V Mikkilä1, H Vepsäläinen1, T Saloheimo1, S A Gonzalez2, J D Meisel3, G Hu4, C M Champagne4, J-P Chaput5, T S Church4, P T Katzmarzyk4, R Kuriyan6, A Kurpad6, E V Lambert7, C Maher8, J Maia9, V Matsudo10, T Olds8, V Onywera11, O L Sarmiento2, M Standage12, M S Tremblay5, C Tudor-Locke13, P Zhao14, M Fogelholm1. 1. Department of Food and Environmental Sciences, University of Helsinki , Helsinki, Finland. 2. Department of Public Health, School of Medicine, Department of Public Health, Universidad de los Andes , Bogota, Colombia. 3. Department of Industrial Engineering, Faculty of Engineering, CeiBA Complex Systems Research Center, Universidad de los Andes , Bogotá, Colombia. 4. Pennington Biomedical Research Center , Baton Rouge, LA, USA. 5. Children's Hospital of Eastern Ontario Research Institute , Ottawa, Ontario, Canada. 6. St Johns Research Institute , Bangalore, India. 7. Department of Human Biology, Faculty of Health Sciences, Division of Exercise Science and Sports Medicine, University of Cape Town , Cape Town, South Africa. 8. Alliance for Research in Exercise Nutrition and Activity (ARENA), School of Health Sciences, University of South Australia , Adelaide, South Australia, Australia. 9. CIFI2D, Faculdade de Desporto, University of Porto , Porto, Portugal. 10. Centro de Estudos do Laboratório de Aptidão Física de São Caetano do Sul , Sao Paulo, Brazil. 11. Department of Recreation Management and Exercise Science, Kenyatta University , Nairobi, Kenya. 12. Department of Health, University of Bath , Bath, UK. 13. Pennington Biomedical Research Center, Baton Rouge, LA, USA; Department of Kinesiology, University of Massachusetts Amherst, Amerherst, MA, USA. 14. Tianjin Women's and Children's Health Center , Tianjin, China.
Abstract
OBJECTIVES: Dietary pattern is defined as a combination of foods and drinks and the frequency of consumption within a population. Dietary patterns are changing on a global level, which may be linked to an increased incidence of chronic diseases. The aim of this study was to identify and compare the dietary patterns among 9-11-year-old children living in urban regions in different parts of the world. METHODS: Participants were 7199 children (54% girls), aged 9-11 years, from 12 countries situated in all major world regions. Food consumption was assessed using a 23-item Food Frequency Questionnaire (FFQ). To identify dietary patterns, principal components analyses (PCA) were carried out using weekly portions as input variables. RESULTS: Both site-specific and pooled PCA resulted in two strong components. Component 1 ('unhealthy diet pattern') included fast foods, ice cream, fried food, French fries, potato chips, cakes and sugar-sweetened sodas with >0.6 loadings. The loadings for component 2 ('healthy diet pattern') were slightly weaker with only dark-green vegetables, orange vegetables, vegetables in general, and fruits and berries reaching a >0.6 loading. The site-specific diet pattern scores had very strong correlations with the pattern scores from the pooled data: r=0.82 and 0.94 for components 1 and 2, respectively. CONCULSIONS: The results suggest that the same 'healthier' and 'unhealthier' foods tend to be consumed in similar combinations among 9-11-year-old children in different countries, despite variation in food culture, geographical location, ethnic background and economic development.
OBJECTIVES: Dietary pattern is defined as a combination of foods and drinks and the frequency of consumption within a population. Dietary patterns are changing on a global level, which may be linked to an increased incidence of chronic diseases. The aim of this study was to identify and compare the dietary patterns among 9-11-year-old children living in urban regions in different parts of the world. METHODS: Participants were 7199 children (54% girls), aged 9-11 years, from 12 countries situated in all major world regions. Food consumption was assessed using a 23-item Food Frequency Questionnaire (FFQ). To identify dietary patterns, principal components analyses (PCA) were carried out using weekly portions as input variables. RESULTS: Both site-specific and pooled PCA resulted in two strong components. Component 1 ('unhealthy diet pattern') included fast foods, ice cream, fried food, French fries, potato chips, cakes and sugar-sweetened sodas with >0.6 loadings. The loadings for component 2 ('healthy diet pattern') were slightly weaker with only dark-green vegetables, orange vegetables, vegetables in general, and fruits and berries reaching a >0.6 loading. The site-specific diet pattern scores had very strong correlations with the pattern scores from the pooled data: r=0.82 and 0.94 for components 1 and 2, respectively. CONCULSIONS: The results suggest that the same 'healthier' and 'unhealthier' foods tend to be consumed in similar combinations among 9-11-year-old children in different countries, despite variation in food culture, geographical location, ethnic background and economic development.
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