2.3. Statistical Analysis
sleepiness, excessive sleepiness
REGRESSION, LATE PREGNANCY, EXCESSIVE SLEEPINESS
Descriptive statistics were calculated for sociodemographic characteristics and feeding-related variables. We examined bivariate associations between each sociodemographic characteristic and sleepiness scores using analysis of variance (ANOVA). Likewise, we examined bivariate associations between each sociodemographic characteristic and the breastfeeding variables. Variables that were associated with either sleepiness or breastfeeding at a modest significance level (To examine cross-sectional and longitudinal associations between excessive sleepiness (as a predictor) during early and late pregnancy and at 6 months postpartum, with breastfeeding intentions, initiation, and behavior at 3 and 6 months (all dichotomous outcomes), we constructed a series of logistic regression models. To examine cross-sectional associations between excessive sleepiness during early and late pregnancy (predictor) with breastfeeding attitudes during pregnancy (continuous outcomes), we constructed a series of linear regression models. Likewise, we used linear regression models to examine cross-sectional associations between excessive sleepiness at 6 months postpartum (predictor) with infant feeding practices and beliefs beyond breastfeeding (continuous outcomes). Data were analyzed using the statistical software package STATA and statistical significance was set at the 0.05 level.