Table 2.
Model* | n | β † | SE | p Value |
---|---|---|---|---|
CAC as ln(AS + 1) | ||||
Model 1 | 2,695 | –0.18 | 0.06 | 0.001 |
Model 2 | –0.13 | 0.05 | 0.011 | |
Model 3 | –0.25 | 0.07 | <0.001 | |
AAC as ln(AS + 1) | ||||
Model 1 | 2,681 | –0.19 | 0.06 | 0.001 |
Model 2 | –0.09 | 0.06 | 0.09 | |
Model 3 | –0.13 | 0.08 | 0.07 |
Tobit regression analyses were adjusted as follows: model 1 adjusted for calcium and energy intake, age, sex, and exam cycle. Model 2 adjusted as for model 1, plus BMI, smoking status, SBP, fasting insulin, total-to-high-density lipoprotein cholesterol ratio, use of hormone replacement therapy (women only), menopausal status (women only), treatment for hyperlipidemia, hypertension or cardiovascular disease prevention, or diabetes, and alcohol intake. Model 3 adjusted as for model 2, plus intake of vitamins K and D, saturated fat, and fiber.
β Coefficients of Tobit regression can be interpreted as most linear regression coefficients on the natural log scale, that is, as percent changes per 50-mg/day increments in magnesium intake, obtained by exponentiating the coefficient and subtracting 1. For example, in model 3 of the CAC regression, the –0.25 β coefficient can be thought of as [e–0.25 – 1] = –22%, or 22% lower CAC per 50-mg/day increment in intake.
Abbreviations as in Table 1.