Using multiple correspondence analysis to identify behaviour patterns associated with overweight and obesity in Vanuatu adults
Bibliographic Data
| ID | 15095055 |
|---|---|
| Authors | Andrew Van Horn (0000-0002-5203-8049, Temple University), Charles A Weitz (0000-0001-5222-6966, Temple University, corresponding author), Kathryn M Olszowy (0000-0003-0843-4519, Cleveland State University), Kelsey Needham Dancause (0000-0002-8677-9953, Université du Québec à Montréal), Cheng Sun (0000-0002-2744-0896, Binghamton University), Alysa Pomer (0000-0003-1267-1189, Yale University), Harold Silverman (Feinstein Institute for Medical Research), Gwang Lee (0000-0002-1299-9478, Binghamton University), Leonard Tarivonda (Vanuatu Cultural Centre), Chim W Chan (0000-0002-4039-2649, Karolinska Institutet), Akira Kaneko (0000-0003-2411-3352, Osaka City University), J Koji Lum (Binghamton University), Ralph M Garruto (0000-0003-4985-8190, Binghamton University) |
| Year | 2019 |
| Volume | 22 |
| Issue | 09 |
| Pages | 1533-1544 |
| Publication date | 2019-06-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Public Health Nutrition (JOURNAL) |
| Journal identifiers | ISSN: 1368-9800 • E-ISSN: 1475-2727 |
| Publisher | Cambridge University Press (CUP) (PUBLISHER) |
| DOI | 10.1017/s1368980019000302 |
| PMID | 30846019 |
| OpenAlex | W2922270433 |
| Language | EN |
| Citations received | 7 |
| References cited | 28 |
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. Participants Ni-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
Cartography · Categorical variable · Geography · Modernization theory · Multiple correspondence analysis · Obesity · Overweight · Percentile · Political science · Scale (ratio · Sociology · Statistics · Cognitive and psychological constructs research · Demography · Mathematics · Medicine · Sensory Analysis and Statistical Methods · Gerontology · Internal Medicine
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| Unique citing works | 7 |
|---|---|
| Citations per year | 1,75 |
| Citation span | 2022 - 2026 (5) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 7 |