination of four shape-invariant growth functions, modified by time-scale and height-scale parameters: a (Q)uadratic-function for the continuous growth from fetal life to adulthood; a negative (E)xponential-function adds the rapid, declining fetal/infancy growth; a (P)ubertal-function the specific pubertal growth spurt; a (S)top-function the declining growth until adult height. A constructed variable, MathSelect, was developed for assessing data-quality. CIs and SD-scores for growth estimates were calculated for each individual. QEPS-model estimates used for pubertal growth; from the T-function: onset of puberty as minimal height velocity (AgeT ONSET ); mid-puberty as peak height velocity (AgeT PHV ); end of puberty as height velocity decreased to 1 cm/year (AgeT END ); duration of different intervals and gain (AgeT ONSET–END and Tpubgain); from the P-function: onset of puberty, estimated as growth at 1% or 5% (AgeP1 , AgeP5); mid-puberty as 50% (AgeP50) and PHV (AgeP PHV ); end of pubertal growth at 95 or 99% (AgeP95, AgeP99); duration of different intervals and pubertal gain (Ppubgain; P max ); from the QES-function: gain (QESpubgain) . Application of these mathematical estimates for onset, middle and end of puberty of P-function, QES-function, and T-function during puberty showed: the later the onset of puberty, the greater the adult height; pubertal gain due to the P-function growth was independent of age at onset of puberty; boys had higher total gain during puberty due to P-function growth than to QES-function growth; for girls it was reversed. QEPS is the first growth model to provide individualized estimates of both the specific pubertal growth function and the total growth during puberty, with accompanying SD-scores and Cis for each individual. These QEPS-derived estimates enable more in-depth analysis of different aspects of pubertal growth than previously possible.

Childhood BMI may influence subsequent growth in height as well as the timing of puberty. The aim of the present study was to investigate associations between BMI in childhood and subsequent height gain/pubertal growth. Longitudinal growth data were used (GrowUp1990Gothenburg cohort, n = 1,901). The QEPS growth-model was used to characterize height gain in relation to the highest BMISDS value between 3.5 and 8 y of age. Children were defined as overweight/obese (OwOb) or normal weight/underweight (NwUw), using the 2012 International Obesity Task Force criteria. A negative association between childhood BMISDS and pubertal height gain was observed. Already at birth, OwOb children were heavier than NwUw children, and had a greater height velocity during childhood. Onset of puberty was 3.5/3.0 mo earlier in OwOb girls/boys, and they had 2.3/3.1 cm less pubertal height gain from the QEPS-models specific P-function than NwUw children. Adult height was not related to childhood BMI. We found that pubertal height gain was inversely related to peak BMI in childhood. Higher childhood BMISDS was associated with more growth before onset of puberty, earlier puberty, and less pubertal height gain, resulting in similar adult heights for OwOb and NwUw children.

Background Only one mathematical model to date describes human growth and its different phases from fetal life until adult height. Aim To develop a model describing growth from fetal life to adult height taking maturation/biological tempo into consideration. Methods Subjects: The model was developed based on longitudinal mean height values obtained from published growth references for a cohort of 3650 healthy Swedish children followed from birth circa 1974 until adult height combined with birth-length for circa 400 000 healthy infants born 1990-1995. Results The QEPS-model for individual growth was constructed with a combination of four basic shape-invariant growth functions: a quadratic Q-function and a negative exponential E-function, both started during fetal life, 8 months before birth; the E-function levelled off after birth, whereas the Q-function continued until end of growth. A specific nonlinear pubertal P-function started at onset of puberty, and a stop S-function ended growth according to both the Q-function continuing during puberty and the specific P-function. For each function, an individual height-scale parameter was defined, and for the E- and P-functions, a time-scale parameter; giving six modifying parameters in total. In addition standardized proportional scores were used for biological interpretations. The QEPS-model was used to fit and generate mathematical functions suitable to describe the growth of the healthy population of Swedish children; thereafter, the model was modified using four height-scale parameters to model individual height in cm, and two time-scale parameters to adjust for the individual tempo of growth. Individual confidence intervals were calculated for all parameters. Conclusions A new shape-invariant growth model, QEPS, was developed, that requires only four basic growth functions to describe the total pattern of growth in height from fetal life to adult height, with addition of height- and time-scale parameters describing individual growth. The model can describe a wide variety of growth curves. Moreover, it is the first model to provide confidence intervals which enable us to describe the precision/quality of individual parameters.

To establish new reference values for measurements of waist circumference and waist-to-height ratio in preschool children.A population-based, cross-sectional study of 4502 children aged 0-5 years derived from child health care in a Swedish county. Measurements of weight, height and waist circumference were recorded using a standardized procedure.New reference values for waist circumference and waist-to-height ratio for preschool children are presented. Reference charts were constructed and are presented. Waist circumference increased with age (r = 0.80, p0.001). After adjustment to the individual height, expressed as waist-to-height ratio, there was an inverse correlation to age during the first 5 years of age (r = -0.87, p0.001).The new reference values for waist circumference and waist-to-height ratio for Swedish preschool children enable future identification of new risk populations for childhood obesity. For clinicians, new reference charts for these two variables are provided for practical use.

The aim of the study was to develop and validate models that could predict the growth responses to GH therapy of individual children. Models for prediction of the initial one and 2-y growth response were constructed from a cohort of 269 prepubertal children (Model group) with isolated GH deficiency or idiopathic short stature, using a nonlinear multivariate data fitting technique. Five sets of clinical information were used. The "Basic model" was created using auxological data from the year before the start of GH treatment and parental heights. In addition to Basic model data, the other four models included growth data from the first 2 y of life, or IGF-I, or GH secretion estimated during a provocation test (AITT) or a spontaneous GH secretion profile. The performance of the models was validated by calculating the differences between predicted and observed growth responses in 149 new GH treated children (Validation group) who fulfilled the inclusion criteria used in the original cohort. The SD of these differences (SD(res)) in the validation group was compared with the SD(res) for the model group. For the 1st y, the SD(res) for the Basic model was 0.28 SDscores. The lowest SD(res) (0.19 SDscores), giving the most narrow prediction interval, was achieved adding the 24h GH profile and data on growth from the first 2 y of life to the Basic model. The models presented permit estimation of GH responsiveness in children over a broad range in GH secretion, and with an accuracy of the models substantially better than when using maximal GH response during an provocation test. The predicted individual growth response, calculated using a computer program, can serve as a guide for evidence-based decisions when selecting children to GH treatment.

Growth hormone (GH) promotes longitudinal growth and bone mineralization. In this study, a proteomic approach was used to analyze the association between serum protein expression pattern and height-adjusted bone mineralization in short prepubertal children receiving GH treatment. Patterns of protein expression were compared with those associated with longitudinal bone growth. Specific protein expression patterns associated with changes in height-adjusted bone mineralization in response to GH treatment were identified. Out of the 37 peaks found in significant regression models, 27 were uniquely present in models correlated with changes in bone mineralization and 7 peaks were uniquely present in models correlated with changes in height. The peaks identified corresponded to apolipoproteins, transthyretin, serum amyloid A4 and hemoglobin beta. We conclude that a proteomic approach could be used to identify specific protein expression patterns associated with bone mineralization in response to GH treatment and that height-adjusted bone mineralization and longitudinal bone growth are regulated partly by the same and partly by different mechanisms. Protein isoforms with different post-translational modifications might be of importance in the regulation of these processes. However, further validation is needed to assess the clinical significance of the results.

Background Mathematical models can be used to predict individual growth responses to growth hormone (GH) therapy. The aim of this study was to construct and validate high-precision models to predict the growth response to GH treatment of short children, independent of their GH status, birth size and gestational age. As the GH doses are included, these models can be used to individualize treatment. Methods Growth data from 415 short prepubertal children were used to construct models for predicting the growth response during the first years of GH therapy. The performance of the models was validated with data from a separate cohort of 112 children using the same inclusion criteria. Results Using only auxological data, the model had a standard error of the residuals (SDres), of 0.23 SDS. The model was improved when endocrine data (GHmax profile, IGF-I and leptin) collected before starting GH treatment were included. Inclusion of these data resulted in a decrease of the SDres to 0.15 SDS (corresponding to 1.1 cm in a 3-year-old child and 1.6 cm in a 7-year old). Validation of these models with a separate cohort, showed similar SDres for both types of models. Preterm children were not included in the Model group, but predictions for this group were within the expected range. Conclusion These prediction models can with high accuracy be used to identify short children who will benefit from GH treatment. They are clinically useful as they are constructed using data from short children with a broad range of GH secretory status, birth size and gestational age.