2 resultados para 100 Songs Project

em DigitalCommons@The Texas Medical Center


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Accurate ascertainment of risk factors and disease status is vital in public health research for proper classification of research subjects. The two most common ways of obtaining this data is by self-report and review of medical records (MRs). South Texas Women’s Health Project was a case-control study looking at interrelationships between hormones, diet, and body size and breast cancer among Hispanic women 30-79 years of age. History of breast cancer, diabetes mellitus (DM) and use of DM medications was ascertained from a personal interview. At the time of interview, the subject identified her major health care providers and signed the medical records release form, which was sent to the designated providers. The MRs were reviewed to confirm information obtained from the interview.^ Aim of this study was to determine the sensitivity and specificity between MRs and personal interview in diagnosis of breast cancer, DM and DM treatment. We also wanted to assess how successful our low-cost approach was in obtaining pertinent MRs and what factors influenced the quality of MR or interview data. Study sample was 721 women with both self-report and MR data available by June 2007. Overall response rate for MR requests was 74.5%. MRs were 80.9% sensitive and 100% specific in confirming breast cancer status. Prevalence of DM was 22.7% from the interviews and 16% from MRs. MRs did not provide definite information about DM status of 53.6% subjects. Sensitivity and specificity of MRs for DM status was 88.9% and 90.4% respectively. Disagreement on DM status from the two sources was seen in 15.9% subjects. This discordance was more common among older subjects, those who were married and were predominantly Spanish speaking. Income and level of education did not have a statistically significantly association with this disagreement.^ Both self-report and MRs underestimate the prevalence of DM. Relying solely on MRs leads to greater misclassification than relying on self-report data. MRs have good to excellent specificity and thus serve as a good tool to confirm information obtained from self-report. Self-report and MRs should be used in a complementary manner for accurate assessment of DM and breast cancer status.^

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To reach the goals established by the Institute of Medicine (IOM) and the Centers for Disease Control's (CDC) STOP TB USA, measures must be taken to curtail a future peak in Tuberculosis (TB) incidence and speed the currently stagnant rate of TB elimination. Both efforts will require, at minimum, the consideration and understanding of the third dimension of TB transmission: the location-based spread of an airborne pathogen among persons known and unknown to each other. This consideration will require an elucidation of the areas within the U.S. that have endemic TB. The Houston Tuberculosis Initiative (HTI) was a population-based active surveillance of confirmed Houston/Harris County TB cases from 1995–2004. Strengths in this dataset include the molecular characterization of laboratory confirmed cases, the collection of geographic locations (including home addresses) frequented by cases, and the HTI time period that parallels a decline in TB incidence in the United States (U.S.). The HTI dataset was used in this secondary data analysis to implement a GIS analysis of TB cases, the locations frequented by cases, and their association with risk factors associated with TB transmission. ^ This study reports, for the first time, the incidence of TB among the homeless in Houston, Texas. The homeless are an at-risk population for TB disease, yet they are also a population whose TB incidence has been unknown and unreported due to their non-enumeration. The first section of this dissertation identifies local areas in Houston with endemic TB disease. Many Houston TB cases who reported living in these endemic areas also share the TB risk factor of current or recent homelessness. Merging the 2004–2005 Houston enumeration of the homeless with historical HTI surveillance data of TB cases in Houston enabled this first-time report of TB risk among the homeless in Houston. The homeless were more likely to be US-born, belong to a genotypic cluster, and belong to a cluster of a larger size. The calculated average incidence among homeless persons was 411/100,000, compared to 9.5/100,000 among housed. These alarming rates are not driven by a co-infection but by social determinants. The unsheltered persons were hospitalized more days and required more follow-up time by staff than those who reported a steady housing situation. The homeless are a specific example of the increased targeting of prevention dollars that could occur if TB rates were reported for specific areas with known health disparities rather than as a generalized rate normalized over a diverse population. ^ It has been estimated that 27% of Houstonians use public transportation. The city layout allows bus routes to run like veins connecting even the most diverse of populations within the metropolitan area. Secondary data analysis of frequent bus use (defined as riding a route weekly) among TB cases was assessed for its relationship with known TB risk factors. The spatial distribution of genotypic clusters associated with bus use was assessed, along with the reported routes and epidemiologic-links among cases belonging to the identified clusters. ^ TB cases who reported frequent bus use were more likely to have demographic and social risk factors associated with poverty, immune suppression and health disparities. An equal proportion of bus riders and non-bus riders were cultured for Mycobacterium tuberculosis, yet 75% of bus riders were genotypically clustered, indicating recent transmission, compared to 56% of non-bus riders (OR=2.4, 95%CI(2.0, 2.8), p<0.001). Bus riders had a mean cluster size of 50.14 vs. 28.9 (p<0.001). Second order spatial analysis of clustered fingerprint 2 (n=122), a Beijing family cluster, revealed geographic clustering among cases based on their report of bus use. Univariate and multivariate analysis of routes reported by cases belonging to these clusters found that 10 of the 14 clusters were associated with use. Individual Metro routes, including one route servicing the local hospitals, were found to be risk factors for belonging to a cluster shown to be endemic in Houston. The routes themselves geographically connect the census tracts previously identified as having endemic TB. 78% (15/23) of Houston Metro routes investigated had one or more print groups reporting frequent use for every HTI study year. We present data on three specific but clonally related print groups and show that bus-use is clustered in time by route and is the only known link between cases in one of the three prints: print 22. (Abstract shortened by UMI.)^