Statistical Analysis.
cognitive aging
REGRESSION, SECONDARY
Demographic, clinical, and baseline cognitive data were summarized by the randomized treatment group, and differences were tested with The effect of the randomized dietary flavanol intervention on the change in the primary outcome (ModRey: Immediate Recall from baseline to 1 y) and the secondary outcomes (ModRey: Immediate Recall from baseline to 2 and 3 y; ModBent: Correct Rejection and Flanker: Direction Effect from baseline to 1, 2, and 3 y) was tested with linear mixed-effects models with no additional control for multiple testing. Predictors included baseline measures of the respective outcome, dichotomous treatment (dietary flavanol or placebo), categorical year, treatment × year interaction, and a random intercept to account for repeated measures over time. Missing data for follow-up were accounted for within the mixed-effects model under a missing at random assumption. Cohen’s d effect sizes were calculated for all treatment effects to allow a direct comparison of magnitude using the baseline SD of each variable across both groups.The associations between baseline cognitive measures (ModRey: Immediate Recall; ModBent: Correct Rejection; and Flanker: Direction Effect) and baseline aHEI and gVLM were examined with Pearson correlation coefficients. Linear regression with baseline cognitive measures as the outcome predicted by the aHEI or gVLM (continuous and also categorized into tertiles) further tested the association unadjusted and adjusted for sex, age, education, and race.Additional secondary analyses tested for treatment effect modification on the cognitive measures across time by baseline healthy eating and gVLM. Note that effect modification by gVLM levels was not originally a prespecified analysis because at the time of study registration, this biomarker had not been accredited. However, we included it in our investigations after it became available, as it complemented our existing approaches to investigate a potential link between habitual diet quality, flavanol consumption, and cognitive aging in a more direct, specific, and objective way. Specifically, tertiles of the baseline values of the aHEI or the gVLM were included (separately) in the mixed-effects model along with their interaction with the dichotomous treatment, time, and time by treatment. The test of interaction between the baseline aHEI and treatment or baseline gVLM and treatment was used to determine whether any treatment effects were different by baseline tertile. When significant interactions were found, post hoc tests of the treatment effect within each tertile of the aHEI and gVLM were performed. Moreover, a treatment effect contrast within each tertile of the aHEI and gVLM averaging the specific effects over all three follow-up time points was also obtained. These contrasts and tests were obtained from the same overall mixed-effects model with interactions. Per protocol analyses were also performed restricting to the subset of subjects who met the definition for pill compliance, having ≥75% compliance taken at year 1. This subset of year 1 pill compliers was used for all PP analyses, even those including year 2 and 3 outcomes to ensure consistency of the study sample being analyzed. Of note, year 2 and 3 pill compliance among year 1 pill compliers was very high, 93.5% in year 2 and 90.6% in year 3. Analyses were carried out using SAS 9.4.