Linear mixed-effects regression (LMER) models with an identification variable included as the random effect were used. The LMER models included a random intercept and fixed effects of visit factor, sex, age, BMI, diabetes, high cholesterol, anxiety, self-reported stress level, self-reported depression, marital status, education level, and family history of heart disease and hypertension. Two models were fit to systolic BP (SBP) and 2 models were fit to diastolic BP (DBP) data. Model 1 included the visit factor and basic demographic variables (sex, age, BMI, and education in years). Model 2 additionally included diabetes, high cholesterol, anxiety, self-reported stress level, self-reported depression, marital status, and family history of heart disease and hypertension. Owing to the explanatory nature of the study, P values were not adjusted. The significance level for all tests were set at .05 (2-tailed). Data were presented as mean (SD) for continuous variables and frequency (% total) for categorical variables. The statistical computing program R (R Foundation for Statistical Computing) was used for all analyses.