Abstract

Given the increasing prevalence of adult obesity, furthering the understanding of the determinants of measures such as Body Mass Index (BMI) remains high on the policy agenda. We contribute to existing literature on modelling BMI by proposing an extension to latent class modelling, which serves to unveil a more detailed picture of the determinants of BMI. Interest here lies in latent class analysis with: a regression model and predictor variables explaining class membership; a regression model and predictor variables explaining the outcome variable within BMI classes; and instances where the BMI classes are naturally ordered and labelled by expected values within class. A simple and generic way of parameterising both the class probabilities and the statistical representation of behaviours within each class is proposed, that simultaneously preserves the ranking according to class-specific expected values and yields a parsimonious representation of the class probabilities. Based on a wide range of metrics, the newly proposed approach is found to dominate the prevailing one; and moreover, results are often quite different across the two.

Download paper (PDF, 369.5 KB)

Presenter

Professor Mark Harris, Curtin University

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Venue

Level 6, Colin Clark building (#39)
The University of Queensland
St Lucia campus
Room: 
629