Cesarean section is major surgery, and as in most surgical procedures, there are health risks to both the mother and the baby. Despite the recommendation of the U.S. Department of Health and Human Services (DHHS) in Healthy People 2000, and in Healthy People 2010 to reduce the number of deliveries by cesarean section, the number of cesarean deliveries in the U.S. have increased from 6% of all deliveries in 1970 to nearly 25% in 2001 ranging from 29.9 in Louisiana to 17.2 in Utah (Martin et al. 2002). Cesarean rates were higher among black women than among white, and Hispanic women, and cesarean delivery rates increased with age, doubling from age 20-24 to age 35-39. The proposed research has three specific aims: (1) to analyze biennial data from the National Hospital Discharge Surveys (NHDS) from 1990 to 2002 to examine the individual-level variation in the likelihood of a cesarean delivery, by patient characteristics, hospital ownership, size, location, and payment source; (2) to analyze biennial Natality Data from the National Vital Statistics from 1990 and 2002 to examine the variation in cesarean rates across different levels of aggregation (i.e., county, city, state, and region), and over time by patient mix and community-level characteristics; and (3) to conduct a pre- and post-delivery survey with a sample of women who are in the third trimester (around the 26 the week) of their pregnancy at the first interview, and with their prenatal health care provider (e.g., physician, obstetrician, or midwife) to collect patient-, provider-, and hospital-level information that will allow us to conduct an in-depth examination of the non-clinical (non-obstetric) factors that might lead to a cesarean delivery. We will attach hospital-level and community-level information to each patient's survey data. This phase of the research will be a guided by a health care utilization model (Andersen 1968). The three specific aims comprise complementary analyses that examine different aspects of the same research problem and address different research questions. To attain our analytical objectives we will use descriptive and multivariate analysis techniques, such as, bivariate linear regression, multiple regression, logistic regression, multinomial Iogit regression, and hierarchical linear modeling (or random-effects model) as appropriate. The results from the proposed study will help explain the temporal and geographical variation in cesarean delivery rates, and contribute to our understanding of the multi-level factors associated with elective (i.e., in the absence of clinical indications) cesarean section. [unreadable] [unreadable] [unreadable] [unreadable]