How can we best chart children's growth in the paperless age? The UK experience.

Growth charts have played an integral part in the monitoring and assessment of children's health for the past 50 years, but their use is now under threat as paperless electronic systems become more widely used. While the obvious solution is to adopt electronic charting systems, this can prove challenging in practice. This article describes the key issues to consider in planning this transition and the charting options available, ranging from bespoke local systems to commercial packages and a new initiative by the Royal College of Paediatrics and Child Health.

Growth reference charts for children with hypochondroplasia.

Hypochondroplasia (HCH) is a rare skeletal dysplasia causing mild short stature. There is a paucity of growth reference charts for this population. Anthropometric data were collected to generate height, weight, and head circumference (HC) growth reference charts for children with a diagnosis of HCH. Mixed longitudinal anthropometric data and genetic analysis results were collected from 14 European specialized skeletal dysplasia centers. Growth charts were generated using Generalized Additive Models for Location, Scale, and Shape. Measurements for height (983), weight (896), and HC (389) were collected from 188 (79 female) children with a diagnosis of HCH aged 0-18 years. Of the 84 children who underwent genetic testing, a pathogenic variant in FGFR3 was identified in 92% (77). The data were used to generate growth references for height, weight, and HC, plotted as charts with seven centiles from 2nd to 98th, for ages 0-4 and 0-16 years. HCH-specific growth charts are important in the clinical care of these children. They help to identify if other comorbidities are present that affect growth and development and serve as an important benchmark for any prospective interventional research studies and trials.

Quantifying Variability in Motor Function in Duchenne Muscular Dystrophy: UK Centiles for the NorthStar Ambulatory Assessment, 10 m Walk Run Velocity and Rise from Floor Velocity in GC Treated Boys.

Background Boys with Duchenne Muscular Dystrophy (DMD) display heterogeneous motor function trajectory in clinics, which represents a significant obstacle to monitoring. OBJECTIVE: In this paper, we present the UK centiles for the North Star Ambulatory Assessment (NSAA), the 10 m walk/run time (10MWR) and velocity (10MWRV), and the rise from floor time (RFF) and velocity (RFFV) created from a cohort of glucocorticoid treated DMD boys between the age of 5 and 16 years. METHODS: Participants were included from the UK NorthStar registry if they had initiated steroids (primarily deflazacorts/prednisolone, intermittent/daily) and were not enrolled in an interventional trial. Assessments were included if the participant had a complete NSAA, the timed tests had been completed or the corresponding items were 0, or the participant was recorded as non-ambulant, in which case the NSAA was assumed 0. RESULTS: We analysed 3987 assessments of the NSAA collected from 826 participants. Of these, 1080, 1849 and 1199 were imputed as 0 for the NSAA, RFFV and 10MWRV respectively. The 10th, 25th, 50th, 75th and 90th centiles were presented. The NSAA centiles showed a peak score of 14, 20, 26, 30 and 32 respectively, with loss of ambulation at 10.7, 12.2 and 14.3 years for the 25th, 50th and 75th centiles, respectively. The centiles showed loss of rise from floor at 8.6, 10.1 and 11.9 years and a loss of 10MWR of 0 at 8.9, 10.3 and 13.8 years for the 25th, 50th and 75th centiles, respectively. The centiles were pairwise less correlated than the raw scores, suggesting an increased ability to detect variability in the DMD cohort. CONCLUSIONS: The NSAA, 10MWR and RFF centiles may provide insights for clinical monitoring of DMD boys, particularly in late ambulatory participants who are uniformly declining. Future work will validate the centiles in national and international natural history cohorts.

Faster rehabilitation weight gain during childhood is associated with risk of non-communicable disease in adult survivors of severe acute malnutrition.

Nutritional rehabilitation during severe acute malnutrition (SAM) aims to quickly restore body size and minimize poor short-term outcomes. We hypothesized that faster weight gain during treatment is associated with greater cardiometabolic risk in adult life. Anthropometry, body composition (DEXA), blood pressure, blood glucose, insulin and lipids were measured in a cohort of adults who were hospitalized as children for SAM between 1963 and 1993. Weight and height measured during hospitalization and at one year post-recovery were abstracted from hospital records. Childhood weight gain during nutritional rehabilitation and weight and height gain one year post-recovery were analysed as continuous variables, quintiles and latent classes in age, sex and minimum weight-for-age z-scores-adjusted regression models against adult measurements. Data for 278 adult SAM survivors who had childhood admission records were analysed. Of these adults, 85 also had data collected 1 year post-hospitalisation. Sixty percent of participants were male, mean (SD) age was 28.2 (7.7) years, mean (SD) BMI was 23.6 (5.2) kg/m2. Mean admission age for SAM was 10.9 months (range 0.3-36.3 months), 77% were wasted (weight-for-height z-scores<-2). Mean rehabilitation weight gain (SD) was 10.1 (3.8) g/kg/day and 61.6 (25.3) g/day. Rehabilitation weight gain > 12.9 g/kg/day was associated with higher adult BMI (difference = 0.5 kg/m2, 95% CI: 0.1-0.9, p = 0.02), waist circumference (difference = 1.4 cm, 95% CI: 0.4-2.4, p = 0.005), fat mass (difference = 1.1 kg, 95% CI: 0.2-2, p = 0.02), fat mass index (difference = 0.32kg/m2, 95% CI: -0.0001-0.6, p = 0.05), and android fat mass (difference = 0.09 kg, 95% CI: 0.01-0.2, p = 0.03). Post-recovery weight gain (g/kg/month) was associated with lean mass (difference = 1.3 kg, 95% CI: 0.3-2.4, p = 0.015) and inversely associated with android-gynoid fat ratio (difference = -0.03, 95% CI: -0.07to-0.001 p = 0.045). Rehabilitation weight gain exceeding 13g/kg/day was associated with adult adiposity in young, normal-weight adult SAM survivors. This challenges existing guidelines for treating malnutrition and warrants further studies aiming at optimising these targets.

Regional references vs. international standards for assessing weight and length by gestational age in Lithuanian neonates.

Introduction: There is no global consensus as to which standards are the most appropriate for the assessment of birth weight and length. The study aimed to compare the applicability of regional and global standards to the Lithuanian newborn population by sex and gestational age, based on the prevalence of small or large for gestational age (SGA/LGA). Materials and Methods: Analysis was performed on neonatal length and weight data obtained from the Lithuanian Medical Birth Register from 1995 to 2015 (618,235 newborns of 24-42 gestational weeks). Their distributions by gestation and sex were estimated using generalized additive models for location, scale, and shape (GAMLSS), and the results were compared with the INTERGROWTH-21st (IG-21) standard to evaluate the prevalence of SGA/LGA (10th/90th centile) at different gestational ages. Results: The difference in median length at term between the local reference and IG-21 was 3 cm-4 cm, while median weight at term differed by 200 g. The Lithuanian median weight at term was higher than in IG-21 by a full centile channel width, while the median length at term was higher by two channel widths. Based on the regional reference, the prevalence rates of SGA/LGA were 9.7%/10.1% for boys and 10.1%/9.9% for girls, close to the nominal 10%. Conversely, based on IG-21, the prevalence of SGA in boys/girls was less than half (4.1%/4.4%), while the prevalence of LGA was double (20.7%/19.1%). Discussion: Regional population-based neonatal references represent Lithuanian neonatal weight and length much more accurately than the global standard IG-21 which provides the prevalence rates for SGA/LGA that differ from the true values by a factor of two.

Post-malnutrition growth and its associations with child survival and non-communicable disease risk: a secondary analysis of the Malawi 'ChroSAM' cohort.

OBJECTIVE: To explore patterns of post-malnutrition growth (PMGr) during and after treatment for severe malnutrition and describe associations with survival and non-communicable disease (NCD) risk 7 years post-treatment. DESIGN: Six indicators of PMGr were derived based on a variety of timepoints, weight, weight-for-age z-score and height-for-age z-score (HAZ). Three categorisation methods included no categorisation, quintiles and latent class analysis (LCA). Associations with mortality risk and seven NCD indicators were analysed. SETTING: Secondary data from Blantyre, Malawi between 2006 and 2014. PARTICIPANTS: A cohort of 1024 children treated for severe malnutrition (weight-for-length z-score < 70 % median and/or MUAC (mid-upper arm circumference) < 110 mm and/or bilateral oedema) at ages 5-168 months. RESULTS: Faster weight gain during treatment (g/d) and after treatment (g/kg/day) was associated with lower risk of death (adjusted OR 0·99, 95 % CI 0·99, 1·00; and adjusted OR 0·91, 95 % CI 0·87, 0·94, respectively). In survivors (mean age 9 years), it was associated with greater hand grip strength (0·02, 95 % CI 0·00, 0·03) and larger HAZ (6·62, 95 % CI 1·31, 11·9), both indicators of better health. However, faster weight gain was also associated with increased waist:hip ratio (0·02, 95 % CI 0·01, 0·03), an indicator of later-life NCD risk. The clearest patterns of association were seen when defining PMGr based on weight gain in g/d during treatment and using the LCA method to describe growth patterns. Weight deficit at admission was a major confounder. CONCLUSIONS: A complex pattern of benefits and risks is associated with faster PMGr. Both initial weight deficit and rate of weight gain have important implications for future health.

Centile reference chart for resting metabolic rate through the life course.

OBJECTIVE: Reference centile charts are widely used for the assessment of growth and have progressed from describing height and weight to include body composition variables such as fat and lean mass. Here, we present centile charts for an index of resting energy expenditure (REE) or metabolic rate, adjusted for lean mass versus age, including both children and adults across the life course. DESIGN, PARTICIPANTS AND INTERVENTION: Measurements of REE by indirect calorimetry and body composition using dual-energy X-ray absorptiometry were made in 411 healthy children and adults (age range 6-64 years) and serially in a patient with resistance to thyroid hormone α (RTHα) between age 15 and 21 years during thyroxine therapy. SETTING: NIHR Cambridge Clinical Research Facility, UK. RESULTS: The centile chart indicates substantial variability, with the REE index ranging between 0.41 and 0.59 units at age 6 years, and 0.28 and 0.40 units at age 25 years (2nd and 98th centile, respectively). The 50th centile of the index ranged from 0.49 units (age 6 years) to 0.34 units (age 25 years). Over 6 years, the REE index of the patient with RTHα varied from 0.35 units (25th centile) to 0.28 units (<2nd centile), depending on changes in lean mass and adherence to treatment. CONCLUSION: We have developed a reference centile chart for an index of resting metabolic rate in childhood and adults, and shown its clinical utility in assessing response to therapy of an endocrine disorder during a patient's transition from childhood to adult.

World variation in head circumference for children from birth to 5 years and a comparison with the WHO standards.

OBJECTIVE: A recent review reported that the WHO 2006 growth standards reflect a smaller head circumference at 24 months than seen in 18 countries. Whether this happens in early infancy and to what extent populations differ is not clear. This scooping review aimed to estimate the rates of children in different populations identified as macrocephalic or microcephalic by WHO standards. METHODS: We reviewed population-representative head circumference-for-age references. For each reference, we calculated the percentages of head circumferences that would be classified as microcephalic (<3rd WHO centile) or macrocephalic (>97th WHO centile) at selected ages. RESULTS: Twelve references from 11 countries/regions (Belgium, China, Ethiopia, Germany, Hong Kong, India, Japan, Norway, Saudi Arabia, UK and USA) were included. Median head circumference was larger than that for the Multicentre Growth Reference Study populations in both sexes in all these populations except for Japanese and Chinese children aged 1 month and Indians. Overall, at 12/24 months, 8%-9% children would be classified as macrocephalic and 2% would be classified as microcephalic, compared with the expected 3%. However at 1 month, there were geographic differences in the rate of macrocephaly (6%-10% in Europe vs 1%-2% in Japan and China) and microcephaly (1%-3% vs 6%-14%, respectively). CONCLUSIONS: Except for Indians and some Asian neonates, adopting the WHO head circumference standards would overdiagnose macrocephaly and underdiagnose microcephaly. Local population-specific cut-offs or references are more appropriate for many populations. There is a need to educate healthcare professionals about the limitations of the WHO head circumference standards.

Fitness of INTERGROWTH-21st birth weight standards for Chinese-ethnicity babies.

OBJECTIVE: To determine the fitness of the INTERGROWTH-21st birth weight standards (INTERGROWTH21) for ethnic Chinese babies compared with a local reference (FOK2003). DESIGN: Population-based analysis of territory-wide birth data. SETTING: All public hospitals in Hong Kong. PARTICIPANTS: Live births between 24 and 42 complete weeks' gestation during 2006-2017. MAIN OUTCOME MEASURES: Babies' birth weight Z-scores were calculated using published methods. The two references were compared in three aspects: (1) the proportions of large-for-gestational-age (LGA) or small-for-gestational-age (SGA) infants, (2) the gestation-specific and sex-specific mean birth weight Z-scores and (3) the predictive power for SGA-related complications. RESULTS: 488 896 infants were included. Using INTERGROWTH21, among neonates born <33 weeks' gestation, the mean birth weight Z-scores per week were closer to zero (-0.2 to 0.05), while most of them were further from zero (0.06 to 0.34) after excluding infants with a high risk of abnormal intrauterine growth. Compared with FOK2003, INTERGROWTH21 classified smaller proportions of infants as SGA (8.3% vs 9.6%) and LGA (6.6% vs 7.9%), especially SGA among preterm infants (13.1% vs 17.0%). The area under the receiver operating characteristic curve for predicting SGA-related complications was greater with FOK2003 (0.674, 95% CI 0.670 to 0.677) than INTERGROWTH21 (0.658, 95% CI 0.655 to 0.661) (p<0.001). CONCLUSIONS: INTERGROWTH21 performed less well than FOK2003, a local reference for ethnic Chinese babies, especially in infants born <33 weeks' gestation. Although the differences are clinically small, both these references performed poorly for extremely preterm infants, and thus a more robust chart based on a larger sample of appropriately selected infants is needed.

Changes in the growth of very preterm infants in England 2006-2018.

OBJECTIVE: To compare weight gain from birth to term equivalent age in very preterm infants in England born during two eras (2006-2011 and 2014-2018); to assess demographic and care factors influencing weight gain. METHODS: Data for infants born before 32 weeks of gestation during 2014-2018 in England were obtained (29 687 infants). Weight gain modelled using SuperImposition by Translation And Rotation (SITAR), with infants grouped by gestational week. A cohort from 2006 to 2011 was used for comparison (3288 infants). Multiple linear regression was used to assess factors influencing change in weight SD score from birth to 36 weeks postmenstrual age. RESULTS: Weight gain velocity (termed 'intensity' in SITAR models) was greater in the more recent cohort for all gestation groups born before 30 weeks of gestation. After adjustment for gestation, birth weight and other perinatal factors, care elements associated with faster weight gain included delivery in a level 3 unit (0.09 SD less weight gain deficit, 95% CI: 0.07 to 0.10) and parenteral nutrition initiation during the first day of life (0.08 SD, 95% CI: 0.06 to 0.10). Factors associated with slower weight gain included early ventilation (-0.07 SD, 95% CI: -0.08 to -0.05) and less deprived neighbourhood (-0.012 SD per Index of Multiple Deprivation decile, 95% CI: -0.015 to -0.009). CONCLUSIONS: Weight gain for extremely preterm infants was faster during 2014-2018 than during 2006-2011. Early initiation of parenteral nutrition and birth in a level 3 unit may contribute to faster weight gain.

An improved algorithm to harmonize child overweight and obesity prevalence rates.

BACKGROUND: Prevalence rates of child overweight and obesity for a group of children vary depending on the BMI reference and cut-off used. Previously we developed an algorithm to convert prevalence rates based on one reference to those based on another. OBJECTIVE: To improve the algorithm by combining information on overweight and obesity prevalence. METHODS: The original algorithm assumed that prevalence according to two different cut-offs A and B differed by a constant amount dz on the z-score scale. However the results showed that the z-score difference tended to be greater in the upper tail of the distribution and was better represented by b × dz , where b was a constant that varied by group. The improved algorithm uses paired prevalence rates of overweight and obesity to estimate b for each group. Prevalence based on cut-off A is then transformed to a z-score, adjusted up or down according to b × dz and back-transformed, and this predicts prevalence based on cut-off B. The algorithm's performance was tested on 228 groups of children aged 6-17 years from 20 countries. RESULTS: The revised algorithm performed much better than the original. The standard deviation (SD) of residuals, the difference between observed and predicted prevalence, was 0.8% (n = 2320 comparisons), while the SD of the difference between pairs of the original prevalence rates was 4.3%, meaning that the algorithm explained 96.7% of the baseline variance (88.2% with original algorithm). CONCLUSIONS: The improved algorithm appears to be effective at harmonizing prevalence rates of child overweight and obesity based on different references.

Life history trade-offs associated with exposure to low maternal capital are different in sons compared to daughters: Evidence from a prospective Brazilian birth cohort.

Background: Environmental exposures in early life explain variability in many physiological and behavioural traits in adulthood. Recently, we showed that exposure to a composite marker of low maternal capital explained the clustering of adverse behavioural and physical traits in adult daughters in a Brazilian birth cohort. These associations were strongly mediated by whether or not the daughter had reproduced by the age of 18 years. Using evolutionary life history theory, we attributed these associations to trade-offs between competing outcomes, whereby daughters exposed to low maternal capital prioritised investment in reproduction and defence over maintenance and growth. However, little is known about such trade-offs in sons. Methods: We investigated 2,024 mother-son dyads from the same birth cohort. We combined data on maternal height, body mass index, income, and education into a composite "maternal capital" index. Son outcomes included reproductive status at the age of 18 years, growth trajectory, adult anthropometry, body composition, cardio-metabolic risk, educational attainment, work status, and risky behaviour (smoking, violent crime). We tested whether sons' early reproduction and exposure to low maternal capital were associated with adverse outcomes and whether this accounted for the clustering of adverse outcomes within individuals. Results: Sons reproducing early were shorter, less educated, and more likely to be earning a salary and showing risky behaviour compared to those not reproducing, but did not differ in foetal growth. Low maternal capital was associated with a greater likelihood of sons' reproducing early, leaving school, and smoking. High maternal capital was positively associated with sons' birth weight, adult size, and staying in school. However, the greater adiposity of high-capital sons was associated with an unhealthier cardio-metabolic profile. Conclusion: Exposure to low maternal investment is associated with trade-offs between life history functions, helping to explain the clustering of adverse outcomes in sons. The patterns indicated future discounting, with reduced maternal investment associated with early reproduction but less investment in growth, education, or healthy behaviour. However, we also found differences compared to our analyses of daughters, with fewer physical costs associated with early reproduction. Exposure to intergenerational "cycles of disadvantage" has different effects on sons vs. daughters, hence interventions may have sex-specific consequences.

Assessment of height growth in Indian children using growth centiles and growth curves.

BACKGROUND: Growth centiles and growth curves are two ways to present child anthropometry; however, they differ in the type of data used, the method of analysis, the biological parameters fitted and the form of interpretation. AIM: To fit and compare height growth centiles and curves in Indian children. SUBJECTS AND METHODS: 1468 children (796 boys) from Pune India aged 6-18 years with longitudinal data on age and height (n = 7781) were analysed using GAMLSS (Generalised Additive Models for Location Scale and Shape) for growth centiles, and SITAR (SuperImposition by Rotation and Translation) for growth curves. RESULTS: SITAR explained 98.7% and 98.8% of the height variance in boys and girls, with mean age at peak height velocity 13.1 and 11.0 years, and mean peak velocity 9.0 and 8.0 cm/year, respectively. GAMLSS (Box-Cox Cole Green model) also captured the pubertal growth spurt but the centiles were shallower than the SITAR mean curve. Boys showed a mid-growth spurt at age 8 years. CONCLUSION: GAMLSS displays the distribution of height in the population by age and sex, while SITAR effectively and parsimoniously summarises the pattern of height growth in individual children. The two approaches provide distinct, useful information about child growth.

Towards standardised and valid anthropometric indicators of nutritional status in middle childhood and adolescence.

Recognition of the importance of nutrition during middle childhood (age 5-9 years) and adolescence (age 10-19 years) is increasing, particularly in the context of global food insecurity and rising overweight and obesity rates. Until now, policy makers have been slow to respond to rapidly changing patterns of malnutrition across these age groups. One barrier has been a scarcity of consistent and regular nutrition surveillance systems for these age groups. What should be measured, and how best to operationalise anthropometric indicators that have been the cornerstone of nutrition surveillance in younger children and in adults, has been the topic of ongoing debate. Even with consensus on the importance of a given anthropometric indicator, difficulties arise in interpreting trends over time and between countries owing to the use of different terminologies, reference data, and cutoff points. In this Viewpoint we highlight the need to revisit anthropometric indicators across middle childhood and adolescence, a process that will require WHO and UNICEF coordination, the engagement of national implementors and policy makers, and partnership with research communities and donors.

Implications of leg length for metabolic health and fitness.

Background and objectives: Several studies have linked longer legs with favorable adult metabolic health outcomes and greater offspring birth weight. A recent Mendelian randomization study suggested a causal link between height and cardiometabolic risk; however, the underlying reasons remain poorly understood. Methodology: Using a cross-sectional design, we tested in a convenience sample of 70 healthy young women whether birth weight and tibia length as markers of early-life conditions associated more strongly with metabolically beneficial traits like organ size and skeletal muscle mass (SMM) than a statistically derived height-residual variable indexing later, more canalized growth. Results: Consistent with the 'developmental origins of health and disease' hypothesis, we found relatively strong associations of tibia length-but not birth weight-with adult organ size, brain size, SMM and resting energy expenditure measured by magnetic resonance imaging (MRI), dual-energy X-ray absorptiometry and indirect calorimetry, respectively. Conclusions and implications: Building on prior work, these results suggest that leg length is a sensitive marker of traits directly impacting metabolic and reproductive health. Alongside findings in the same sample relating tibia length and height-residual to MRI-measured pelvic dimensions, we suggest there may exist a degree of coordination in the development of long bone, lean mass and pelvic traits, possibly centered on early, pre-pubertal growth periods. Such phenotypic coordination has important implications for fitness, serving to benefit both adult health and the health of offspring in subsequent generations.

Neonatal head circumference by gestation reflects adaptation to maternal body size: comparison of different standards.

Neonatal head circumference (HC) not only represents the brain size of Homo sapiens, but is also an important health risk indicator. Addressing a lack of comparative studies on head size and its variability in term and preterm neonates from different populations, we aimed to examine neonatal HC by gestation according to a regional reference and a global standard. Retrospective analysis of data on neonatal HC obtained from the Lithuanian Medical Birth Register from 2001 to 2015 (423 999 newborns of 24-42 gestational weeks). The varying distribution by gestation and sex was estimated using GAMLSS, and the results were compared with the INTERGROWTH-21st standard. Mean HC increased with gestation in both sexes, while its fractional variability fell. The 3rd percentile matched that for INTERGROWTH-21st at all gestations, while the 50th and 97th percentiles were similar up to 27 weeks, but a full channel width higher than INTERGROWTH-21st at term. INTERGROWTH-21st facilitates the evaluation of neonatal HC in early gestations, while in later gestations, the specific features of neonatal HC of a particular population tend to be more precisely represented by regional references.

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.

Exploring an algorithm to harmonize International Obesity Task Force and World Health Organization child overweight and obesity prevalence rates.

BACKGROUND: The International Obesity Task Force (IOTF) and World Health Organization (WHO) body mass index (BMI) cut-offs are widely used to assess child overweight, obesity and thinness prevalence, but the two references applied to the same children lead to different prevalence rates. OBJECTIVES: To develop an algorithm to harmonize prevalence rates based on the IOTF and WHO cut-offs, to make them comparable. METHODS: The cut-offs are defined as age-sex-specific BMI z-scores, for example, WHO +1 SD for overweight. To convert an age-sex-specific prevalence rate based on reference cut-off A to the corresponding prevalence based on reference cut-off B, first back-transform the z-score cut-offs zA and zB to age-sex-specific BMI cut-offs, then transform the BMIs to z-scores zB,A and zA,B using the opposite reference. These z-scores together define the distance between the two cut-offs as the z-score difference dzA,B=12zB-zA+zA,B-zB,A . Prevalence in the target group based on cut-off A is then transformed to a z-score, adjusted up or down according to dzA,B and back-transformed, and this predicts prevalence based on cut-off B. The algorithm's performance was tested on 74 groups of children from 14 European countries. RESULTS: The algorithm performed well. The standard deviation (SD) of the difference between pairs of prevalence rates was 6.6% (n = 604), while the residual SD, the difference between observed and predicted prevalence, was 2.3%, meaning that the algorithm explained 88% of the baseline variance. CONCLUSIONS: The algorithm goes some way to addressing the problem of harmonizing overweight and obesity prevalence rates for children aged 2-18.