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Analysis of patterns of food intake in nutritional epidemiology: food classification in principal components analysis and the subsequent impact on estimates for endometrial cancer

Published online by Cambridge University Press:  02 January 2007

Susan E McCann ,
James R Marshall ,
John R Brasure ,
Saxon Graham  and
Jo L Freudenheim
Susan E McCann*
Affiliation:
Department of Social and Preventive Medicine, 270 Farber Hall, University at Buffalo, Buffalo, NY 14214, USA
James R Marshall
Affiliation:
Arizona Cancer Center, 1515 N. Campbell Avenue, PO Box 245024, Tucson, AZ 85724-5024, USA
John R Brasure
Affiliation:
Department of Social and Preventive Medicine, 270 Farber Hall, University at Buffalo, Buffalo, NY 14214, USA
Saxon Graham
Affiliation:
Department of Social and Preventive Medicine, 270 Farber Hall, University at Buffalo, Buffalo, NY 14214, USA
Jo L Freudenheim
Affiliation:
Department of Social and Preventive Medicine, 270 Farber Hall, University at Buffalo, Buffalo, NY 14214, USA
*
*Corresponding author: Email mccann@acsu.buffalo.edu
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Abstract

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Objective:

To assess the effect of different methods of classifying food use on principal components analysis (PCA)-derived dietary patterns, and the subsequent impact on estimation of cancer risk associated with the different patterns.

Methods:

Dietary data were obtained from 232 endometrial cancer cases and 639 controls (Western New York Diet Study) using a 190-item semi-quantitative food-frequency questionnaire. Dietary patterns were generated using PCA and three methods of classifying food use: 168 single foods and beverages; 56 detailed food groups, foods and beverages; and 36 less-detailed groups and single food items.

Results:

Classification method affected neither the number nor character of the patterns identified. However, total variance explained in food use increased as the detail included in the PCA decreased (~8%, 168 items to ~17%, 36 items). Conversely, reduced detail in PCA tended to attenuate the odds ratio (OR) associated with the healthy patterns (OR 0.55, 95% confidence interval (CI) 0.35–0.84 and OR 0.77, 95% CI 0.49–1.20, 168 and 36 items, respectively) but not the high-fat patterns (OR 0.95, 95% CI 0.57–1.58 and OR 0.85, 0.51–1.40, 168 and 36 items, respectively).

Conclusions:

Greater detail in food-use information may be desirable in determination of dietary patterns for more precise estimates of disease risk.

Keywords

Dietary patternsEndometrial cancerStatistical methods
Type
Research Article
Information
Public Health Nutrition , Volume 4 , Issue 5 , October 2001 , pp. 989 - 997
Copyright
Copyright © CABI Publishing 2001

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