Abstract:Rapid weight gain (RWG) during infancy is a known risk factor for later childhood obesity. It can be measured using a range of definitions across various time periods in the first 2 years of life. In recent years, some early childhood obesity prevention trials have included a focus on preventing RWG during infancy, with modest success. Overall, RWG during infancy remains common, yet little work has examined whether infants with this growth pattern should receive additional care when it is identified in health-… Show more
“…To identify children that experienced rapid weight gain, a change in zWeight equal or greater than 0.67 within the first nine months of life was used, as per convention, although there is disagreement on the optimal time frame to use (23).…”
Background: Conventional methods for modelling longitudinal growth data focus on the analysis of mean longitudinal trends or the identification of abnormal growth based on cross-sectional standardized z-scores. Latent Class Mixed Modelling (LCMM) considers the underlying heterogeneity in growth profiles and allows for the identification of groups of subjects that follow similar longitudinal trends. Methods: LCMM was used to identify underlying latent profiles of growth for univariate responses of standardized height, standardized weight, standardized body mass index and standardized weight-for-length/height measurements and multivariate response of joint standardized height and standardized weight measurements from birth to five years for a sample of 1143 children from a South African birth cohort, the Drakenstein Child Health Study (DCHS). Allocations across latent growth classes were compared to better understand the differences and similarities across the classes identified given different composite measures of height and weight as input. Results: Four classes of growth within standardized height (n1=516, n2=112, n3=187, n4=321) and standardized weight (n1=263, n2=150, n3=584, n4=142), three latent growth classes within Body Mass Index (BMI) (n1=481, n2=485, n3=149) and Weight for length/height (WFH) (n1=321, n2=710, n3=84) and five latent growth classes within the multivariate response of standardized height and standardized weight (n1=318, n2=205, n3=75, n4=296, n5=242) were identified, each with distinct trajectories over childhood. A strong association was found between various growth classes and abnormal growth features such as rapid weight gain, stunting, underweight and overweight. Conclusions: With the identification of these classes, a better understanding of distinct childhood growth trajectories and their predictors may be gained, informing interventions to promote optimal childhood growth.
“…To identify children that experienced rapid weight gain, a change in zWeight equal or greater than 0.67 within the first nine months of life was used, as per convention, although there is disagreement on the optimal time frame to use (23).…”
Background: Conventional methods for modelling longitudinal growth data focus on the analysis of mean longitudinal trends or the identification of abnormal growth based on cross-sectional standardized z-scores. Latent Class Mixed Modelling (LCMM) considers the underlying heterogeneity in growth profiles and allows for the identification of groups of subjects that follow similar longitudinal trends. Methods: LCMM was used to identify underlying latent profiles of growth for univariate responses of standardized height, standardized weight, standardized body mass index and standardized weight-for-length/height measurements and multivariate response of joint standardized height and standardized weight measurements from birth to five years for a sample of 1143 children from a South African birth cohort, the Drakenstein Child Health Study (DCHS). Allocations across latent growth classes were compared to better understand the differences and similarities across the classes identified given different composite measures of height and weight as input. Results: Four classes of growth within standardized height (n1=516, n2=112, n3=187, n4=321) and standardized weight (n1=263, n2=150, n3=584, n4=142), three latent growth classes within Body Mass Index (BMI) (n1=481, n2=485, n3=149) and Weight for length/height (WFH) (n1=321, n2=710, n3=84) and five latent growth classes within the multivariate response of standardized height and standardized weight (n1=318, n2=205, n3=75, n4=296, n5=242) were identified, each with distinct trajectories over childhood. A strong association was found between various growth classes and abnormal growth features such as rapid weight gain, stunting, underweight and overweight. Conclusions: With the identification of these classes, a better understanding of distinct childhood growth trajectories and their predictors may be gained, informing interventions to promote optimal childhood growth.
“…Reviews indicate that children who show increases in weight-for-age z scores of at least 0.67 over some time frame between birth and 2 years of age have two to four times the risk of having overweight later in childhood compared with children who do not display such rapid increases in growth [1][2][3]. Although these data suggest that identification of rapidly growing infants might offer a potential intervention window, this identification is complicated by the lack of a standardized definition of RIWG and time frame/s over which weight gain should be assessed [4,5].…”
Section: Introductionmentioning
confidence: 99%
“…To date, RIWG has most frequently been defined as an increase in weight‐for‐age z score of at least 0.67 standard deviations (SD) between two time points [5]. The use of weight alone, without consideration of length, likely occurs because it is weight that is more often routinely collected as part of usual growth monitoring at this age and because of the higher reliability of weight measurements compared with length/height.…”
ObjectiveThe aim of this study was to determine which growth indicator (weight, weight‐for‐length, BMI) and time frame (6‐ or 12‐month intervals between 0 and 24 months) of rapid infant weight gain (RIWG) best predicted obesity risk and body composition at 11 years of age.MethodsRIWG (increase ≥0.67 z scores between two time points) was calculated from weight and length/height at birth, 0.5, 1, 1.5, and 2 years. The predictive value of each measure and time frame was calculated in relation to obesity (BMI ≥95th percentile) and body fat (fat mass index [FMI], dual‐energy X‐ray absorptiometry scan) at 11 years.ResultsThe sensitivity (1.5% to 62.1%) and positive predictive value (12.5% to 33.3%) of RIWG to predict obesity varied considerably. Having obesity at any time point appeared a stronger risk factor than any indicator of RIWG for obesity at 11 years. Obesity at any age during infancy consistently predicted a greater FMI of around 1.1 to 1.5 kg/m2 at 11 years, whereas differences for RIWG were inconsistent.ConclusionsA simple measure of obesity status at a single time point between 6 and 24 months of age appeared a stronger risk factor for later obesity and FMI than RIWG assessed by any indicator, over any time frame.
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