912 resultados para Competing risks, Estimation of predator mortality, Over dispersion, Stochastic modeling


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The aim of this study was to determine cancer mortality rates for the United Arab Emirates (UAE) and to create an atlas of cancer mortality for the UAE. This atlas is the first of its kind in the Gulf country and the Middle East. Death certificates were reviewed for a period from January 1, 1990 to December 31, 1999 and cancer deaths were identified. Cancer mortality cases were verified by comparing with medical records. Age-adjusted cancer mortality rates were calculated by gender, emirate/medical district and nationality (UAE nationals and overall UAE population). Individual rates for each emirate were compared to the overall rate of the corresponding population for the same cancer site and gender. Age-adjusted rates were mapped using MapInfo software. High rates for liver, lung and stomach cancer were observed in Abu Dhabi, Dubai and the northern emirates, respectively. Rates for UAE nationals were greater compared to the overall UAE population. Several factors were suggested that may account for high rates of specific cancers observed in certain emirates. It is hoped that this atlas will provide leads that will guide further epidemiologic and public health activities aimed at preventing cancer. ^

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Genome-Wide Association Study analytical (GWAS) methods were applied in a large biracial sample of individuals to investigate variation across the genome for its association with a surrogate low-density lipoprotein (LDL) particle size phenotype, the ratio of LDL-cholesterol level over ApoB level. Genotyping was performed on the Affymetrix 6.0 GeneChip with approximately one million single nucleotide polymorphisms (SNPs). The ratio of LDL cholesterol to ApoB was calculated, and association tests used multivariable linear regression analysis with an additive genetic model after adjustment for the covariates sex, age and BMI. Association tests were performed separately in African Americans and Caucasians. There were 9,562 qualified individuals in the Caucasian group and 3,015 qualified individuals in the African American group. Overall, in Caucasians two statistically significant loci were identified as being associated with the ratio of LDL-cholesterol over ApoB: rs10488699 (p<5 x10-8, 11q23.3 near BUD13) and the SNP rs964184 (p<5 x10-8 11q23.3 near ZNF259). We also found rs12286037 ((p<4x10-7) (11q23.3) near APOA5/A4/C3/A1 with suggestive associate in the Caucasian sample. In exploratory analyses, a difference in the pattern of association between individuals taking and not taking LDL-cholesterol lowering medications was observed. Individuals who were not taking medications had smaller p-value than those taking medication. In the African-American group, there were no significant (p<5x10-8) or suggestive associations (p<4x10-7) with the ratio of LDL-cholesterol over ApoB after adjusting for age, BMI, and sex and comparing individuals with and without LDL-cholesterol lowering medication. Conclusions: There were significant and suggestive associations between SNP genotype and the ratio of LDL-cholesterol to ApoB in Caucasians, but these associations may be modified by medication treatment.^

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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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Infant mortality as a problematic situation has been recognized for some 130 years in one form or another. It has undergone various changes in its empirical dimensions relative to whom we study within the population, what we study--low birth-weight vs. pre-term births--and how we study it--whether demographically or medically. An analysis of the process by which the condition was raised by claims makers as an intolerable situation among America's urban residents reveals that demographic and medical data were sparse. Nonetheless, a judgement about the meaning and significance of the condition was made, and that interpretation led to the promulgation of systems to both document and address the condition as it has come to be defined.^ This investigation depicts the historical context and natural history of infant mortality as one of a number of social problems that came to be defined through the interplay among groups and individuals making claims and how their claims came to the public policy agenda as worthy of collective resources--who won, who lost and why. The process of social definition focuses attention on the claims makers and the ways they contrast the meaning, origins and remedies for this troubling condition. The historical context becomes the frame of reference for understanding the actions of the claims makers and the meaning and significance they attached to the problem.^ We purport that "context" provides a closer reality than disjoined "value free" accounts. Context provides the evidence for the definition, who participated in the process, why and by what means.^ The role of women in the definitional process reveals the differences in approaches utilized by the women of the settlement house reform movement and African-American women working at the grass-roots. Much of the work done by these two groups provided options to the problem's remedy; however, their differences paved the way to our current (principally medically-oriented) definition and its inherent limitations. ^

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The geographic distribution of average annual age-adjusted mortality rates (1964-1976) for four types of cancer (all cancer sites combined, gastrointestinal, urinary, and lung cancer) were compared by sources of drinking water for 254 Texas counties and county rural areas and 301 Texas cities. Exposure variables considered were surface versus ground water, public water supplies versus individuals wells, and trihalomethane levels in municipal water supplies. Each general source of "surface" and "ground" water was further divided by aggregating ground water using areas by aquifers and surface water using study areas by river basins. Potential confounding variables taken into account included median education, employment in cancer risk industries, population mobility, ethnicity, and urbanicity. A pattern of higher and lower cancer mortality rates was found for populations using some aquifers and river basins. Further study is required to determine whether the differences in cancer mortality rates that were observed are related to drinking water content or are coincidental with differences in personal characteristics which could not be taken into account in this ecologic study design. ^

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This study provides a review of the current alcoholism planning process of the Houston-Galveston planning process of the Houston-Galveston Area Council, an agency carrying out planning for a thirteen county region in surrounding Houston, Texas. The four central groups involved in this planning are identified, and the role that each plays and how it effects the planning outcomes is discussed.^ The most substantive outcome of the Houston-Galveston Area Council's alcoholism planning, the Regional Alcoholism/Alcohol Abuse Plan is examined. Many of the shortcomings in the data provided, and the lack of other data necessary for planning are offered.^ A problem oriented planning model is presented as an alternative to the Houston-Galveston Area Council's current service oriented approach to alcoholism planning. Five primary phases of the model, identification of the problem, statement of objectives, selection of alternative programs, implementation, and evaluation, are presented, and an overview of the tasks involved in the application of this model to alcoholism planning is offered.^ A specific aspect of the model, the use of problem status indicators is explored using cirrhosis and suicide mortality data. A review of the literature suggests that based on five criteria, availability, subgroup identification, validity, reliability, and sensitivity, both suicide and cirrhosis are suitable as indicators of the alcohol problem when combined with other indicators.^ Cirrhosis and suicide mortality data are examined for the thirteen county Houston-Galveston Region for the years 1969 through 1976. Data limitations preclude definite conclusions concerning the alcohol problem in the region. Three hypotheses about the nature of the regional alcohol problem are presented. First, there appears to be no linear trend in the number of alcoholics that are at risk of suicide and cirrhosis mortality. Second, the number of alcoholics in the metropolitan areas seems to be greater than the number of rural areas. Third, the number of male alcoholics at risk of cirrhosis and suicide mortality is greater than the number of female alcoholics.^

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The purpose of this study was to examine, in the context of an economic model of health production, the relationship between inputs (health influencing activities) and fitness.^ Primary data were collected from 204 employees of a large insurance company at the time of their enrollment in an industrially-based health promotion program. The inputs of production included medical care use, exercise, smoking, drinking, eating, coronary disease history, and obesity. The variables of age, gender and education known to affect the production process were also examined. Two estimates of fitness were used; self-report and a physiologic estimate based on exercise treadmill performance. Ordinary least squares and two-stage least squares regression analyses were used to estimate the fitness production functions.^ In the production of self-reported fitness status the coefficients for the exercise, smoking, eating, and drinking production inputs, and the control variable of gender were statistically significant and possessed theoretically correct signs. In the production of physiologic fitness exercise, smoking and gender were statistically significant. Exercise and gender were theoretically consistent while smoking was not. Results are compared with previous analyses of health production. ^

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HIV/AIDS is a treatable although incurable disease that presents immense challenges to those infected including physical, social and psychological effects. As of 2009, an estimated 2.4 million people were living with HIV or AIDS in India, 0.3% of the country's population. In India, it is difficult to not only treat but also to track because it is associated with socio-economic factors such as illiteracy, social biases, poor sanitation, malnutrition and social class. Nevertheless, it is important to know the prevalence of HIV/AIDS for several reasons. At the individual level, the quality of life of people living with HIV/AIDS is markedly lower than their counterparts without the disease and is associated with challenges. At the community level, it is important to identify high risk groups, monitor prevention efforts, and allocate appropriate resources to target programs for the reduction of transmission of HIV. ^

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This study proposed a novel statistical method that modeled the multiple outcomes and missing data process jointly using item response theory. This method follows the "intent-to-treat" principle in clinical trials and accounts for the correlation between outcomes and missing data process. This method may provide a good solution to chronic mental disorder study. ^ The simulation study demonstrated that if the true model is the proposed model with moderate or strong correlation, ignoring the within correlation may lead to overestimate of the treatment effect and result in more type I error than specified level. Even if the within correlation is small, the performance of proposed model is as good as naïve response model. Thus, the proposed model is robust for different correlation settings if the data is generated by the proposed model.^

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Accurate quantitative estimation of exposure using retrospective data has been one of the most challenging tasks in the exposure assessment field. To improve these estimates, some models have been developed using published exposure databases with their corresponding exposure determinants. These models are designed to be applied to reported exposure determinants obtained from study subjects or exposure levels assigned by an industrial hygienist, so quantitative exposure estimates can be obtained. ^ In an effort to improve the prediction accuracy and generalizability of these models, and taking into account that the limitations encountered in previous studies might be due to limitations in the applicability of traditional statistical methods and concepts, the use of computer science- derived data analysis methods, predominantly machine learning approaches, were proposed and explored in this study. ^ The goal of this study was to develop a set of models using decision trees/ensemble and neural networks methods to predict occupational outcomes based on literature-derived databases, and compare, using cross-validation and data splitting techniques, the resulting prediction capacity to that of traditional regression models. Two cases were addressed: the categorical case, where the exposure level was measured as an exposure rating following the American Industrial Hygiene Association guidelines and the continuous case, where the result of the exposure is expressed as a concentration value. Previously developed literature-based exposure databases for 1,1,1 trichloroethane, methylene dichloride and, trichloroethylene were used. ^ When compared to regression estimations, results showed better accuracy of decision trees/ensemble techniques for the categorical case while neural networks were better for estimation of continuous exposure values. Overrepresentation of classes and overfitting were the main causes for poor neural network performance and accuracy. Estimations based on literature-based databases using machine learning techniques might provide an advantage when they are applied to other methodologies that combine `expert inputs' with current exposure measurements, like the Bayesian Decision Analysis tool. The use of machine learning techniques to more accurately estimate exposures from literature-based exposure databases might represent the starting point for the independence from the expert judgment.^

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Studies suggest that slim infants (low weight-for-height) experienced higher mortality rates than average or high weight-for-height infants (Miller and Hassanein, 1973; Hoffman, Meirik, and Bakketeig, 1984). In this study, the 1980 National Natality Survey and the National Fetal Mortality Survey were used to examine the association of weight, height and perinatal mortality. All singleton births to white married mothers, between 18 and 34 years of age and of parity less than 4, for whom both mother's and hospital questionnaires were completed in those two surveys (3796 live births and 2043 fetal deaths) were selected for analysis. Overall, low weight and height infants had excess mortality rates. However, after adjustment for low birthweight and preterm birth status, low weight and height infants had only slightly higher mortality rates than their medium or high weight and height counterparts. The current study consists of relatively well-educated white married mothers of optimal reproductive age and low parity. Therefore, lower than expected mortality rates for slim infants may be attributed to these favorable demographic factors in this sample as compared with previous studies, or because of advances in perinatal medicine, slim infants may be prevented from achieving the high mortality seen in earlier studies. ^