A Prospective Analysis of Plasma Phospholipid Fatty Acids and Breast Cancer Risk in 2 Provinces in Canada.

BACKGROUND

Studies suggest that fatty acid status influences breast cancer etiology, yet the roles of individual fatty acids in breast cancer risk are unclear, specifically when central adiposity and menopausal status are considered.

OBJECTIVES

This study examined the associations of fatty acid status with breast cancer risk including location, menopausal status, and waist-to-hip ratio as key variables.

METHODS

Prediagnostic plasma phospholipid fatty acids were measured in women with breast cancer (= 393) and age-matched controls (= 786) from a nested case-control prospective study within Alberta's Tomorrow Project (ATP) and British Columbia Generations Project (BCGP) cohorts. Binary logistic regression models were used to evaluate associations of fatty acids and breast cancer risk with subgroup analysis for menopausal status and waist-to-hip ratio.

RESULTS

Women from BCGP had a higher n-3 (ɷ-3) fatty acid status compared with the ATP (6.4% ± 0.08% vs. 5.3% ± 0.06%; < 0.001), so subsequent analysis was blocked by cohort. Overall, fatty acids had inconsistent associations with risk. In the ATP among premenopausal women, total long-chain n-3 fatty acids (OR= 1.78; 95% CI: 0.58, 5.43; trend = 0.007, interaction = 0.07) were positively associated with breast cancer risk, whereas in BCGP, DHA (OR= 0.66; 95% CI: 0.28, 1.53; trend = 0.03, interaction = 0.05) and total long-chain n-3 fatty acids (OR= 0.66; 95% CI: 0.28, 1.54; trend = 0.03) were associated with decreased cancer risk when the waist-to-hip ratio was <0.85.

CONCLUSIONS

Our findings suggest that regional variations in fatty acid status influence breast cancer risk, resulting in positive associations of total long-chain n-3 fatty acids in premenopausal ATP women and negative associations of these fatty acids in BCGP women with a waist-to-hip ratio below guidelines. This study highlights the complexity and difficulty in using fatty acid status to predict breast cancer risk in diverse populations without the consideration of other risk factors.