940 resultados para United States Catholic Historical Society
Resumo:
Cutaneous malignant melanoma (CMM) is the cancer of the melanocytes, the cells that produce the pigment melanin, and is an aggressive skin cancer that is most prevalent in the white population. Although most cases of malignant melanoma are white, black and other non-white populations also develop this disease. However, the etiologic factors involved in the development of melanoma in these lower-risk populations are not well known. Generally, survival rates of malignant melanoma have been found to be lower in blacks than for whites with similar stage of disease at diagnosis. ^ This study presents an analysis of the differences in survival between black and white cases with malignant melanoma of the skin as the only or first primary cancer, found in the National Cancer Institute Surveillance, Epidemiology and End Results (SEER) cancer registry from 1973 to 1997. A total of 54,193 cases of CMM were diagnosed in black and white patients between 1973 and 1997. Black patients tended to be older, with a mean age of 64.46 years, compared to 53.14 years for white patients. Eighty-nine percent of patients were diagnosed with CMM as the only cancer. (Abstract shortened by UMI.)^
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Public preferences for policy are formed in a little-understood process that is not adequately described by traditional economic theory of choice. In this paper I suggest that U.S. aggregate support for health reform can be modeled as tradeoffs among a small number of behavioral values and the stage of policy development. The theory underlying the model is based on Samuelson, et al.'s (1986) work and Wilke's (1991) elaboration of it as the Greed/Efficiency/Fairness (GEF) hypothesis of motivation in the management of resource dilemmas, and behavioral economics informed by Kahneman and Thaler's prospect theory. ^ The model developed in this paper employs ordered probit econometric techniques applied to data derived from U.S. polls taken from 1990 to mid-2003 that measured support for health reform proposals. Outcome data are four-tiered Likert counts; independent variables are dummies representing the presence or absence of operationalizations of each behavioral variable, along with an integer representing policy process stage. Marginal effects of each independent variable predict how support levels change on triggering that variable. Model estimation results indicate a vanishingly small likelihood that all coefficients are zero and all variables have signs expected from model theory. ^ Three hypotheses were tested: support will drain from health reform policy as it becomes increasingly well-articulated and approaches enactment; reforms appealing to fairness through universal health coverage will enjoy a higher degree of support than those targeted more narrowly; health reforms calling for government operation of the health finance system will achieve lower support than those that do not. Model results support the first and last hypotheses. Contrary to expectations, universal health care proposals did not provide incremental support beyond those targeted to “deserving” populations—children, elderly, working families. In addition, loss of autonomy (e.g. restrictions on choice of care giver) is found to be the “third rail” of health reform with significantly-reduced support. When applied to a hypothetical health reform in which an employer-mandated Medical Savings Account policy is the centerpiece, the model predicts support that may be insufficient to enactment. These results indicate that the method developed in the paper may prove valuable to health policy designers. ^
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The study compares a measure of income inequality with polarization scores of U.S. Representatives from the 104th to the 109th Congresses. It attempts to explain the link, on the abstract level, between high inequality and high polarization. The end findings indicate that inequality increases a Representative's likelihood to act liberally.
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This paper explores the dynamic linkages that portray different facets of the joint probability distribution of stock market returns in NAFTA (i.e., Canada, Mexico, and the US). Our examination of interactions of the NAFTA stock markets considers three issues. First, we examine the long-run relationship between the three markets, using cointegration techniques. Second, we evaluate the dynamic relationships between the three markets, using impulse-response analysis. Finally, we explore the volatility transmission process between the three markets, using a variety of multivariate GARCH models. Our results also exhibit significant volatility transmission between the second moments of the NAFTA stock markets, albeit not homogenous. The magnitude and trend of the conditional correlations indicate that in the last few years, the Mexican stock market exhibited a tendency toward increased integration with the US market. Finally, we do note that evidence exists that the Peso and Asian financial crises as well as the stock-market crash in the US affect the return and volatility time-series relationships.
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Education in Geographic information science (GIS/LIS) happens in the United States both within surveying-related academic programs and in other academic programs that use spatially oriented data and information. This article presents an overview of two such programs. The first is a four-year Bachelor of Science degree program in Geographic Information Science at Texas A&M University-Corpus Christi. The second is a concentration with a four-year Bachelor of Science degree program in Natural Resources at the University of Connecticut (UConn). Geographic information science is the primary focus of the Texas A&M program, whereas GIS/LIS is an emphasis of the UConn program. Both approaches are presented for comparison.
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by E. D. Morel
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by Edmund D. Morel
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Racial/ethnic disparities in diabetes mellitus (DM) and hypertension (HTN) have been observed and explained by socioeconomic status (education level, income level, etc.), screening, early diagnosis, treatment, prognostic factors, and adherence to treatment regimens. To the author's knowledge, there are no studies addressing disparities in hypertension and diabetes mellitus utilizing Hispanics as the reference racial/ethnic group and adjusting for sociodemographics and prognostic factors. This present study examined racial/ethnic disparities in HTN and DM and assessed whether this disparity is explained by sociodemographics. To assess these associations, the study utilized a cross-sectional design and examined the distribution of the covariates for racial/ethnic group differences, using the Pearson Chi Square statistic. The study focused on Non-Hispanic Blacks since this ethnic group is associated with the worst health outcomes. Logistic regression was used to estimate the prevalence odds ratio (POR) and to adjust for the confounding effects of the covariates. Results indicated that except for insurance coverage, there were statistically significant differences between Non-Hispanic Blacks and Non-Hispanic Whites, as well as Hispanics with respect to study covariates. In the unadjusted logistic regression model, there was a statistically significant increased prevalence of hypertension among Non-Hispanic Blacks compared to Hispanics, POR 1.36, 95% CI 1.02-1.80. Low income was statistically significantly associated with increased prevalence of hypertension, POR 0.38, 95% CI 0.32-0.46. Insurance coverage, though not statistically significant, was associated with an increase in the prevalence of hypertension, p>0.05. Concerning DM, Non-Hispanic Blacks were more likely to be diabetic, POR 1.10, 95% CI 0.85-1.47. High income was statistically significantly associated with decreased prevalence of DM, POR 0.47, 95% CI 0.39-0.57. After adjustment for the relevant covariates, the racial disparities between Hispanics and Non-Hispanic Blacks in HTN was removed, adjusted prevalence odds (APOR) 1.21, 95% CI 0.88-1.67. In this sample, there was racial/ethnic disparity in hypertension but not in diabetes mellitus between Hispanics and Non-Hispanic Blacks, with disparities in hypertension associated with socioeconomic status (family income, education, marital status) and also by alcohol, physical activity and age. However, race, education and BMI as class variables were statistically significantly associated with hypertension and diabetes mellitus p<0.0001. ^