24 resultados para likelihood to publication


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Background. First synthesized in 1874, dichlorodiphenyltrichloroethane (DDT) was not used until the second half of World War II after its insecticidal properties were discovered in 1939. For decades DDT has been used globally with the intent of eradicating malaria. This began in 1955 when the eighth World Health Assembly launched a global campaign selecting DDT as the chemical of choice for the eradication of malaria. The United States banned DDT use in 1972 partially due to the publication of “Silent Spring” by Rachel Carson in 1962 which suggested that DDT was harmful to the environment, wildlife and is a carcinogen. ^ Objectives. To critically review the literature on DDT, and evaluate its importance in malaria prevention and control. Methods: The design of this systematic literature review is a narrative summary and evaluation of the papers reviewed. The data came from searches using PubMed and MEDLINE which are free and publicly available databases. Inclusive criteria that were considered during the search are English language peer reviewed journal articles published in the last 20 years. The keywords were: “insecticidal and agricultural use of DDT”, “human impact of malaria”, “economic impact of malaria”, “benefits of DDT”, “effects of DDT”, “importance of malaria control”, and alternatives to DDT for malaria control. ^ Results. Malaria continues to be one of the most common infectious diseases and creates a tremendous global public health problem. WHO recommends DDT for malaria vector control because compared to other pesticides, it is the most persistent in indoor spraying. ^ Conclusion. Indoor spraying of DDT in malaria endemic areas may cause increased exposure of the chemical to humans; however I conclude that the overall benefits outweigh the risks because more lives are saved due to fewer infections with malaria.^

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A Bayesian approach to estimating the intraclass correlation coefficient was used for this research project. The background of the intraclass correlation coefficient, a summary of its standard estimators, and a review of basic Bayesian terminology and methodology were presented. The conditional posterior density of the intraclass correlation coefficient was then derived and estimation procedures related to this derivation were shown in detail. Three examples of applications of the conditional posterior density to specific data sets were also included. Two sets of simulation experiments were performed to compare the mean and mode of the conditional posterior density of the intraclass correlation coefficient to more traditional estimators. Non-Bayesian methods of estimation used were: the methods of analysis of variance and maximum likelihood for balanced data; and the methods of MIVQUE (Minimum Variance Quadratic Unbiased Estimation) and maximum likelihood for unbalanced data. The overall conclusion of this research project was that Bayesian estimates of the intraclass correlation coefficient can be appropriate, useful and practical alternatives to traditional methods of estimation. ^

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A Bayesian approach to estimation of the regression coefficients of a multinominal logit model with ordinal scale response categories is presented. A Monte Carlo method is used to construct the posterior distribution of the link function. The link function is treated as an arbitrary scalar function. Then the Gauss-Markov theorem is used to determine a function of the link which produces a random vector of coefficients. The posterior distribution of the random vector of coefficients is used to estimate the regression coefficients. The method described is referred to as a Bayesian generalized least square (BGLS) analysis. Two cases involving multinominal logit models are described. Case I involves a cumulative logit model and Case II involves a proportional-odds model. All inferences about the coefficients for both cases are described in terms of the posterior distribution of the regression coefficients. The results from the BGLS method are compared to maximum likelihood estimates of the regression coefficients. The BGLS method avoids the nonlinear problems encountered when estimating the regression coefficients of a generalized linear model. The method is not complex or computationally intensive. The BGLS method offers several advantages over Bayesian approaches. ^

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In geographical epidemiology, maps of disease rates and disease risk provide a spatial perspective for researching disease etiology. For rare diseases or when the population base is small, the rate and risk estimates may be unstable. Empirical Bayesian (EB) methods have been used to spatially smooth the estimates by permitting an area estimate to "borrow strength" from its neighbors. Such EB methods include the use of a Gamma model, of a James-Stein estimator, and of a conditional autoregressive (CAR) process. A fully Bayesian analysis of the CAR process is proposed. One advantage of this fully Bayesian analysis is that it can be implemented simply by using repeated sampling from the posterior densities. Use of a Markov chain Monte Carlo technique such as Gibbs sampler was not necessary. Direct resampling from the posterior densities provides exact small sample inferences instead of the approximate asymptotic analyses of maximum likelihood methods (Clayton & Kaldor, 1987). Further, the proposed CAR model provides for covariates to be included in the model. A simulation demonstrates the effect of sample size on the fully Bayesian analysis of the CAR process. The methods are applied to lip cancer data from Scotland, and the results are compared. ^

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Traditional comparison of standardized mortality ratios (SMRs) can be misleading if the age-specific mortality ratios are not homogeneous. For this reason, a regression model has been developed which incorporates the mortality ratio as a function of age. This model is then applied to mortality data from an occupational cohort study. The nature of the occupational data necessitates the investigation of mortality ratios which increase with age. These occupational data are used primarily to illustrate and develop the statistical methodology.^ The age-specific mortality ratio (MR) for the covariates of interest can be written as MR(,ij...m) = ((mu)(,ij...m)/(theta)(,ij...m)) = r(.)exp (Z('')(,ij...m)(beta)) where (mu)(,ij...m) and (theta)(,ij...m) denote the force of mortality in the study and chosen standard populations in the ij...m('th) stratum, respectively, r is the intercept, Z(,ij...m) is the vector of covariables associated with the i('th) age interval, and (beta) is a vector of regression coefficients associated with these covariables. A Newton-Raphson iterative procedure has been used for determining the maximum likelihood estimates of the regression coefficients.^ This model provides a statistical method for a logical and easily interpretable explanation of an occupational cohort mortality experience. Since it gives a reasonable fit to the mortality data, it can also be concluded that the model is fairly realistic. The traditional statistical method for the analysis of occupational cohort mortality data is to present a summary index such as the SMR under the assumption of constant (homogeneous) age-specific mortality ratios. Since the mortality ratios for occupational groups usually increase with age, the homogeneity assumption of the age-specific mortality ratios is often untenable. The traditional method of comparing SMRs under the homogeneity assumption is a special case of this model, without age as a covariate.^ This model also provides a statistical technique to evaluate the relative risk between two SMRs or a dose-response relationship among several SMRs. The model presented has application in the medical, demographic and epidemiologic areas. The methods developed in this thesis are suitable for future analyses of mortality or morbidity data when the age-specific mortality/morbidity experience is a function of age or when there is an interaction effect between confounding variables needs to be evaluated. ^

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The purpose of this research was to better understand the impact of the terrorist attacks in 2001 on public health, particularly for Texas public health. This study employed mixed methods to examine changes to public health culture within Texas local public health agencies, important attitudes of public health workers toward responding to a disaster, and the funding policies that might ensure our investment in public health emergency preparedness is protected. ^ A qualitative analysis of interviews conducted with a large sample of public health officials in Texas found that all the constituent parts of a peculiar culture for public health preparedness existed that spanned the state's local health departments regardless of size, or funding level. The new preparedness culture in Texas had the hallmarks necessary for a robust public health preparedness and emergency response system. ^ The willingness of public health workers, necessary to make these kinds of changes and mount a disaster response was examined in one of Texas' most experienced disaster response teams—the public health workers for the City of Houston. A hypothesized latent variable model showed that willingness mediated all other factors in the model (self-efficacy, knowledge, barriers, and risk perception) for self-reported likelihood of reporting to work for a disaster. The RMSEA for the final model was 0.042 with a confidence interval of 0.036—0.049 and the chi-squared difference test was P=0.08, indicating a well-fitted model that suggests willingness is an important factor for consideration by preparedness planners and researchers alike. ^ Finally, with disasters on the rise and federal funding for preparedness dwindling, a review of states' policies for the distribution of these funds and their advantages and disadvantages were examined through a review of current literature and public documents, and a survey of state-level public health officials, emergency management professionals and researchers. Although the base plus per-capita method is the most common, it is not necessarily perceived to be the most effective. No clear "optimal" method emerged from the study, but recommendations for a strategic combination of three methods were made that has the potential to maximize the benefits of each method, while minimizing the weaknesses.^

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According to the transtheoretical model, consciousness raising and social liberation are processes used to help individuals progress through the stages of change for a given behavior. This study assessed the impact of these two processes on readiness to engage in regular physical activity among a convenience sample of 35 adults in the Magnolia Park/Lawndale-Wayside area of Houston, TX. The duration of the study was approximately 4 weeks. All pre/post-test data were collected via self-administered surveys available in English or Spanish. Baseline data were used to determine the culturally relevant content of a one-dose intervention consisting of a presentation and dissemination of educational materials as well as a list of local physical activity opportunities. Although the intervention did not improve progression through the stages of change, significant increases were evident among 5 out of 6 processes of change. Based on these results and qualitative data, this study recommended that the Houston Parks and Recreation Department incorporate cultural competency into the design and publication of materials and revise the schedule of available programs (i.e.: increase the number of walking programs) in order to reflect the physical activity preferences of Magnolia Park/Lawndale-Wayside residents.^

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Pancreatic cancer is the 4th most common cause for cancer death in the United States, accompanied by less than 5% five-year survival rate based on current treatments, particularly because it is usually detected at a late stage. Identifying a high-risk population to launch an effective preventive strategy and intervention to control this highly lethal disease is desperately needed. The genetic etiology of pancreatic cancer has not been well profiled. We hypothesized that unidentified genetic variants by previous genome-wide association study (GWAS) for pancreatic cancer, due to stringent statistical threshold or missing interaction analysis, may be unveiled using alternative approaches. To achieve this aim, we explored genetic susceptibility to pancreatic cancer in terms of marginal associations of pathway and genes, as well as their interactions with risk factors. We conducted pathway- and gene-based analysis using GWAS data from 3141 pancreatic cancer patients and 3367 controls with European ancestry. Using the gene set ridge regression in association studies (GRASS) method, we analyzed 197 pathways from the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Using the logistic kernel machine (LKM) test, we analyzed 17906 genes defined by University of California Santa Cruz (UCSC) database. Using the likelihood ratio test (LRT) in a logistic regression model, we analyzed 177 pathways and 17906 genes for interactions with risk factors in 2028 pancreatic cancer patients and 2109 controls with European ancestry. After adjusting for multiple comparisons, six pathways were marginally associated with risk of pancreatic cancer ( P < 0.00025): Fc epsilon RI signaling, maturity onset diabetes of the young, neuroactive ligand-receptor interaction, long-term depression (Ps < 0.0002), and the olfactory transduction and vascular smooth muscle contraction pathways (P = 0.0002; Nine genes were marginally associated with pancreatic cancer risk (P < 2.62 × 10−5), including five reported genes (ABO, HNF1A, CLPTM1L, SHH and MYC), as well as four novel genes (OR13C4, OR 13C3, KCNA6 and HNF4 G); three pathways significantly interacted with risk factors on modifying the risk of pancreatic cancer (P < 2.82 × 10−4): chemokine signaling pathway with obesity ( P < 1.43 × 10−4), calcium signaling pathway (P < 2.27 × 10−4) and MAPK signaling pathway with diabetes (P < 2.77 × 10−4). However, none of the 17906 genes tested for interactions survived the multiple comparisons corrections. In summary, our current GWAS study unveiled unidentified genetic susceptibility to pancreatic cancer using alternative methods. These novel findings provide new perspectives on genetic susceptibility to and molecular mechanisms of pancreatic cancer, once confirmed, will shed promising light on the prevention and treatment of this disease. ^

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There is not a large body of evidence on in-utero exposure to chemotherapy for pregnancy-associated cancers to help determine the long term effects on offspring. This study is a systematic review of long term follow-up to find evidence for adverse outcomes in exposed offspring. In order for studies to be eligible for this systematic review, they had to have a median follow up of at least 24 months with the resulting child. PubMed, Medline, and Scopus were the databases used, and we included all eligible articles, regardless of the date of publication. The search resulted in six articles meeting the eligibility requirements. The review of findings of these studies suggested that there is not enough evidence to make a determination of the risk of chemotherapy for the offspring. Exposed children in the sample of reviewed papers did have some medical conditions, but the rate and type did not differ from the non-exposed population. However, a limitation of this literature review is the very small sample size of publications on this important topic. This finding of few studies on this topic is an important result of this systematic review. More research and long term follow-up studies must be conducted to address this issue.^