Comparative study of four growth models applied to weight and height growth data in a cohort of US children from birth to 9 years

Head circumference at birth and postnatal growth trajectory in vulnerable groups from Argentina

OBJECTIVES

To investigate the association between the anthropometric status at birth and brain and bone growth during the first year of life. According to the brain-sparing hypothesis, we expect catch-up to be faster in head circumference (HC) than in body length.

METHODS

This is a longitudinal design that included Argentinian infants under 12 months of age with at least three anthropometric records. We classified study participants into four growth status categories according to z-scores for HC (HCZ) and length (LAZ) at birth, with z-score = -2 as a threshold. We used the Count model to describe growth trajectories in HC and length in the first year of life according to the growth status at birth. Recovery indicator for HC and length was taken as the time until the predicted growth trajectory surpassed the threshold curve predicted by z-score = -2 for age.

RESULTS

Growth models included 3399 infants. There were significant differences in the growth parameters between groups in all cases (p < 0.05). Within the group with a low HCZ and a low LAZ at birth, HC recovery was faster than length. In the case of a low z-score for only one of the variables, newborns with a low HCZ recovered faster than individuals born with a low LAZ.

CONCLUSIONS

The postnatal growth pattern in HC and length is associated with the growth status of HC and length at birth. As we hypothesized, the fastest postnatal recovery occurs for HC in cases of intrauterine delayed growth.

A modified Michaelis-Menten equation estimates growth from birth to 3 years in healthy babies in the USA

BACKGROUND

Standard pediatric growth curves cannot be used to impute missing height or weight measurements in individual children. The Michaelis-Menten equation, used for characterizing substrate-enzyme saturation curves, has been shown to model growth in many organisms including nonhuman vertebrates. We investigated whether this equation could be used to interpolate missing growth data in children in the first three years of life and compared this interpolation to several common interpolation methods and pediatric growth models.

METHODS

We developed a modified Michaelis-Menten equation and compared expected to actual growth, first in a local birth cohort (N = 97) then in a large, outpatient, pediatric sample (N = 14,695).

RESULTS

The modified Michaelis-Menten equation showed excellent fit for both infant weight (median RMSE: boys: 0.22 kg [IQR:0.19; 90% < 0.43]; girls: 0.20 kg [IQR:0.17; 90% < 0.39]) and height (median RMSE: boys: 0.93 cm [IQR:0.53; 90% < 1.0]; girls: 0.91 cm [IQR:0.50;90% < 1.0]). Growth data were modeled accurately with as few as four values from routine well-baby visits in year 1 and seven values in years 1-3; birth weight or length was essential for best fit. Interpolation with this equation had comparable (for weight) or lower (for height) mean RMSE compared to the best performing alternative models.

CONCLUSIONS

A modified Michaelis-Menten equation accurately describes growth in healthy babies aged 0-36 months, allowing interpolation of missing weight and height values in individual longitudinal measurement series. The growth pattern in healthy babies in resource-rich environments mirrors an enzymatic saturation curve.

A modified Michaelis-Menten equation estimates growth from birth to 3 years in healthy babies in the US

Background and Objectives

Standard pediatric growth curves cannot be used to impute missing height or weight measurements in individual children. The Michaelis-Menten equation, used for characterizing substrate-enzyme saturation curves, has been shown to model growth in many organisms including nonhuman vertebrates. We investigated this equation could be used to interpolate missing growth data in children in the first three years of life.

Methods

We developed a modified Michaelis-Menten equation and compared expected to actual growth, first in a local birth cohort (N=97) then in a large, outpatient, pediatric sample (N=14,695).

Results

The modified Michaelis-Menten equation showed excellent fit for both infant weight (median RMSE: boys: 0.22kg [IQR:0.19; 90%<0.43]; girls: 0.20kg [IQR:0.17; 90%<0.39]) and height (median RMSE: boys: 0.93cm [IQR:0.53; 90%<1.0]; girls: 0.91cm [IQR:0.50;90%<1.0]). Growth data were modeled accurately with as few as four values from routine well-baby visits in year 1 and seven values in years 1-3; birth weight or length was essential for best fit.

Conclusions

A modified Michaelis-Menten equation accurately describes growth in healthy babies aged 0-36 months, allowing interpolation of missing weight and height values in individual longitudinal measurement series. The growth pattern in healthy babies in resource-rich environments mirrors an enzymatic saturation curve.

A modified Michaelis-Menten equation estimates growth from birth to 3 years in healthy babies in the US

Background and Objectives

Standard pediatric growth curves cannot be used to impute missing height or weight measurements in individual children. The Michaelis-Menten equation, used for characterizing substrate-enzyme saturation curves, has been shown to model growth in many organisms including nonhuman vertebrates. We investigated this equation could be used to interpolate missing growth data in children in the first three years of life.

Methods

We developed a modified Michaelis-Menten equation and compared expected to actual growth, first in a local birth cohort (N=97) then in a large, outpatient, pediatric sample (N=14,695).

Results

The modified Michaelis-Menten equation showed excellent fit for both infant weight (median RMSE: boys: 0.22kg [IQR:0.19; 90%<0.43]; girls: 0.20kg [IQR:0.17; 90%<0.39]) and height (median RMSE: boys: 0.93cm [IQR:0.53; 90%<1.0]; girls: 0.91cm [IQR:0.50;90%<1.0]). Growth data were modeled accurately with as few as four values from routine well-baby visits in year 1 and seven values in years 1-3; birth weight or length was essential for best fit.

Conclusions

A modified Michaelis-Menten equation accurately describes growth in healthy babies aged 0-36 months, allowing interpolation of missing weight and height values in individual longitudinal measurement series. The growth pattern in healthy babies in resource-rich environments mirrors an enzymatic saturation curve.

Longitudinal antimüllerian hormone and its correlation with pubertal milestones

Objective

To examine the changes in AMH levels longitudinally over time and their relationship with both body composition, particularly abdominal adiposity, and milestones of pubertal development in female children.

Design

Secondary analysis of a prospective, longitudinal study.

Setting

University affiliated research center and laboratories.

Patients

Eighty-nine females were examined between 1990 and 2015 to study child growth and development.

Interventions

Demographic, anthropometric, growth, and pubertal milestone data with serum samples stored and subsequently analyzed for AMH.

Main Outcome Measures

Longitudinal change in AMH and predicted AMH levels based on body composition, age, and pubertal milestones including, pubarche, thelarche, and menarche.

Results

Natural log-transformed AMH (AMH_log) levels appeared to have a nonlinear relationship with age, decreasing between 10 and 14 years of age, increasing until 16 years. A mixed effect linear model demonstrated that increased abdominal adiposity (waist/height ratio, WHtR) was significantly associated with the predicted increased AMH_log levels (β=1.37). As females progressed through the Tanner stages, the model predicted decreasing AMH_log values when adjusting for age and WHtR.

Conclusions

Declining AMH levels during puberty may not be reflective of diminished ovarian reserve as observed in adults, but may suggest a permissive role of AMH in the activation of the hypothalamic-pituitary-ovarian axis.

Community context, birth cohorts and childhood body mass index trajectories: Evidence from the China nutrition and health survey 1991-2011

Childhood overweight and obesity have shown an increase in recent birth cohorts. China has undergone rapid socioeconomic transitions accompanied by lifestyle changes that have profoundly affected the physical growth of children. Less empirical research has considered the role of community context on the cohort effects of children's body mass index (BMI) z-score trajectories. We used the mixed effect models for repeated measurements with restricted cubic spline to predict the BMI z-score trajectories in children aged 1-17 years, influenced by different birth cohorts and community context using data from the China Health and Nutrition Survey from 1991 to 2011, and stratified by sex. Results indicated that the mean of BMI z-scores of children aged 1-17 years have increased in the 2000s cohort. Community context contributed to significant differences in BMI z-score increase with age from middle childhood, and this trend of community inequalities divergences in middle childhood in recent birth cohorts. Therefore, to promote equitable growth for all children in China, policy interventions focusing on the community context may have far-reaching effects on the health of children and adolescents.

Comparison of growth models to describe growth from birth to 6 years in a Beninese cohort of children with repeated measurements

OBJECTIVE

To select a growth model that best describes individual growth trajectories of children and to present some growth characteristics of this population.

SETTINGS

Participants were selected from a prospective cohort conducted in three health centres (Allada, Sekou and Attogon) in a semirural region of Benin, sub-Saharan Africa.

PARTICIPANTS

Children aged 0 to 6 years were recruited in a cohort study with at least two valid height and weight measurements included (n=961).

PRIMARY AND SECONDARY OUTCOME MEASURES

This study compared the goodness-of-fit of three structural growth models (Jenss-Bayley, Reed and a newly adapted version of the Gompertz growth model) on longitudinal weight and height growth data of boys and girls. The goodness-of-fit of the models was assessed using residual distribution over age and compared with the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC). The best-fitting model allowed estimating mean weight and height growth trajectories, individual growth and growth velocities. Underweight, stunting and wasting were also estimated at age 6 years.

RESULTS

The three models were able to fit well both weight and height data. The Jenss-Bayley model presented the best fit for weight and height, both in boys and girls. Mean height growth trajectories were identical in shape and direction for boys and girls while the mean weight growth curve of girls fell slightly below the curve of boys after neonatal life. Finally, 35%, 27.7% and 8% of boys; and 34%, 38.4% and 4% of girls were estimated to be underweight, wasted and stunted at age 6 years, respectively.

CONCLUSION

The growth parameters of the best-fitting Jenss-Bayley model can be used to describe growth trajectories and study their determinants.

The aging human body shape

Body shape and composition are heterogeneous among humans with possible impact for health. Anthropometric methods and data are needed to better describe the diversity of the human body in human populations, its age dependence, and associations with health risk. We applied whole-body laser scanning to a cohort of 8499 women and men of age 40–80 years within the frame of the LIFE (Leipzig Research Center for Civilization Diseases) study aimed at discovering health risk in a middle European urban population. Body scanning delivers multidimensional anthropometric data, which were further processed by machine learning to stratify the participants into body types. We here applied this body typing concept to describe the diversity of body shapes in an aging population and its association with physical activity and selected health and lifestyle factors. We find that aging results in similar reshaping of female and male bodies despite the large diversity of body types observed in the study. Slim body shapes remain slim and partly tend to become even more lean and fragile, while obese body shapes remain obese. Female body shapes change more strongly than male ones. The incidence of the different body types changes with characteristic Life Course trajectories. Physical activity is inversely related to the body mass index and decreases with age, while self-reported incidence for myocardial infarction shows overall the inverse trend. We discuss health risks factors in the context of body shape and its relation to obesity. Body typing opens options for personalized anthropometry to better estimate health risk in epidemiological research and future clinical applications.

Longitudinal anthropometry of children and adolescents using 3D-body scanning

3D-body scanning anthropometry is a suitable method for characterization of physiological development of children and adolescents, and for understanding onset and progression of disorders like overweight and obesity. Here we present a novel body typing approach to describe and to interpret longitudinal 3D-body scanning data of more than 800 children and adolescents measured in up to four follow-ups in intervals of 1 year, referring to an age range between 6 and 18 years. We analyzed transitions between body types assigned to lower-, normal- and overweight participants upon development of children and adolescents. We found a virtually parallel development of the body types with only a few transitions between them. Body types of children and adolescents tend to conserve their weight category. 3D body scanning anthropometry in combination with body typing constitutes a novel option to investigate onset and progression of obesity in children.

Trajectories of aggressive and depressive symptoms in male and female overweight children: Do they share a common path or do they follow different routes?

The prevalence of childhood overweight is a major social and public health issue, and primary assessment should focus on early and middle childhood, because weight gain in these phases constitutes a strong predictor of subsequent negative outcomes. Studies on community samples have shown that growth curves may follow linear or non-linear trajectories from early to middle childhood, and can differ based on sex. Overweight children may exhibit a combination of physiological and psychosocial issues, and several studies have demonstrated an association between overweight and internalizing/externalizing behavior. Nevertheless, there is a dearth of longitudinal studies on depressive and aggressive symptoms in children with high BMI. This study adopted a growth curve modeling over three phases to: (1) describe BMI trajectories in two groups of children aged 2–8 (overweight and normal weight) from a community sample; (2) describe the developmental trajectories of children’s aggressive and depressive symptoms from 2 to 8 years of age. Results indicate higher BMI in 2-year-old girls, with males catching up with them by age 8. While overweight females’ BMIs were consistently high, males’ increased at 5 and 8 years. The mean scores for aggressive symptoms at T1 (2 years of age) were the same in all subjects, but a significant deviation occurred from T1 to T2 in both samples, in divergent directions. With regards to children’s depressive symptoms, the two groups had different starting points, with normal weight children scoring lower than overweight youths. Overweight females showed lower depressive scores than overweight males at T1, but they surpassed boys before T2, and showed more maladaptive symptoms at T3. This study solicits professionals working in pediatric settings to consider overweight children’s psychopathological risk, and to be aware that even when children’s BMI does not increase from 2 to 8 years, their psychopathological symptoms may grow in intensity.

Maternal plasma phosphatidylcholine polyunsaturated fatty acids during pregnancy and offspring growth and adiposity

BACKGROUND

Polyunsaturated fatty acids (PUFA) are essential for offspring development, but it is less clear whether pregnancy PUFA status affects growth and adiposity.

METHODS

In 985 mother-offspring pairs from the ongoing Singaporean GUSTO cohort, we analyzed the associations between offspring growth and adiposity outcomes until age 5 years and five PUFAs of interest, measured in maternal plasma at 26-28 weeks' gestation: linoleic acid (LA), arachidonic acid, α-linolenic acid, eicosapentaenoic acid, and docosahexaenoic acid (DHA). We measured fetal growth by ultrasound (n=924), neonatal body composition (air displacement plethysmography (n=252 at birth, and n=317 at age 10 days), and abdominal magnetic resonance imaging (n=317)), postnatal growth (n=979) and skinfold thicknesses (n=981). Results were presented as regression coefficients for a 5% increase in PUFA levels.

RESULTS

LA levels were positively associated with birthweight (β (95% CI): 0.04 (0.01, 0.08) kg), body mass index (0.13 (0.02, 0.25) kg/m²), head circumference (0.11 (0.03, 0.19) cm), and neonatal abdominal adipose tissue volume (4.6 (1.3, 7.8) mL for superficial subcutanous tissue, and 1.2 (0.1, 2.4) mL for internal tissue), but not with later outcomes. DHA levels, although not associated with birth outcomes, were related to higher postnatal length/height: 0.63 (0.09, 1.16) cm at 12 months and 1.29 (0.34, 2.24) cm at 5 years.

CONCLUSIONS

LA was positively associated with neonatal body size, and DHA with child height. Maternal PUFA status during pregnancy may influence fetal and child growth and adiposity.