Quantile contours and allometric modelling for risk classification of abnormal ratios with an application to asymmetric growth-restriction in preterm infants

TL;DR

This paper introduces a novel method combining quantile contours and allometric modelling to classify risk based on anthropometric ratios, applied to preterm infants' growth data to identify those at higher mortality risk.

Contribution

It proposes a new approach using directional quantiles and allometric directions for risk classification in multivariate anthropometric data, with a practical application to preterm infant growth.

Findings

Disproportionately growth-restricted infants with higher HC-to-BW ratios have increased mortality risk.

The method effectively identifies risk groups based on anthropometric ratios.

Maternal hypertension's role in growth restriction is also analyzed.

Abstract

We develop an approach to risk classification based on quantile contours and allometric modelling of multivariate anthropometric measurements. We propose the definition of allometric direction tangent to the directional quantile envelope, which divides ratios of measurements into half-spaces. This in turn provides an operational definition of directional quantile that can be used as cutoff for risk assessment. We show the application of the proposed approach using a large dataset from the Vermont Oxford Network containing observations of birthweight (BW) and head circumference (HC) for more than 150,000 preterm infants. Our analysis suggests that disproportionately growth-restricted infants with a larger HC-to-BW ratio are at increased mortality risk as compared to proportionately growth-restricted infants. The role of maternal hypertension is also investigated.