Reported food intake and distribution of body fat: a repeated cross-sectional study

• Main Authors: Krachler, Benno, Eliasson, Mats, Stenlund, Hans, Johansson, Ingegerd, Hallmans, Göran, Lindahl, Bernt
• Format: Other/Unknown Material
• Language: English
• Published: BioMed Central Ltd. 2006
• Subjects: Northern Sweden
• Online Access: http://www.nutritionj.com/content/5/1/34

Abstract Background Body mass, as well as distribution of body fat, are predictors of both diabetes and cardiovascular disease. In Northern Sweden, despite a marked increase in average body mass, prevalence of diabetes was stagnant and myocardial infarctions decreased. A more favourable distribution of body fat is a possible contributing factor. This study investigates the relative importance of individual food items for time trends in waist circumference (WC) and hip circumference (HC) on a population level. Methods Independent cross-sectional surveys conducted in 1986, 1990, 1994 and 1999 in the two northernmost counties of Sweden with a common population of 250000. Randomly selected age stratified samples, altogether 2982 men and 3087 women aged 25–64 years. Questionnaires were completed and anthropometric measurements taken. For each food item, associations between frequency of consumption and waist and hip circumferences were estimated. Partial regression coefficients for every level of reported intake were multiplied with differences in proportion of the population reporting the corresponding levels of intake in 1986 and 1999. The sum of these product terms for every food item was the respective estimated impact on mean circumference. Results Time trends in reported food consumption associated with the more favourable gynoid distribution of adipose tissue were increased use of vegetable oil, pasta and 1.5% fat milk. Trends associated with abdominal obesity were increased consumption of beer in men and higher intake of hamburgers and French fried potatoes in women. Conclusion Food trends as markers of time trends in body fat distribution have been identified. The method is a complement to conventional approaches to establish associations between food intake and disease risk on a population level.