Literature DB >> 23302518

Development of a pediatric body mass index using longitudinal single-index models.

Jingwei Wu1, Wanzhu Tu2.   

Abstract

As a measure of human adiposity, the body mass index, defined as weight/height(2), has been widely used in clinical investigations. For children undergoing pubertal development, whether this function of height and weight represents an optimal way of quantifying body mass for assessing of specific health outcomes has not been carefully studied. In this study, we propose an alternative pediatric body mass measure for prediction of blood pressure based on recorded height and weight data using single-index modeling techniques. Specifically, we present a general form of partially linear single-index mixed effect models for the determination of this new metric. A methodological contribution of this research is the development of an efficient algorithm for the fitting of a general class of partially linear single-index models in longitudinal data situations. The proposed model and related model fitting algorithm are easily implementable in most computational platforms. Simulation demonstrates superior performance of the new method, as compared to the standard body mass index measure. Using the proposed method, we explore an alternative body mass measure for the prediction of blood pressure in children. The method is potentially useful for the construction of other indices for specific investigations.
© The Author(s) 2012.

Entities:  

Keywords:  Adiposity measurement; body mass index; cubic spline; mixed effect model; penalized nonlinear least square; repeated measures

Mesh:

Year:  2013        PMID: 23302518     DOI: 10.1177/0962280212471470

Source DB:  PubMed          Journal:  Stat Methods Med Res        ISSN: 0962-2802            Impact factor:   3.021


  1 in total

1.  Large-sample estimation and inference in multivariate single-index models.

Authors:  Jingwei Wu; Hanxiang Peng; Wanzhu Tu
Journal:  J Multivar Anal       Date:  2019-01-21       Impact factor: 1.473

  1 in total

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