Using small area estimation and geographic information systems technology to target health services for the uninsured

The three articles that comprise this dissertation describe how small area estimation and geographic information systems (GIS) technologies can be integrated to provide useful information about the number of uninsured and where they are located. Comprehensive data about the numbers and characteristics of the uninsured are typically only available from surveys. Utilization and administrative data are poor proxies from which to develop this information. Those who cannot access services are unlikely to be fully captured, either by health care provider utilization data or by state and local administrative data. In the absence of direct measures, a well-developed estimation of the local uninsured count or rate can prove valuable when assessing the unmet health service needs of this population. However, the fact that these are “estimates” increases the chances that results will be rejected or, at best, treated with suspicion. The visual impact and spatial analysis capabilities afforded by geographic information systems (GIS) technology can strengthen the likelihood of acceptance of area estimates by those most likely to benefit from the information, including health planners and policy makers. ^ The first article describes how uninsured estimates are currently being performed in the Houston metropolitan region. It details the synthetic model used to calculate numbers and percentages of uninsured, and how the resulting estimates are integrated into a GIS. The second article compares the estimation method of the first article with one currently used by the Texas State Data Center to estimate numbers of uninsured for all Texas counties. Estimates are developed for census tracts in Harris County, using both models with the same data sets. The results are statistically compared. The third article describes a new, revised synthetic method that is being tested to provide uninsured estimates at sub-county levels for eight counties in the Houston metropolitan area. It is being designed to replicate the same categorical results provided by a current U.S. Census Bureau estimation method. The estimates calculated by this revised model are compared to the most recent U.S. Census Bureau estimates, using the same areas and population categories. ^

Psychosocial influences on fruit, vegetable and milk consumption among a cohort of Houston-area 5th graders

Epidemiological evidence suggests that fruit and vegetable intake is negatively associated with the development of several chronic diseases, including heart disease, some cancers and diabetes mellitus. Inadequate consumption of milk during developmental years is associated with osteoporosis. Consumption of fruit, vegetable and milk (FVM) declines from childhood to adolescence. Adolescent eating habits persist into adulthood; thus, understanding psychosocial factors such as self-efficacy, norms and preferences, is important for developing effective interventions. Preferences, one of the most consistent correlates of fruit and vegetable consumption in children and adolescents, may mediate the relationships between self-efficacy and norms and fruit and vegetable consumption. ^ Fifth grade students from one middle school in South Texas were followed for two years. Students completed lunch food records and questionnaires assessing fruit, vegetable and milk self-efficacy and norms and fruit and vegetable preferences. Principal component analyses identified four scales: Fruit Self-Efficacy, Vegetable Self-Efficacy, Fruit and Vegetable Norms, and Milk Influences. Reliability and validity of the four scales and emerging subscales were assessed using Cronbach's alpha and consumption data, respectively. Associations between longitudinal FVM consumption and self-efficacy and norms were tested. Additionally, the influence of preferences on the relationship of self-efficacy, norms and fruit and vegetable consumption was examined. ^ Confirmatory factor analyses confirmed four scales and subscales. Internal consistency and test-retest reliabilities were acceptable. Self-efficacy and norms were related to FVM consumption and changes in fruit and high fat vegetable consumption over the two-year period. While intake over the two-year period differed statistically, eating patterns were stable. Preferences mediated the relation between fruit self-efficacy and FV norms and fruit consumption. ^ In conclusion, self-efficacy and norms about consuming FVM at school appear to influence FVM consumption. Because eating patterns were similar over the two-year period, establishing healthy eating habits in elementary school is important. While FVM self-efficacy and norms influenced FVM consumption in children, only fruit preferences mediated the relationship of fruit consumption, self-efficacy and norms. Since the influences of FVM consumption appear to differ, interventions designed to increase consumption should target these differences and consider the specificity of self-efficacy and norms. ^