@article{4581cc9c16d9495f8df86b7daf2d2da3,
title = "Using data from multiple studies to develop a child growth correlation matrix",
abstract = "In many countries, the monitoring of child growth does not occur in a regular manner, and instead, we may have to rely on sporadic observations that are subject to substantial measurement error. In these countries, it can be difficult to identify patterns of poor growth, and faltering children may miss out on essential health interventions. The contribution of this paper is to provide a framework for pooling together multiple datasets, thus allowing us to overcome the issue of sparse data and provide improved estimates of growth. We use data from multiple longitudinal growth studies to construct a common correlation matrix that can be used in estimation and prediction of child growth. We propose a novel 2-stage approach: In stage 1, we construct a raw matrix via a set of univariate meta-analyses, and in stage 2, we smooth this raw matrix to obtain a more realistic correlation matrix. The methodology is illustrated using data from 16 child growth studies from the Bill and Melinda Gates Foundation's Healthy Birth Growth and Development knowledge integration project and identifies strong correlation for both height and weight between the ages of 4 and 12 years. We use a case study to provide an example of how this matrix can be used to help compute growth measures.",
keywords = "SDS, child health, correlation, growth",
author = "Craig Anderson and Luo Xiao and William Checkley",
note = "Funding Information: The HBGDki initiative was supported by the Bill and Melinda Gates Foundation. The article contents are the sole responsibility of the authors and may not necessarily represent the official views of the Bill & Melinda Gates Foundation or other agencies that may have supported the primary data studies included in the HBGDki knowledge base. The authors thank all study subjects, data contributors, and primary funding agencies for all data used in this study. Funding Information: (grip, Iqbal et al14); PROVIDE Study PR-10060, funded by NIH grant R01 AI043596 (prvd,Nayloretal15); Infant Growth in Peru (phua, Lopez de Roma{\~n}a et al16); Respiratory Pathogens Birth Cohort (rspk, Iqbal et al14); Peru Zn Fortification (pzn, Brown et al17); Longitudinal study of bovine serum concentrate (BSC) in Guatemala (gbsc, Begin et al18); Medical Research Council (MRC) Keneba (knba, Hennig et al19); Study of Biomarkers for Environmental Enteropathy (ee, Iqbal et al14); Deuterium dilution study in Mali (mmam, Ackatia-Armah et al20); Child Malnutrition and Infection Network (cmin, MAL-ED Investigators21); Zn Trial in Burkina Faso (bfzn, Hess et al22); CMC Vellore Birth Cohort 2002 (cmc, Rehman et al23); NIH Birth Cohort Study, funded by NIH grant R01 AI043596 (nbrt, Mondal et al24); Longitudinal Growth Study in Bangladesh (bngd, Brown et al25); NIH Preschool Cohort Study, funded by NIH grant R01 AI043596 (npre, Haque et al26). Publisher Copyright: {\textcopyright} 2018 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd",
year = "2019",
month = aug,
day = "30",
doi = "10.1002/sim.7696",
language = "English (US)",
volume = "38",
pages = "3540--3554",
journal = "Statistics in Medicine",
issn = "0277-6715",
publisher = "John Wiley and Sons Ltd",
number = "19",
}