Michael Hermanussen1, Karol Stec2, Christian Aßmann3, Christof Meigen4, Stef Van Buuren5. 1. Aschauhof, 24340, Altenhof, Germany. 2. Bioinformatics Group, Institute of Biochemistry and Biology, University of Potsdam, 14476, Potsdam-Golm, Germany. 3. Otto-Friedrich-Universität Bamberg, Chair of Statistics and Econometrics, Feldkirchenstr. 21, 96045, Bamberg, Germany. 4. Deutsches Zentrum für Neurodegenerative Erkrankungen, Holbeinstr. 13-15, 53175, Bonn, Germany. 5. Department of Statistics, TNO Prevention and Health, 2301 CE Leiden, The Netherlands.
Abstract
OBJECTIVES: To reanalyze the between-population variance in height, weight, and body mass index (BMI), and to provide a globally applicable technique for generating synthetic growth reference charts. METHODS: Using a baseline set of 196 female and 197 male growth studies published since 1831, common factors of height, weight, and BMI are extracted via Principal Components separately for height, weight, and BMI. Combining information from single growth studies and the common factors using in principle a Bayesian rationale allows for provision of completed reference charts. RESULTS: The suggested approach can be used for generating synthetic growth reference charts with LMS values for height, weight, and BMI, from birth to maturity, from any limited set of height and weight measurements of a given population. CONCLUSION: Generating synthetic growth reference charts by incorporating information from a large set of reference growth studies seems suitable for populations with no autochthonous references at hand yet.
OBJECTIVES: To reanalyze the between-population variance in height, weight, and body mass index (BMI), and to provide a globally applicable technique for generating synthetic growth reference charts. METHODS: Using a baseline set of 196 female and 197 male growth studies published since 1831, common factors of height, weight, and BMI are extracted via Principal Components separately for height, weight, and BMI. Combining information from single growth studies and the common factors using in principle a Bayesian rationale allows for provision of completed reference charts. RESULTS: The suggested approach can be used for generating synthetic growth reference charts with LMS values for height, weight, and BMI, from birth to maturity, from any limited set of height and weight measurements of a given population. CONCLUSION: Generating synthetic growth reference charts by incorporating information from a large set of reference growth studies seems suitable for populations with no autochthonous references at hand yet.
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