Dietary patterns in adult population from Argentina

ELORRIAGA N, DEFAGÓ MD, GUTIÉRREZ L, DESIMONE H, POGGIO R, IRAZOLA V

Granada

Congreso; 20 Congreso de la IUNS (International Union of Nutritional Sciences); 2013

International Union of Nutritional Sciences

Background and objectives: Dietary patterns (DP) have been used to identify different combinations of foods that may be associated with mortality and risk of chronic disease. The objective of this study was to identify DP in the adult population of Argentina, and explore associations with socio-demographic features. Methods: We defined DP among 3,000 adults between 35 to 74 years old, participating in CESCAS I, a population-based cohort study carried out in two cities in Argentina, Marcos Paz and Bariloche. Data on food intake was obtained from a validated self-administered food frequency questionnaire. Principal component Analysis (PCA) was used to identify DP. A summary score for each pattern was then derived and used in multiple regression analysis to examine the relationship between DP and socio-demographic variables. Results: Using PCA, we identified 3 major eating patterns. The first factor (Traditional dietary pattern), was characterized by a high intake of refined grains, red meat, whole fat dairy products, vegetable oils, and ?mate?, a traditional South American infused drink frequently consumed in Argentina; the second factor (Healthy dietary pattern), was characterized by a high intake of vegetables, fruit, low fat dairy products, whole grains, and legumes; the third factor (Processed-food dietary pattern) consisted mainly of processed meat, snacks, pizza, and ?empanadas?, a stuffed bread baked or fried. After adjusting for energy intake, we found that DP were associated with age, gender, and educational level. Healthy DP score was higher among women and high educational level (p=0.001) while men and young people scored significantly higher in the Processed-food DP (p=0.01). Conclusions: Local DP has been identified in our population. This study will provide useful information to set priority targets for nutrition interventions.