Dissertation Titles and Synopses

Solar Disinfection of Drinking Water: Effectiveness, in Periurban Households in Siddhipur Village, Kathmandu Valley, Nepal by Rochelle C. Rainey, PhD, Oregon State University, 2003, 189 pages The effectiveness of solar disinfection (SODIS) in reducing levels of fecal contamination from household containers was tested in this study by examining pH, turbidity, and fecal contamination of drinking water from household water storage containers, wells and taps, and the Godawari River. The study also investigated the relationship between use of SODIS and reported episodes of diarrheal illness in the participating households. Forty households from Siddhipur Village in the Kathmandu Valley participated in the study from March to July 2002. The study included a baseline survey of health and water quality, training in how and why to use solar disinfection, and 2 follow-ups. The results showed: 1) Water from all sources is contaminated with fecal coliform bacteria. 2) There is less contamination in water from the household containers than from wells and taps. 3) SODIS did significantly reduce the level of fecal contamination. 4) SODIS was not adopted by most households in this study. 5) The level of education and awareness about water and sanitation was low. It is recommended that the entire water distribution system for a village be examined to identify specific points of potential contamination in order to protect (from human and animal waste) the riparian zone upstream from the intake for the village reservoir. Education about water and sanitation, as well as information and training on other simple methods for household disinfection, should be provided to schoolchildren and primary food preparers. Additional research is needed to determine the effectiveness of SODIS in the shorter, colder winter days and at higher altitudes before final recommendations can be made for general use in Nepal. Geographic Information Systems and Environmental Exposure Modeling by Allison Lee Robinson, PhD, University of Pittsburgh, 2003, 118 pages This study speaks to the need for improved measures of environmental exposures that can be applied to human health risk assessment. Sophisticated methods are needed that can estimate exposures over specified geographical areas in order to evaluate human health risk from environmental pollutants. Present studies attempting to evaluate the impact of air pollution on public health typically use summarized and uncertain surrogates for spatially distributed pollution. This research study presented sophisticated means of estimating environmental exposures. Geographic information systems provide efficient methods for determining exposure indices, allowing for geographically relevant estimations. Toxic Release Inventory emission sites and fine Particulate Matter emission sites are used as the source of pollution emissions. Six counties of western Pennsylvania provided the geographic area of study. Using Health Tracking Data to Assess the Potential, Link Between Environment and Disease by Max Rony Francois, PhD, University of South Florida, 2003, 117 pages The purpose of this study was to develop a methodology aimed at identifying the health-based environmental indicators that will be used in the environmental assessment of a community. Various databases were reviewed to access the 1996–1999 estimates of emissions of toxic chemicals for the State of Florida (by county). Information on these environmental indicators was obtained from various US Environmental Protection Agency sources: the National Emissions Trend, the Aerometric Information Retrieval System databases, and the Toxics Release Inventory. The environmental indicators selected included carbon monoxide, nitrogen oxides, particulate matter less than 10 microns, particulate matter less than 5 microns, sulfur dioxide, volatile organic compounds, ammonia, and total industrial releases. For 1996–1999, 4 respiratory discharge diagnoses were assessed for each county through the Florida Agency for Health Care Administration. The model did not predict the mortality outcomes particularly well, except for deaths from all causes, for which the R2 ranged from 0.15 to 0.33. However, the model worked well in accurately and consistently predicting the respiratory-related admissions for 1996–1999. For these 4 years, the full model explained 53%–59% of the variance in the admissions classified by ICD-9 codes 506 and 519. For pneumonia, the model's accuracy was similarly high. Indeed, the proportion of the variance explained by this model ranges from 56% to 58%. For chronic obstructive pulmonary disease (COPD), the model was 52%–56% predictive. For asthma, the accuracy of the full model ranged from 16% to 24%. This model appears to be a valid tool for the prediction of respiratory-related admissions in Florida. Social Class Differences and Malaria in Ghana by Kwame Annor Boadu, PhD, University of Alberta, 2002, 276 pages Disease patterns in Ghana in this study are suggested to be conditioned by an entire complex of demographic, economic, social, cultural, political, and environmental factors. This study examines the relationship between social class differences and the prevalence of malaria in Ghana. Data utilized were obtained from the 1997 Core Welfare Indicators Questionnaire (CWIQ) Survey, a study conducted by the Ghana Statistical Service in collaboration with the World Bank. A total of 14 514 household heads were successfully interviewed, of which 9,162 were rural household heads and 5,352 were urban household heads. The research method involves the construction of a composite index of social class from 6 indicators: education, dwelling ownership, number of cattle, modern household items, main source of cooking fuel, and type of toilet facility. Some of these factors not only affect exposure to the risk of malaria, but they also are indicators of social class or socioeconomic status. Social class represents the main predictor variable in the investigation, and it is examined together with marital status and personal hygiene. The prevalence rate of malaria is the dependent variable while sex, age, and ecological zone are employed as controls. The focus on malaria stems from the pervasive influence of the disease as the leading cause of morbidity and mortality in Ghana and its linkage to socioeconomic and environmental conditions. After bivariate analysis was performed to establish the correlation among the selected indicators, principal component analysis was employed to determine the proportion of variance. The generated factor loadings in the component matrix are used as weights representing the proportional contribution of each indicator to the index. Three groups (lower, middle, and upper class) were identified in the sample population. Multivariate logistic regression was then executed to examine the influence of social class on malaria, while controlling for all other variables. The results indicate that social class has no direct influence on the prevalence of malaria in Ghana. Rather, its effect is mediated by marital status. This outcome suggests that regardless of class position, marital status represents a powerful influence in the transmission of malaria in Ghana. These dissertations are most easily accessed via the ProQuest Digital Dissertations Web site, wwwlib.umi.com/dissertations. Most recent dissertations are available in PDF format for download (in their entirety) free of charge for those readers affiliated with a subscribing university. If an unaffiliated individual wishes to order a dissertation, the full abstract can be viewed at the ProQuest Web site, and the entire document can be purchased bound or unbound for a reasonable fee from ProQuest. Many thanks are extended to Jonathan Erlen, PhD, medical historian at the University of Pittsburgh School of Medicine, for providing a monthly stream of newly minted dissertations from which to choose for this section.

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