9 resultados para Washington (State) -- Yakima County.

em DigitalCommons@The Texas Medical Center


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This study explores the issue of teenage pregnancy in a case study of Liberty County, a rural area in Texas with no public health department. It also describes the decision-making process and barriers faced in the beginning phases of adopting a sexual education program, and sets forth an implementation plan for two school districts on disseminating an evidence-based, comprehensive curriculum. Methods include a review of epidemiological data surrounding teenage pregnancy on the national, state, and county level; a literature review of factors related to teenage pregnancy and past interventions implemented in a rural community; a policy review of past and current bills in Legislature; and an analysis of barriers and decision making in implementing an evidence based program through qualitative observations, discussions with community members during meetings, presentations, and discussions. Results of this study indicate that there is a lack of research conducted in rural areas in the field of teenage pregnancy prevention and sexual education programs. Barriers experienced in Liberty County are shown to be consistent in scientific literature such as funding, logistical issues, and problems approaching the School Board in adopting a comprehensive sexual education program. This study fills a large gap in the literature on rural adolescents and attempts to analyze the process of decision-making in a rural area related to adoption of sexual education programming. In order to relieve this health disparity, further research should focus on rural areas to gain insight on the attitudes and behaviors of rural adolescents and beliefs among community stakeholders.^

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Natural disasters occur in various forms such as hurricanes, tsunamis, earthquakes, outbreaks, etc. The most unsettling aspect of a natural disaster is that it can strike at any moment. Over the past decade, our society has experienced an alarming increase of natural disasters. How to expeditiously respond and recover from natural disasters has become a precedent question for public health officials. To date, the most recent natural disaster was the January 12, 2010 earthquake in Haiti; however the most memorable was that of Hurricane Katrina (“Haiti Earthquake”, 2010). ^ This study provides insight on the need to develop a National Disaster Response and Recovery Program which effectively responds to natural disasters. The specific aims of this paper were to (1) observe the government’s role on federal, state and local levels in assisting Hurricanes Katrina and Rita evacuees, (2) assess the prevalence of needs among Hurricanes Katrina and Rita families participating in the Disaster Housing Assistance Program (DHAP) and (3) describe the level of progress towards “self sufficiency” for the DHAP families receiving case management social services. ^ Secondary data from a cross-sectional “Needs Assessment” questionnaire were analyzed. The questionnaire was administered initially and again six months later (follow-up) by H.A.U.L. case managers. The “Needs Assessment” questionnaire collected data regarding participants’ education, employment, transportation, child care, health resources, income, permanent housing and disability needs. Case managers determined the appropriate level of social services required for each family based on the data collected from the “Needs Assessment” questionnaire. ^ Secondary data provided by the H.A.U.L. were analyzed to determine the prevalence of needs among the DHAP families. In addition, differences measured between the initial and follow-up (at six months) questionnaires were analyzed to determine statistical significance between case management services provided and prevalence of needs among the DHAP families from initial to 6 months later at follow-up. The data analyzed describe the level of progress made by these families to achieve program “self sufficiency” (see Appendix A). Disaster assistance programs which first address basic human needs; then socioeconomic needs may offer an essential tool in aiding disaster affected communities quickly recover from natural disasters. ^

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This research examines the graduation rate experienced by students receiving public education services in the state of Texas. Special attention is paid to that subgroup of Texas students who meet Texas Education Agency criteria for handicapped status. The study is guided by two research questions: What are the high school completion rates experienced by handicapped and nonhandicapped students attending Texas public schools? and What are the predictors of graduation for handicapped and nonhandicapped students?^ In addition, the following hypotheses are explored. Hypothesis 1: Handicapped students attending a Texas public school will experience a lower rate of high school completion than their nonhandicapped counterparts. Hypothesis 2: Handicapped and nonhandicapped students attending school in a Texas public school with a budget above the median budget for Texas public schools will experience a higher rate of high school completion than similar students in Texas public schools with a budget below the median budget. Hypothesis 3: Handicapped and nonhandicapped students attending school in large Texas urban areas will experience a lower rate of high school completion than similar students in Texas public schools in rural areas. Hypothesis 4: Handicapped and nonhandicapped students attending a Texas public school in a county which rates above the state median for food stamps and AFDC recipients will experience a lower rate of high school completion than students living in counties below the median.^ The study will employ extant data from the records of the Texas Education Agency for the 1988-1989 and the 1989-1990 school years, from the Texas Department of Health for the years of 1989 and 1990, and from the 1980 Census.^ The study reveals that nonhandicapped students are graduating with a two year average rate of.906, while handicapped students following an Individualized Educational Program (IEP) achieve a two year average rate of.532, and handicapped students following the regular academic program present a two year average graduation rate of only.371. The presence of other handicapped students, and the school district's average expense per student are found to contribute significantly to the completion rates of handicapped students. Size groupings are used to elucidate the various impacts of these variables on different school districts and different student groups.^ Conclusions and implications are offered regarding the need to reach national consensus on the definition and computation of high school completion for both handicapped and nonhandicapped students, and the need for improved statewide tracking of handicapped completion rates. ^

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While numerous studies have found similar mortality rates for Hispanics compared to non-Hispanic whites, surprisingly little is known about years of potential life lost (YPLL) differentials in mortality. The primary purpose of this paper is to quantify the effect that YPLL has on Hispanics in order to determine if YPLL differs between Hispanics and non-Hispanic whites. Using YPLL may bring attention to dissimilarities that are often obscured through traditional measures. Bexar County 2000-2004 data from the Texas Department of State Health Services, Vital Statistics Unit was analyzed for the descriptive analysis and 2003 Bexar County Multiple Cause Death data was analyzed for the regression analysis. The multiple regression models were used to examine Hispanic and non-Hispanic white differences in years of potential life lost (YPLL) before age 75 from all-causes of death. For this analysis, YPLL was regressed on ethnicity, education level and marital status for men and women. The descriptive analysis found YPLL from all-causes was greater among non-Hispanic whites than Hispanics. However, the regression analysis found Hispanics lost more year of potential from all-causes of death compared to non-Hispanic whites. This indicates that the effect of ethnicity on YPLL differs for different methods of analysis. Future research efforts should keep in mind the method of analysis when using YPLL. Understanding differences in mortality among Hispanics and non-Hispanic whites is important for targeting future health policies and research to aid in eliminating Hispanic health disparities. ^

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This study assesses adolescent's health issues in Comal County, TX. Adolescents are defined as youth between the ages of 12 to 17 years of age, who resided in Comal County during the time period of 2000 to 2007. The analysis focused on high risk behaviors including use of gateway drugs—tobacco and alcohol; illegal substance use; and reproductive health related indicators, including sexual activity, sexually transmitted diseases, and pregnancy. This study is based on the primary and secondary data collected as part of the 2008 Comal County Community Assessment. It compares findings from the primary data sources to extant data from four secondary data sources including: (1) The Centers for Disease Control & Prevention (national) Healthy People 2010; (2) The Centers for Disease Control & Prevention, Youth Risk Behavior Surveillance Survey, 2007; (3) The Texas Department of State Health Services, 2000 to 2007; and The Pride Survey (Local and Statewide). The methods are drawn from the literature on "rapid epidemiologic appraisal" (Annett H. & Rifkin S. B., 1988). The study focus on corroborating the perceptions, subjective concerns, opinions and beliefs of the Comal County key stakeholders and community participants with qualitative and quantitative indicators of health and well being. The value of this approach is to inform community leaders using a public health perspective and evidence in their decisions about priority setting and resources allocation activities for prevention of high risk behaviors and promotion of adolescent health and well being. ^

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Background. Over half of children in the United States under age five spend 32 hours a week in child care, facilities, where they consume approximately 33-50% of their food intake. ^ Objectives. The aim of this research was to identify the effects of state nutrition policies on provision of food in child care centers. ^ Subjects. Eleven directors or their designee from ten randomly selected licensed child care centers in Travis County, Texas were interviewed. Centers included both nonprofit and for-profit centers, with enrollments ranging from 19 to 82. ^ Methods. Centers were selected using a web-based list of licensed child care providers in the Austin area. One-on-one interviews were conducted in person with center directors using a standard set of questions developed from previous pilot work. Interview items included demographic data, questions about state policies regarding provision of foods in centers, effects of policies on child care center budgets and foods offered, and changes in the provision of food. All interviews were audiotaped and transcribed, and themes were identified using standard qualitative techniques. ^ Results. Four of the centers provided both meals and snacks, four provided snacks only, and two did not provide any food. Directors of centers that provided food were more likely to report adherence to the Minimum Standards than directors of centers that did not. In general, center directors reported that the regulations were loosely enforced. In contrast, center directors were more concerned about a local city-county regulation that required food permits and new standards for kitchens. Most of these local regulations were cost prohibitive and, as a result, centers had changed the types of foods provided, which included providing less fresh produce and more prepackaged items. Although implementation of local regulations had reduced provision of fruits and vegetables to children, no adjustments were reported for allocation of resources, tuition costs or care of the children. ^ Conclusions. Qualitative data from a small sample of child care directors indicate that the implementation and accountability of food- and nutrition-related guidelines for centers is sporadic, uncoordinated, and can have unforeseen effects on the provision of food. A quantitative survey and dietary assessment methods should be conducted to verify these findings in a larger and more representative sample.^

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The need for timely population data for health planning and Indicators of need has Increased the demand for population estimates. The data required to produce estimates is difficult to obtain and the process is time consuming. Estimation methods that require less effort and fewer data are needed. The structure preserving estimator (SPREE) is a promising technique not previously used to estimate county population characteristics. This study first uses traditional regression estimation techniques to produce estimates of county population totals. Then the structure preserving estimator, using the results produced in the first phase as constraints, is evaluated.^ Regression methods are among the most frequently used demographic methods for estimating populations. These methods use symptomatic indicators to predict population change. This research evaluates three regression methods to determine which will produce the best estimates based on the 1970 to 1980 indicators of population change. Strategies for stratifying data to improve the ability of the methods to predict change were tested. Difference-correlation using PMSA strata produced the equation which fit the data the best. Regression diagnostics were used to evaluate the residuals.^ The second phase of this study is to evaluate use of the structure preserving estimator in making estimates of population characteristics. The SPREE estimation approach uses existing data (the association structure) to establish the relationship between the variable of interest and the associated variable(s) at the county level. Marginals at the state level (the allocation structure) supply the current relationship between the variables. The full allocation structure model uses current estimates of county population totals to limit the magnitude of county estimates. The limited full allocation structure model has no constraints on county size. The 1970 county census age - gender population provides the association structure, the allocation structure is the 1980 state age - gender distribution.^ The full allocation model produces good estimates of the 1980 county age - gender populations. An unanticipated finding of this research is that the limited full allocation model produces estimates of county population totals that are superior to those produced by the regression methods. The full allocation model is used to produce estimates of 1986 county population characteristics. ^

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In 1941 the Texas Legislature appropriated $500,000 to the Board of Regents of the University of Texas to establish a cancer research hospital. The M. D. Anderson Foundation offered to match the appropriation with a grant of an equal sum and to provide a permanent site in Houston. In August, 1942 the Board of Regent of the University and the Trustees of the Foundation signed an agreement to embark on this project. This institution was to be the first one in the medical center, which was incorporated in October, 1945. The Board of Trustees of the Texas Medical Center commissioned a hospital survey to: - Define the needed hospital facilities in the area - Outline an integrated program to meet these needs - Define the facilities to be constructed - Prepare general recommendations for efficient progress The Hospital Study included information about population, hospitals, and other health care and education facilities in Houston and Harris County at that time. It included projected health care needs for future populations, education needs, and facility needs. It also included detailed information on needs for chronic illnesses, a school of public health, and nursing education. This study provides valuable information about the general population and the state of medicine in Houston and Harris County in the 1940s. It gives a unique perspective on the anticipated future as civic leaders looked forward in building the city and region. This document is critical to an understanding of the Texas Medical Center, Houston and medicine as they are today. SECTIONS INCLUDE: Abstract The Abstract was a summary of the 400 page document including general information about the survey area, community medical assets, and current and projected medical needs which the Texas Medical Center should meet. The 123 recommendations were both general (e.g., 12. “That in future planning, the present auxiliary department of the larger hospitals be considered inadequate to carry an added teaching research program of any sizable scope.”) and specific (e.g., 22. That 14.3% of the total acute bed requirement be allotted for obstetric care, reflecting a bed requirement of 522 by 1950, increasing to 1,173 by 1970.”) Section I: Survey Area This section basically addressed the first objective of the survey: “define the needed hospital facilities in the area.” Based on the admission statistics of hospitals, Harris County was included in the survey, with the recognition that growth from out-lying regional areas could occur. Population characteristics and vital statistics were included, with future trends discussed. Each of the hospitals in the area and government and private health organizations, such as the City-County Welfare Board, were documented. Statistics on the facilities use and capacity were given. Eighteen recommendations and observations on the survey area were given. Section II: Community Program This section basically addressed the second objective of the survey: “outline an integrated program to meet these needs.” The information from the Survey Area section formed the basis of the plans for development of the Texas Medical Center. In this section, specific needs, such as what medical specialties were needed, the location and general organization of a medical center, and the academic aspects were outlined. Seventy-four recommendations for these plans were provided. Section III: The Texas Medical Center The third and fourth objectives are addressed. The specific facilities were listed and recommendations were made. Section IV: Special Studies: Chronic Illness The five leading causes of death (heart disease, cancer, “apoplexy”, nephritis, and tuberculosis) were identified and statistics for morbidity and mortality provided. Diagnostic, prevention and care needs were discussed. Recommendations on facilities and other solutions were made. Section IV: Special Studies: School of Public Health An overview of the state of schools of public health in the US was provided. Information on the direction and need of this special school was also provided. Recommendations on development and organization of the proposed school were made. Section IV: Special Studies: Needs and Education Facilities for Nurses Nursing education was connected with hospitals, but the changes to academic nursing programs were discussed. The needs for well-trained nurses in an expanded medical environment were anticipated to result in significant increased demands of these professionals. An overview of the current situation in the survey area and recommendations were provided. Appendix A Maps, tables and charts provide background and statistical information for the previous sections. Appendix B Detailed census data for specific areas of the survey area in the report were included. Sketches of each of the fifteen hospitals and five other health institutions showed historical information, accreditations, staff, available facilities (beds, x-ray, etc.), academic capabilities and financial information.

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A population based ecological study was conducted to identify areas with a high number of TB and HIV new diagnoses in Harris County, Texas from 2009 through 2010 by applying Geographic Information Systems to determine whether distinguished spatial patterns exist at the census tract level through the use of exploratory mapping. As of 2010, Texas has the fourth highest occurrence of new diagnoses of HIV/AIDS and TB.[31] The Texas Department of State Health Services (DSHS) has identified HIV infected persons as a high risk population for TB in Harris County.[29] In order to explore this relationship further, GIS was utilized to identify spatial trends. ^ The specific aims were to map TB and HIV new diagnoses rates and spatially identify hotspots and high value clusters at the census tract level. The potential association between HIV and TB was analyzed using spatial autocorrelation and linear regression analysis. The spatial statistics used were ArcGIS 9.3 Hotspot Analysis and Cluster and Outlier Analysis. Spatial autocorrelation was determined through Global Moran's I and linear regression analysis. ^ Hotspots and clusters of TB and HIV are located within the same spatial areas of Harris County. The areas with high value clusters and hotspots for each infection are located within the central downtown area of the city of Houston. There is an additional hotspot area of TB located directly north of I-10 and a hotspot area of HIV northeast of Interstate 610. ^ The Moran's I Index of 0.17 (Z score = 3.6 standard deviations, p-value = 0.01) suggests that TB is statistically clustered with a less than 1% chance that this pattern is due to random chance. However, there were a high number of features with no neighbors which may invalidate the statistical properties of the test. Linear regression analysis indicated that HIV new diagnoses rates (β=−0.006, SE=0.147, p=0.970) and census tracts (β=0.000, SE=0.000, p=0.866) were not significant predictors of TB new diagnoses rates. ^ Mapping products indicate that census tracts with overlapping hotspots and high value clusters of TB and HIV should be a targeted focus for prevention efforts, most particularly within central Harris County. While the statistical association was not confirmed, evidence suggests that there is a relationship between HIV and TB within this two year period.^