Dietary patterns in Irish adolescents: a comparison of cluster and principal component analyses

• Published in: Public health nutrition Vol. 16; no. 5; pp. 848 - 857
• Main Authors: Hearty, Áine P, Gibney, Michael J
• Format: Journal Article
• Language: English
• Published: Cambridge, UK Cambridge University Press 01.05.2013
• Subjects: Adolescent; adolescent nutrition; Adolescents; Assessment and methodology; Beverages; Biological and medical sciences; breakfast cereals; Choice Behavior; Cluster Analysis; data collection; Diet - statistics & numerical data; Diet Records; eating habits; energy; Energy Intake; Feeding Behavior; Female; Food; Food groups; food intake; Food Preferences; food records; Food, Organic; Health promotion; healthy diet; Humans; Ireland; Male; Manual workers; Medical sciences; Nutrition Surveys; pasta; Principal Component Analysis; Principal components analysis; Public health. Hygiene-occupational medicine; Social classes; Software; Statistical methods; surveys; Surveys and Questionnaires; Teenagers; Traditional foods; variance; Europe; Ireland; Cluster analysis; Dietary patterns; Adolescents; Principal component analysis; Human; Automatic classification; Diet; Adolescent; Comparative study; Irish
• ISSN: 1368-9800; 1475-2727; 1475-2727
• DOI: 10.1017/S1368980011002473

Pattern analysis of adolescent diets may provide an important basis for nutritional health promotion. The aims of the present study were to examine and compare dietary patterns in adolescents using cluster analysis and principal component analysis (PCA) and to examine the impact of the format of the dietary variables on the solutions. Analysis was based on the Irish National Teens Food Survey, in which food intake data were collected using a semi-quantitative 7 d food diary. Thirty-two food groups were created and were expressed as either g/d or percentage contribution to total energy. Dietary patterns were identified using cluster analysis (k-means) and PCA. Republic of Ireland, 2005-2006. A representative sample of 441 adolescents aged 13-17 years. Five clusters based on percentage contribution to total energy were identified, 'Healthy', 'Unhealthy', 'Rice/Pasta dishes', 'Sandwich' and 'Breakfast cereal & Main meal-type foods'. Four principal components based on g/d were identified which explained 28 % of total variance: 'Healthy foods', 'Traditional foods', 'Sandwich foods' and 'Unhealthy foods'. A 'Sandwich' and an 'Unhealthy' pattern are the main dietary patterns in this sample. Patterns derived from either cluster analysis or PCA were comparable, although it appears that cluster analysis also identifies dietary patterns not identified through PCA, such as a 'Breakfast cereal & Main meal-type foods' pattern. Consideration of the format of the dietary variable is important as it can directly impact on the patterns obtained for both cluster analysis and PCA.