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J Am Diet Assoc. 2002 Sep;102(9):1239-46.

Dietary patterns predict the development of overweight in women: The Framingham Nutrition Studies.

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1
Framingham Nutrition Studies, Department of Social and Behavioral Sciences, Boston University School of Public Health, 715 Albany Street, Boston, MA 02118, USA.

Abstract

OBJECTIVE:

To investigate relationships between dietary patterns and the development of overweight.

DESIGN:

Longitudinal analyses during 12 years of follow-up involved the identification of dietary patterns at baseline using cluster analysis applied to a 145-item semiquantitative food frequency questionnaire.

SUBJECTS/SETTING:

737 non-overweight women in the Framingham Offspring/Spouse cohort (mean age, 45 years).

MAIN OUTCOME MEASURE:

Development of overweight (BMI> or =25) at follow-up.

STATISTICAL ANALYSES:

Relative risks were calculated using Proc Genmod and multivariate models comprehensively considered potential confounders.

RESULTS:

Five dietary patterns were identified among the cohort at baseline: Heart Healthy, Light Eating, Wine and Moderate Eating, High Fat, and Empty Calorie. Over 12 years, the crude risk of becoming overweight was 29% overall, ranging from 22% of women in the Wine and Moderate Eating cluster to 41% of women in the Empty Calorie cluster. Compared with women who ate a lower-fat, nutritionally varied Heart Healthy diet, women who ate an Empty Calorie diet that was rich in sweets and fats with fewer servings of nutrient-dense fruits, vegetables, and lean food choices were at higher risk for developing overweight [RR 1.4, 95% CI (0.9, 2.2)] after adjusting for age, smoking status, physical activity, menopausal status, energy intake, intentional dieting, and usual weight pattern. Women who ate an Empty Calorie dietary pattern were also younger and were more likely to smoke.

CONCLUSIONS:

Behavioral interventions for weight management and obesity prevention may be enhanced by creatively targeting differences in eating patterns, dietary quality, and other lifestyle behaviors of distinct subgroups of the population.

PMID:
12792620
[Indexed for MEDLINE]

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