Early childhood growth trajectories in a Medicaid population

Trajectory Patterns of Weight and Length in Children: From Birth Until 2-Years of Age

OBJECTIVE

The aim was to identify trajectory patterns of weight and length in children from birth until two years of life and establish associations with maternal and child characteristics.

METHODS

A mixed-cohort study was conducted in public health services in Colombo-PR, Brazil, between 2018 and 2022. Pregnancy information was gathered through anthropometric data collection and questionnaires. Birth data were extracted from birth record forms, while weight and length data in the first two years of life were obtained from physical and electronic health service records. Weight and length trajectory patterns were identified using a group-based trajectory model. The definition of the number of trajectory patterns to be selected considered the model fit to the type of variable, its practical utility, as well as the probabilities of group membership.

RESULTS

Two trajectory patterns of weight and length were identified among the children. The majority exhibited a pattern of weight (67.8%, n = 382) and length (90.9%, n = 472) considered high and stable, with a tendency to decelerate from one and a half years of age. The probability of belonging to the lower weight gain group was associated with female sex (41.5%, p < 0.001), smoking during pregnancy (48.7%, p = 0.008), prematurity (65.0%, p = 0.001), cesarean delivery (36.4%, p = 0.009), small for gestational age (69.0%, p < 0.001), and twinning (69.2%, p = 0.002). Similarly, the probability of belonging to the lower length gain group was associated with female sex (11.7%, p < 0.001), smoking during pregnancy (20.6%, p = 0.003), cesarean delivery (10.1%, p = 0.048), born small for gestational age (46.4%, p < 0.001), and twinning (46.1%, p < 0.001).

CONCLUSION

Conditions during pregnancy and childbirth can impact growth patterns in the first two years of life.

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.