We used Cox proportional hazard models to examine the associations between major dietary patterns and diabetes risk. To reduce random within-person variation and best represent long-term dietary intake, we calculated cumulative averages of dietary pattern scores from our repeated dietary measurements.4 For example, dietary intake in 1984 was used to predict diabetes occurrence from 1984 to 1986, and the average of 1984 and 1986 intake was used to predict risk from 1986 to 1990, and so on. The regression analyses were adjusted for age (<49 y, 50-54 y, 55-59 y, 60-64 y, and ≥65 y), family history of diabetes (yes vs no), history of hypercholesterolemia (yes vs no), smoking (never, past, current with 1-14 cigarettes per day, current with 15-24 cigarettes per day, current with ≥25 cigarettes per day, and missing), hormone therapy use (premenopausal, never, past, and current hormone use), caloric intake, history of hypertension (yes vs no), physical activity (<1 h/wk, 1-1.9 h/wk, 2-3.9 h/wk, 4-6.9 h/wk, and ≥7 h/wk), alcohol intake (abstainer, 0.1-5.0 g/d, 5.1-15.0 g/d, 15.1-30.0 g/d, and >30g/d), body mass index (BMI; continuous and quadratic terms), and missing FFQ. The proportions with a missing FFQ in 1986, 1990, and 1994 were 17%, 16%, and 14%, respectively. In separate analyses, we only included symptomatic cases. In addition, we examined the association between different forms of red meat and diabetes risk, since these are the major contributors to the Western dietary pattern. We also conducted analyses jointly classifying women by processed meats and family history of diabetes, obesity status (BMI [calculated as weight in kilograms divided by the square of height in meters] ≥30), physical activity, alcohol intake, and smoking status. To minimize confounding by adiposity, we additionally adjusted for waist-hip ratio among women with the available data.