Latent classes of anthropometric growth in early childhood using uni- and multivariate approaches in a South African birth cohort
Year: 2025
Type: article
Abstract: 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 (n 1 =516, n 2 =112, n 3 =187, n 4 =321) and standardized weight (n 1 =263, n 2 =150, n 3 =584, n 4 =142), three latent growth classes within Body Mass Index (BMI) (n 1 =481, n 2 =485, n 3 =149) and Weight for length/height (WFH) (n 1 =321, n 2 =710, n 3 =84) and five latent growth classes within the multivariate response of standardized height and standardized weight (n 1 =318, n 2 =205, n 3 =75, n 4 =296, n 5 =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. Key Messages Four latent classes of growth were identified within standardized height and standardized weight. Three latent classes of growth were identified within standardized body mass index and standardized weight-for-length/height. Five latent classes of growth were identified within a multivariate response of standardized height and standardized weight. Latent classes identified using various composite measures of standardized height and standardized weight (standardized body mass index and standardized weight-for-length/height and a multivariate response of standardized height and standardized weight) were distinct, reiterating the benefit of examining each outcome. A strong association was found between various growth classes and abnormal growth features such as rapid weight gain, stunting, underweight and overweight.
Source: PLoS ONE
Institution: University of Cape Town
Language: English
Subfield: Nutrition and Dietetics
Field: Nursing
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,382
Funders: Foundation for the National Institutes of Health, Carnegie Corporation of New York, Bill and Melinda Gates Foundation, South African Medical Research Council, University of Cape Town, National Institutes of Health, Medical Research Council, National Human Genome Research Institute, National Institute of Allergy and Infectious Diseases
Awards: G1543706905, G1773366302, G3482719555, J. Craig Venter Institute - to use new molecular technologies to elucidate the nasopharyngeal microbiome in GEMS & PERCH sites where factors such as ethnicity, environment, an..., G3685900323, Center for Research on the Respiratory Microbiota of African Children (ReMAC), G5562055028, G6432821569, G9000260478
OpenAlex ID: W4408824152