Crozier, SR;
Johnson, W;
Cole, TJ;
Macdonald-Wallis, C;
Muniz-Terrera, G;
Inskip, HM;
Tilling, K;
(2019)
A discussion of statistical methods to characterize early growth and its impact on bone mineral content later in childhood.
Annals of Human Biology
, 46
(1)
pp. 17-26.
10.1080/03014460.2019.1574896.
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Abstract
Background: Many statistical methods are available to model longitudinal growth data and relate derived summary measures to later outcomes. / Aim: To apply and compare commonly used methods to a realistic scenario including pre- and postnatal data, missing data, and confounders. / Subjects and methods: Data were collected from 753 offspring in the Southampton Women’s Survey with measurements of bone mineral content (BMC) at age 6 years. Ultrasound measures included crown-rump length (11 weeks’ gestation) and femur length (19 and 34 weeks’ gestation); postnatally, infant length (birth, 6 and 12 months) and height (2 and 3 years) were measured. A residual growth model, two-stage multilevel linear spline model, joint multilevel linear spline model, SITAR and a growth mixture model were used to relate growth to 6-year BMC. / Results: Results from the residual growth, two-stage and joint multilevel linear spline models were most comparable: an increase in length at all ages was positively associated with BMC, the strongest association being with later growth. Both SITAR and the growth mixture model demonstrated that length was positively associated with BMC. / Conclusions: Similarities and differences in results from a variety of analytic strategies need to be understood in the context of each statistical methodology.
| Type: | Article |
|---|---|
| Title: | A discussion of statistical methods to characterize early growth and its impact on bone mineral content later in childhood |
| Location: | England |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1080/03014460.2019.1574896 |
| Publisher version: | https://doi.org/10.1080/03014460.2019.1574896 |
| Language: | English |
| Additional information: | Copyright © 2019 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
| Keywords: | Growth mixture models, lifecourse epidemiology, linear spline models, multilevel models, SITAR |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL GOS Institute of Child Health UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL GOS Institute of Child Health > Population, Policy and Practice Dept |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10068529 |
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