Frequencies and descriptive statistics were calculated. Means across the three groups were compared using ANOVA with post-hoc pairwise comparisons. In addition, multivariate linear regression analysis was used to create a model to identify the factors most strongly contributing to the overall LOT-R scores. Variables that were significantly associated with the LOT-R in univariate analysis were entered into the multivariate model. The model was reworked using only those variables that maintained significance until the best-fit model was identified. Interactions between key variables were examined as well. A pvalue of .05 was taken to be statistically significant. Table 1 illustrates the demographic characteristics of women in the sample. Note that two of the three variables upon which women were matched (age and number of previous pregnancies) were not significantly different (see Table 2 ). In fact, the average difference in age across the matched sets was 0.857 years, with a maximum difference of 3 years. The average difference in number of previous pregnancies was .482, with the highest difference being 2.0, reflected in only 4 of the 56 sets. Women from China were enrolled significantly later in their pregnancies than women in the U.S. (p = .04, mean difference of 1.52 weeks), yet the average difference in gestational age across the matched sets was 2.66 weeks.