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The Internal Validity of a Dietary Pattern Analysis. The Framingham Nutrition Studies

P. A. Quatromoni, D. L. Copenhafer, S. Demissie, R. B. D'Agostino, C. E. O'Horo, B-H. Nam and B. E. Millen
Journal of Epidemiology and Community Health (1979-)
Vol. 56, No. 5 (May, 2002), pp. 381-388
Published by: BMJ
Stable URL: http://www.jstor.org/stable/25569711
Page Count: 8
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The Internal Validity of a Dietary Pattern Analysis. The Framingham Nutrition Studies
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Abstract

Study objectives: To examine the internal validity of a dietary pattern analysis and its ability to discriminate clusters of people with similar dietary patterns using independently assessed nutrient intakes and heart disease risk factors. Design and participants: Population based study characterising dietary patterns using cluster analysis applied to data from the semiquantitative Framingham food frequency questionnaire collected from 1942 women ages 18-76 years, between 1984-88. Setting: Framingham, Massachusetts. Main results: Of 1942 women included in the cluster analysis, 1828 (94%) were assigned to one of the five dietary pattern clusters: Heart Healthy, Light Eating, Wine and Moderate Eating, High Fat, and Empty Calorie. Dietary patterns differed substantially in terms of individual nutrient intakes, overall dietary risk, heart disease risk factors, and predicted heart disease risk. Women in the Heart Healthy cluster had the most nutrient dense eating pattern, the lowest level of dietary risk, more favourable risk factor levels, and the lowest probability of developing heart disease. Those in the Empty Calorie cluster had a less nutritious dietary pattern, the greatest level of dietary risk, a heavier burden of heart disease risk factors, and a relatively higher probability of developing heart disease. Cluster reproducibility using discriminant analysis showed that 80% of the sample was correctly classified. The cluster technique was highly sensitive and specific (75% to 100%). Conclusions: These findings support the internal validity of a dietary pattern analysis for characterising dietary exposures in epidemiological research. The authors encourage other researchers to explore this technique when investigating relations between nutrition, health, and disease.

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