Using Multiple Correspondence Analysis to Identify Behaviour Patterns Associated with Overweight and Obesity in Vanuatu Adults

Overview

Journal Public Health Nutr

Publisher Cambridge University Press

Date 2019 Mar 9

PMID 30846019

Citations 6

Authors

Andrew Van Horn

Charles A Weitz

Kathryn M Olszowy

Kelsey N Dancause

Cheng Sun

Alysa Pomer

Harold Silverman

Gwang Lee

Leonard Tarivonda

Chim W Chan

Akira Kaneko

J Koji Lum

Ralph M Garruto

Affiliations

Soon will be listed here.

Abstract

Objective: The present study evaluates the use of multiple correspondence analysis (MCA), a type of exploratory factor analysis designed to reduce the dimensionality of large categorical data sets, in identifying behaviours associated with measures of overweight/obesity in Vanuatu, a rapidly modernizing Pacific Island country.

Design: Starting with seventy-three true/false questions regarding a variety of behaviours, MCA identified twelve most significantly associated with modernization status and transformed the aggregate binary responses of participants to these twelve questions into a linear scale. Using this scale, individuals were separated into three modernization groups (tertiles) among which measures of body fat were compared and OR for overweight/obesity were computed.

Setting: Vanuatu.ParticipantsNi-Vanuatu adults (n 810) aged 20-85 years.

Results: Among individuals in the tertile characterized by positive responses to most of or all the twelve modernization questions, weight and measures of body fat and the likelihood that measures of body fat were above the US 75th percentile were significantly greater compared with individuals in the tertiles characterized by mostly or partly negative responses.

Conclusions: The study indicates that MCA can be used to identify individuals or groups at risk for overweight/obesity, based on answers to simply-put questions. MCA therefore may be useful in areas where obtaining detailed information about modernization status is constrained by time, money or manpower.

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