Using multiple correspondence analysis to identify behaviour patterns associated with overweight and obesity in
Andrew van Horn1, Charles A Weitz1, Kathryn M Olszowy2
11Department of Anthropology,Temple University,214 Gladfelter Hall,1801 N. Broad Street,Philadelphia,PA 19122,USA.
Public Health Nutrition
|March 9, 2019
Summary
Multiple Correspondence Analysis (MCA) identified modernization behaviors linked to overweight/obesity in Vanuatu. Higher modernization scores correlated with increased body fat and obesity risk.
Area of Science:
- Public Health
- Anthropology
- Biostatistics
Background:
- Vanuatu faces rapid modernization, a factor linked to rising overweight/obesity rates.
- Understanding behavioral correlates of obesity is crucial for public health interventions in developing nations.
Purpose of the Study:
- To evaluate Multiple Correspondence Analysis (MCA) for identifying behaviors associated with overweight/obesity in Vanuatu.
- To assess the relationship between modernization status and body fat measures using MCA.
Main Methods:
- MCA was applied to 73 behavioral questions from 810 Ni-Vanuatu adults (aged 20-85).
- Twelve key behaviors were identified and used to create a modernization scale, dividing participants into tertiles.
- Body fat measures and overweight/obesity odds ratios (OR) were compared across modernization tertiles.
Main Results:
- Individuals in the highest modernization tertile showed significantly greater weight, body fat, and likelihood of being in the top 25% for body fat compared to lower tertiles.
- MCA successfully reduced complex behavioral data into a meaningful modernization scale.
Conclusions:
- MCA is a viable tool for identifying individuals or groups at risk for overweight/obesity using simple behavioral questions.
- MCA offers a practical approach for obesity risk assessment in resource-limited settings where detailed modernization data is challenging to collect.
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