Note as well that the samples differ significantly on a few key variables. First is in terms of educational attainment. In Ghana and China, approximately a third or respondents were high school graduates or less, compared to only seven percent in the U.S. Our data suggest that educational attainment is associated with optimism/pessimism and health-related quality of life. What is less clear is through what mechanism. Further research is needed to disentangle these associations. The second key difference in the samples is related to their reports of current and previous treatment for emotional issues. While nearly 40% of U.S. women in our sample reported ever seeking care for emotional issues, only 5% of Chinese women in our sample said the same. While this may reflect true differences in need for mental health care, more likely it reflects social norms and access issues surrounding treatment for mental health issues. Nonetheless, such differences are indicative of the likely many other variables that would differ across cultures that were not measured in this study and that might have an effect on optimism/pessimism or selfassessed health-related quality of life. Finally, the samples were likely to be very different in terms of standard of living. Women in Ghana were recruited from a public hospital, suggesting lower income participants, whereas women in China and the U.S. were either 'public' or 'private,' depending upon the type of insurance being used. We attempted to assess income to sort out these differences in a meaningful way, but there were numerous challenges. The first is the distinction between family and individual income. In China, family income may or may not include extended family. There may be four -or even six -adults in one household, awaiting the arrival of a single child. In Africa, family income was challenging for some respondents to answer, whether due to lack of knowledge or the challenge of translating non-currency income into survey response options. In addition, assuming for a moment that our survey instrument accurately collected and recorded a representative gradient of incomes in each culture, how does one compare being 'low income' in the U.S. versus being 'low income' in sub-Saharan Africa? The combination of missing data and uncertain interpretation of our income-related items made meaningful comparisons challenging at best, misleading at worst, thus income data were removed from analysis.