No abstract

The findings of this study indicate that Web-based, computer-tailored nutrition information can have a short-term effect on the determinants of fat, fruit, and vegetable intake. The effect of the tailored information may be partly explained by the perceived personal relevance and individualization of the information.

No abstract

No abstract

The association between diet and cancer, predominantly investigated univariately, has often been inconsistent, possibly because of the large number of candidate risk factors and their high intercorrelations. Analysis of dietary patterns is expected to give more insight than analysis of single nutrients or foods. This study aimed to develop and apply a common methodological approach to determine dietary patterns in four cohort studies originating in Finland, the Netherlands, Sweden and Italy. Food items on each of the food frequency questionnaires were aggregated into 51 food groups, defined on the basis of their position in the diet pattern and possible relevance to cancer etiology. Exploratory factor analysis was used to analyze dietary patterns. Using a standardized approach, 3-5 stable dietary patterns were identified, explaining 20-29% of total variance in consumption of the food groups. Two dietary patterns, which explained most of the variance, were consistent across the studies. The first pattern was characterized by high consumption of (salad) vegetables, the second by high consumption of pork, processed meat and potatoes. In addition, a few specifically national food patterns were identified. Sensitivity analyses showed that the identified patterns were robust for number of factors extracted, distribution of input variables and energy adjustment. Our findings suggest that some important eating patterns are shared by the four populations under study, whereas other eating patterns are population specific.