Evidence map›Paper›PMID 42286114›Full record

ArticleInternational journal of obesity (2005)2026

Capturing infant and child growth dynamics with P-splines mixed effects models.

María Alejandra Hernandez, Zheyuan Li, Tim J Cole, Yi Ying Ong, Kate Tilling, Ahmed Elhakeem

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Article in International journal of obesity (2005), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

María Alejandra HernandezMRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK.
Zheyuan LiSchool of Mathematics and Statistics, Henan University, Kaifeng, Henan, China.ORCID http://orcid.org/0000-0002-7434-5947
Tim J ColeUCL Great Ormond Street Institute of Child Health, London, UK.ORCID http://orcid.org/0000-0001-5711-8200
Yi Ying OngYong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.ORCID http://orcid.org/0000-0003-3072-765X
Kate TillingMRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK.
Ahmed ElhakeemMRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK. a.elhakeem@bristol.ac.uk.ORCID http://orcid.org/0000-0001-7637-6360

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundInvestigating early life growth dynamics is important for understanding the developmental origins of obesity. Basis splines (B-splines) provide excellent flexibility for modelling complex growth patterns, but they are prone to overfitting. Penalised B-splines (P-splines) extend B-splines by using a penalty to control their flexibility and avoid overfitting. Despite their advantages, P-splines remain underused in epidemiology, partly due to lack of guidance and accessible software. Our aim was to provide a guide on applying P-spline linear mixed effects models to analyse early life growth trajectories and extract key growth features.

methodsWe outline the theoretical foundation and fitting procedures for P-splines and illustrate their use on repeated height, weight, and body mass index (BMI) measures up to age 10 years from a Southeast Asian birth cohort (n = 1014). P-splines linear mixed effects models were fitted by reformulating P-splines as mixed models with sparse matrices for efficient estimation. From the fitted trajectories, we estimated infant peak growth velocity, magnitude and timing of infant peak BMI and childhood rebound BMI, and examined their sex differences, intercorrelations, and associations with prenatal factors.

resultsInfant peak height velocity (means:.4.4 vs. 3.9 cm/month) and peak weight velocity (1121 vs. 890 grams/month) was higher in boys than girls. Infancy peak BMI (17.4 vs. 16.8 kg/m

conclusionsP-splines simplify knot selection, making them a valuable approach for growth modelling. Software, code and datasets are provided to promote uptake of this method.

Indexed as

Child DevelopmentBody HeightBody Mass IndexChildChild, PreschoolFemaleHumansInfantInfant, NewbornMale

Identifiers

PMID42286114
PMCPMC13461364

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.