Multivariate models were adjusted for potential confounders, including age, race/ethnicity (non-Hispanic white, non-Hispanic black, or other), educational level (less than high school, high school graduate, some college, or college graduate/postgraduate), marital status (married or not married), self-reported health status (excellent, very good, good, fair, or poor), body mass index (BMI) (calculated as weight in kilograms divided by height in meters squared) (<18.5, 18.5-<25, 25-<30, 30-<35, or ≥35), physical activity (never/rarely, ≤3 times per month, or 1, 2, 3, 4, or ≥5 times per week), smoking status (0, 1-10, 11-20, 21-30, 31-40, 41-50, 51-60, or >60 cigarettes per day), smoking dose (0, 1-10, 11-20, 21-30, 31-40, 41-50, 51-60, or >60 cigarettes per day), years since quitting smoking (never quit, ≥10, 5-9, 1-4, or <1 year), and intakes of alcohol, fruit and vegetable, red meat, whole grain, fat, and total energy (continuous). Menopausal hormone therapy use (never, past, or current) was adjusted in women. Supplemental and dietary calcium intakes were mutually adjusted. For each covariate, missing values (generally <5%) were put in the reference group. Assigning missing values into separate groups did not change the results materially. We also examined the potentially nonlinear relationship between total calcium intake and risk of total CVD mortality using nonparametric regression analyses.21,22 A likelihood ratio test was used to compare the model with both the linear and the cubic spline terms with the model with the linear term only.