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Cancer Control Research

5R03CA113024-02
Chang, Ellen T.
DIET AND RISK OF OVARIAN CANCER

Abstract

DESCRIPTION (provided by applicant): We propose to address several emerging or unresolved hypotheses related to the impact of diet on ovarian cancer risk. Our specific aims are to evaluate the relationship between ovarian cancer risk and (a) phytoestrogens and isothiocyanates, (b) eggs, dietary fats and dairy products, (c) alcohol, and (d) dietary patterns. The California Teachers Study is a prospective study of 133,479 female California teachers who participate in the State Teachers Retirement System and who were active or retired California teachers or administrators at the time the cohort was established in 1995. Our analyses will include the 123,293 women who were California residents at baseline; about 290 of whom will have developed ovarian cancer by December 2002. Dietary intake during the year prior to entering the cohort was assessed via a self-administered food-frequency questionnaire (FFQ), specifically a near final version of the Block95 FFQ. The FFQ included an assessment of 100 food and beverage items as well as questions regarding alcohol use, overall intake of fruits and vegetables, and use of low-fat or non-fat versions of foods. Cancer outcomes in the cohort are identified through annual linkage with the California Cancer Registry (CCR). We will use Poisson regression to estimate the relative risk (i.e. rate ratios and 95% confidence intervals) of ovarian cancer associated with specific foods, food groups, micronutrients, non-nutritive compounds, and dietary patterns of interest. A priori definitions and factor analysis will be used to classify women based on their "types of diet" (i.e. dietary patterns). Due to the size of the CTS, we will have greater than 80% power to detect the anticipated associations. As dietary information was collected prior to disease onset, the study will not be affected by recall bias, unlike case-control studies upon which the majority of the previous work in this area has been based. The results of the proposed analyses will provide further understanding of the etiology of ovarian cancer.


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