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Chunk #11 — Methods — Statistical analyses

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C-reactive protein (CRP) gene polymorphisms, CRP levels, and risk of incident coronary heart disease in two nested case-control studies.
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All analyses were conducted separately for men and women. For baseline characteristics, we used ANOVA methods to compare least square means adjusted for matching factors, and the Chi-square and/or Fisher's Exact tests to compare proportions between cases and controls, between genotype and allele frequencies, and to assess Hardy-Weinberg equilibrium. The primary genetic model was additive (genotype as a continuous variable). Conditional and unconditional logistic regression adjusting for matching factors and multivariate covariates were used to estimate the relative risk (RR) and results were similar. With risk-set sampling, the odds ratio derived from the logistic regression directly estimates the hazard ratio, and thus, the relative risk.[27] In our multivariable model we further adjusted for alcohol intake (nondrinker, 0.1 to 4.9 g/d, 5.0 to 14.9 g/d, 15.0 to 29.9 g/d, ≥30.0 g/d), body mass index (<25, 25 to 29.9, ≥30 kg/m2), physical activity (quintiles), nonsteroidal anti-inflammatory drug (NSAID) use (yes/no), parental history of CHD before the age of 60 (yes/no), history of diabetes (yes/no) and hypertension (yes/no) at baseline, total:HDL-cholesterol ratio (quintiles), and hormone therapy among women (never, past, current). Baseline was