Linear spline multilevel models for summarising childhood growth trajectories: A guide to their application using examples from five birth cohorts

• Type: Article in International Scientific Journal
• Date: 2016

Authors

Howe, LD (Author) Other; Tilling, K (Author) Other; Matijasevich, A (Author) Other; Petherick, ES (Author) Other; Santos AC (Author) FMUP; Fairley, L (Author) Other; Wright, J (Author) Other; Santos, IS (Author) Other; Barros, AJD (Author) Other; Martin, RM (Author) Other; Kramer, MS (Author) Other; Bogdanovich, N (Author) Other; Matush, L (Author) Other; Barros H (Author) FMUP; Lawlor, DA (Author) Other

Journal

Title: Statistical Methods in Medical Research

Vol. 25

Pages: 1854-1874

ISSN: 0962-2802

Publisher: SAGE

Indexing

ISI Web of Knowledge - 99 Citations

Scopus - 105 Citations

Other information

Authenticus ID: P-00M-58F

DOI: 10.1177/0962280213503925

Abstract (EN): Childhood growth is of interest in medical research concerned with determinants and consequences of variation from healthy growth and development. Linear spline multilevel modelling is a useful approach for deriving individual summary measures of growth, which overcomes several data issues (co-linearity of repeat measures, the requirement for all individuals to be measured at the same ages and bias due to missing data). Here, we outline the application of this methodology to model individual trajectories of length/height and weight, drawing on examples from five cohorts from different generations and different geographical regions with varying levels of economic development. We describe the unique features of the data within each cohort that have implications for the application of linear spline multilevel models, for example, differences in the density and inter-individual variation in measurement occasions, and multiple sources of measurement with varying measurement error. After providing example Stata syntax and a suggested workflow for the implementation of linear spline multilevel models, we conclude with a discussion of the advantages and disadvantages of the linear spline approach compared with other growth modelling methods such as fractional polynomials, more complex spline functions and other non-linear models.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 21