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Related Experiment Video

Updated: May 16, 2026

'Boden Food Plate': Novel Interactive Web-based Method for the Assessment of Dietary Intake
04:46

'Boden Food Plate': Novel Interactive Web-based Method for the Assessment of Dietary Intake

Published on: September 18, 2018

BCH-GEE Approach to Examine the Association Between Time-Varying Food Environment Classes and Multi-Level Health

Kelsey A L Alexovitz1, Brisa N Sánchez1, Emma V Sanchez-Vaznaugh2

  • 1Department of Epidemiology and Biostatistics, Dornsife School of Public Health, Drexel University, Philadelphia, Pennsylvania, USA.

Statistics in Medicine
|May 15, 2026
PubMed
Summary

We developed a new statistical method to accurately link population groups over time to health outcomes. This approach corrects for errors, showing unhealthy food environments near schools increase student body mass index.

Keywords:
distal outcomesgeneralized estimating equationslatent transition analysis

Related Experiment Videos

Last Updated: May 16, 2026

'Boden Food Plate': Novel Interactive Web-based Method for the Assessment of Dietary Intake
04:46

'Boden Food Plate': Novel Interactive Web-based Method for the Assessment of Dietary Intake

Published on: September 18, 2018

Area of Science:

  • * Biostatistics
  • * Public Health
  • * Developmental Psychology

Background:

  • * Understanding population heterogeneity and its changes over time is crucial.
  • * Linking these dynamic groups (latent classes) to external factors like health outcomes is a key research interest.
  • * Existing methods for analyzing these associations are often biased or computationally challenging with complex data.

Purpose of the Study:

  • * To propose a novel statistical approach, the biased-adjusted 3-step BCH-GEE, for analyzing associations between time-varying latent classes and multilevel distal outcomes.
  • * To address computational limitations of existing methods in complex data structures.
  • * To examine the relationship between school neighborhood unhealthy food environments and student body mass index (BMI).

Main Methods:

  • * Latent transition analysis to model time-varying latent classes.
  • * Ascertainment of classification errors.
  • * Weighted Generalized Estimating Equations (GEE) to estimate associations with multilevel distal outcomes in a multilevel repeated cross-sectional design.
  • * Simulation studies to validate the method's bias correction.

Main Results:

  • * The proposed BCH-GEE method effectively corrects bias introduced by classification errors in latent class assignment.
  • * Simulation studies confirmed the method's accuracy in estimating effect sizes.
  • * Analysis revealed a significant association between higher density of unhealthy food outlets in school neighborhoods and increased student BMI in California over an 8-year period.

Conclusions:

  • * The biased-adjusted 3-step BCH-GEE approach provides a robust and computationally feasible method for analyzing associations between dynamic latent classes and complex outcomes.
  • * Findings highlight the negative impact of unhealthy food environments near schools on student weight status.
  • * This method can be applied to various research areas involving time-varying population heterogeneity and distal outcomes.