Cultural competence is widely recognized as an essential strategy for reducing health disparities. As the United States' population becomes increasingly ethno-culturally diverse, these disparities are becoming even more pronounced. One particular challenge in this regard concerns overweight/obesity prevalence among American adults, as a disproportionately high number of racial and ethnic minority adults are classified as overweight or obese. Dietary behavior assessments are often utilized by health and human services professionals to obtain the data necessary to promote goals such as the reduction and elimination of overweight/obesity across all ethno-cultural groups. The primary objective of this research study was to develop, test, and evaluate a culturally-competent dietary behavior assessment instrument by effectively synthesizing qualitative methods from Cognitive Anthropology with appropriate survey research and quantitative statistical methods. Specifically, a quantitative methods triangle of hierarchical cluster analysis, binary logistic regression, and Poisson regression in conjunction with the free listing qualitative research technique from Cognitive Anthropology was explored as a possible combined methodological approach for researchers and public health professionals wishing to develop a comprehensive understanding of dietary behaviors at the local community level. Binary logistic regression and Poisson regression enabled the relationship between selected food categories and certain demographic/cultural indicators to be modeled, while hierarchical cluster analyses enabled modeling of the distinct patterns of food category groupings that comprise individuals' regular diet. Additionally, initial qualitative analyses of the raw data promoted an understanding of the influence that the local fast food and dine-in restaurant environment has on the dietary behaviors of the target population. The results of this study suggest that a quantitative methods triangle of hierarchical cluster analysis, binary logistic regression analysis, and Poisson regression analysis founded upon qualitative research principles has potential for use as a combined methodological approach for researchers and public health professionals wishing to develop a comprehensive understanding of dietary behaviors at the local community level. By employing these techniques, researchers can analyze individual dietary behaviors and eating patterns from a multifaceted perspective. In turn, public health professionals can develop community-based, cross-culturally relevant programs and interventions that are equally effective across all ethno-cultural groups in their target population.

This thesis investigates the factors that are associated with annual changes in the share price of Johannesburg Stock Exchange (JSE) listed companies. In this study, an increase in value of a share is when the share price of a company goes up by the end of the financial year as compared to the previous year. Secondary data that was sourced from McGregor BFA website was used. The data was from 2004 up to 2011. Deciding which share to buy is the biggest challenge faced by both investment companies and individuals when investing on the stock exchange. This thesis uses binary logistic regression to identify the variables that are associated with share price increase. The dependent variable was annual change in share price (ACSP) and the independent variables were assets per capital employed ratio, debt per assets ratio, debt per equity ratio, dividend yield, earnings per share, earnings yield, operating profit margin, price earnings ratio, return on assets, return on equity and return on capital employed. Different variable selection methods were used and it was established that the backward elimination method produced the best model. It was established that the probability of success of a share is higher if the shareholders are anticipating a higher return on capital employed, and high earnings/ share. It was however, noted that the share price is negatively impacted by dividend yield and earnings yield. Since the odds of an increase in share price is higher if there is a higher return on capital employed and high earning per share, investors and investment companies are encouraged to choose companies with high earnings per share and the best returns on capital employed. The final model had a classification rate of 68.3% and the validation sample produced a classification rate of 65.2% / Mathematical Sciences / M.Sc. (Statistics)

These studies were undertaken in the state of Mato Grosso, Brazil, in the area of Chapada dos Guimarães and Baixada Cuiabana, which are constituted of a high plateau and a big low plain, respectively, being limited to two areas covered by vegetation with a savannic physiognomy, type Cerrado stricto sensu. Considering the hypothesis that the knowledge both of the biotic and abiotic components of the scenery and their interrelations allows a better understanding of the environmental dynamic, this dissertation had as objectives to characterize the savanna communities' arboreal stratum floristically and phytosociologically, concerning their richness, phytosociological structures and diversity; to identify floristic groupings through varied statistical techniques, representing them by dendrograms; to select species which are really able to make discrimination among the groups; to obtain some discriminant functions to allow classification and reclassification of specimen units, in the groups, to which they have more probability of belonging; to analyze and to characterize the obtained groups; to determine the patterns of distribution of the species of trees by the analysis of correlations of environmental variables with the distribution of the species and plots in the communities being studied; to determine the similarity indexes among the floristic groups and to compare themselves and, finally, to test methods of assorted statistical analysis for application in studies of vegetable communities. Data of vegetation were obtained by the method of multiple plots, with size of 20 X 20 m (400 m2), randomly disposed in each one of the areas being studied. 82 plots were randomly installed. In each one of the 82 patternless units, the circumferences of all the arboreal plants with perimeter to 0,30 m from the level of the soil (PAB) larger or equal to 15,7 cm (DAB 5,0 cm) and the total height of the plants were obtained. In the core of each plot, for determination of the chemical and textural variables of the soil, simple samples of superficial soil were collected (0-30 cm depth). Species were organized according to the families recognized by Angiosperm Phylogeny Group II. The sampling sufficiency was obtained based on the analysis of the curve of the collector. Phytosociological parameters were calculated for each formed group, with the purpose of characterizing them phytosociologically. Having as variables the Index of Covering Value (IVC) of the species, the classification was accomplished by the TWINSPAN (Two-Way Indicator Species Analysis) method, regarding the plots, with the objective of classifying them in floristic groups. The diversity was determined by the Shannon-Wienner and the Simpson Index. The discriminant analysis was undertaken through the STEPWISE method. Considering the matrix of presence and absence of the species in the groups, the floristic similarity was calculated among the groups by the Sorensen Index. To evaluate the hypothesis of the correlation existence between the distribution of the species and environmental variables, the canonical correspondence analysis was accomplished (CCA). The test of permutation of Monte Carlo was applied to verify the importance of the correlations between the emerging distribution patterns of the species and the environmental variables in final CCA. To determine the responsible environmental factors for the distribution of the species, the analysis of regression logistics was used. The Forward Stepwise (Wald) method was used for the sequential selection of the variables. By the species-area curve, it could be observed that, from the plot 75 (30.000 m2 out of the area used as sample), the curve is stabilized with the occurrence of 114 species in the 82 studied plots, distributed between 81 genera and 36 botanical families. The families better represented were Fabaceae, Myrtaceae and Vochysiaceae. The alpha diversity from the arboreal vegetation found in the area being studied was of 4,033 considering the Shannon-Wiener Index and of 0,975 considering the Simpson Index, representing a great floristic diversity. The divisions generated by the classification through the TWINSPAN method separated the plots into four groups: Group 1 Myrcia albo-tomentosa Camb. Association; Group 2 Pterodon emarginatus Vog. Association ; Group 3 Curatella americana L. Association; and Group 4 Qualea multiflora Mart. Association. In the discriminant analysis, 100% of the plots were classified correctly in the Groups 1, 2, 3 and 4, indicating precision of the grouping technique used. The largest similarity could be observed in the Groups 2 and 3, whose Sorensen Index was close to 1 (0,7310). In the four floristic groups, Fabaceae, Myrtaceae, Vochysiaceae, Annonaceae and Apocynaceae families were the most representative floristically in terms of genera and species. In CCA the correlations of the environmental variables with the first ordination axis were, in decreasing order of absolute values, saturation for aluminum, altitude s.n.m., saturation of bases, saturation for magnesium, relationship magnesium/potassium, saturation for hydrogen, potassium tenor, pH(H2O) and relationship calcium/potassium. The saturation for calcium variable presented very weak correlation with the first axis, however, with the second ordination axis, it was very strong. In the diagram of ordination of the plots, the four floristic groups were discriminated in sections different from the diagram, reinforcing their visualization as much defined habitats and with composition of particular species, resulting in clear separation of the four soil classes previously identified. The logistic regression analysis was useful to prove the results obtained from CCA, concerning the environmental variables which determined the distribution of the indicative species of the floristic groups in the studied communities. / Estes estudos foram desenvolvidos no estado de Mato Grosso, Brasil, na região de Chapada dos Guimarães e Baixada Cuiabana, que compreendem, respectivamente, um alto platô e uma grande planície baixa, restringindo-se a duas áreas cobertas por vegetação com fisionomia savânica do tipo Cerrado stricto sensu. Partindo-se da hipótese de que o conhecimento tanto dos componentes bióticos e abióticos da paisagem como de suas inter-relações permite um melhor entendimento da dinâmica ambiental, o presente estudo teve como objetivos caracterizar o estrato arbóreo das comunidades de savana estudadas, florística e fitossociologicamente, quanto a riqueza, estrutura fitossociológica e diversidade; identificar agrupamentos florísticos, por meio de técnicas estatísticas multivariadas, representando-os por meio de dendrograma; selecionar espécies com poder real de discriminação entre os grupos; obter funções discriminantes que permitam classificar e reclassificar unidades amostrais, nos grupos, para os quais têm maior probabilidade de pertencerem; analisar e caracterizar os grupos obtidos; determinar os padrões de distribuição das espécies de árvores, por meio da análise de correlações de variáveis ambientais com a distribuição das espécies e parcelas nas comunidades estudadas; determinar os índices de similaridade entre os grupos florísticos obtidos e compará-los; e testar métodos de análise estatística multivariada para aplicação em estudos de comunidades vegetais. Os dados da vegetação foram obtidos empregando-se o método de parcelas múltiplas, com tamanho de 20 X 20 m (400 m2), dispostas aleatoriamente em cada uma das áreas de estudos. Foram instaladas aleatoriamente 82 parcelas. Em cada uma das 82 unidades amostrais, foram obtidas as circunferências de todos as plantas arbóreas com perímetro a 0,30 m do nível do solo (PAB) maior ou igual a 15,7 cm (DAB  5,0 cm), e a altura total das plantas. No centro de cada parcela, para determinação das variáveis químicas e texturais do solo, coletaram-se amostras simples de solo superficial (0-30 cm de profundidade). As espécies foram organizadas de acordo com as famílias reconhecidas pelo Angiosperm Phylogeny Group II. A suficiência de amostragem foi obtida com base na análise da curva do coletor. Os parâmetros fitossociológicos foram calculados para cada grupo formado, com a finalidade de caracterizá-los fitossociológicamente. Tendo como variáveis o Índice de Valor de Cobertura (IVC) das espécies, foi realizada a classificação, por meio do método TWINSPAN (Two-Way Indicator Species Analisys), com relação às parcelas, com o objetivo de classificá-las em grupos florísticos. A diversidade foi determinada por meio do Índice de Shannon-Wienner e de Simpson. Realizou-se a análise discriminante por meio do método STEPWISE. A partir da matriz de presença e ausência das espécies nos grupos, foi calculada a similaridade florística entre os grupos, por meio do Índice de Sorensen. Para avaliar a hipótese da existência de correlação entre a distribuição das espécies e variáveis ambientais, foi realizada a análise de correspondência canônica (CCA). Foi aplicado o teste de permutação de Monte Carlo para verificar a significância das correlações entre os padrões de distribuição emergentes das espécies e as variáveis ambientais na CCA final. Para determinar os fatores ambientais responsáveis pela distribuição das espécies, foi utilizada a análise de regressão logística. À seleção seqüencial das variáveis foi utilizado o método Forward Stepwise (Wald). Pela curva espécie-área, pode-se observar que, a partir da parcela 75 (30.000 m2 da área amostrada), a curva estabiliza-se com a ocorrência de 114 espécies nas 82 parcelas estudadas, distribuídas entre 81 gêneros e 36 famílias botânicas. As famílias mais bem representadas foram Fabaceae, Myrtaceae e Vochysiaceae. A diversidade alfa da vegetação arbórea encontrada na área estudada foi de 4,033 pelo índice de Shannon-Wiener e de 0,975 pelo de Simpson, indicando alta diversidade florística. As divisões geradas pela classificação por meio do método TWINSPAN separaram as parcelas em quatro grupos. Grupo 1 - Associação Myrcia albo-tomentosa Camb.; Grupo 2 - Associação Pterodon emarginatus Vog.; Grupo 3 - Associação Curatella americana L.; e Grupo 4 - Associação Qualea multiflora Mart.. Na análise discriminante, observou-se que 100% das parcelas foram classificadas corretamente nos grupos 1, 2, 3 e 4, indicando precisão da técnica de agrupamento utilizada. A maior similaridade se deu entre os grupos 2 e 3, cujo índice de Sorensen foi próximo de 1 (0,7310). Nos quatro grupos florísticos obtidos, as famílias Fabaceae, Myrtaceae, Vochysiaceae, Annonaceae e Apocynaceae foram as mais representativas florísticamente em número de gêneros e espécies. Na CCA, as correlações das variáveis ambientais com o primeiro eixo de ordenação foram, em ordem decrescente de valores absolutos, saturação por alumínio, altitude s.n.m., saturação de bases, saturação por magnésio, relação magnésio/potássio, saturação por hidrogênio, teor de potássio, pH(H2O) e relação cálcio/potássio. A variável saturação por cálcio apresentou correlação muito fraca com o primeiro eixo, entretanto, com o segundo eixo de ordenação, foi muito forte. No diagrama de ordenação das parcelas, os quatro grupos florísticos foram discriminados em setores diferentes do diagrama, reforçando a visualização dos mesmos como hábitats bem definidos e com composição de espécies particular, resultando em clara separação das quatro classes de solo identificadas previamente. A análise de regressão logística comprovou os resultados obtidos da CCA, em relação às variáveis ambientais que determinaram a distribuição das espécies indicadoras dos grupos florísticos nas comunidades estudadas.

Orientadores: Antonio Carlos Moretti, Márcia Aparecida Gomes Ruggiero / Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Matemática Estatística e Computação Científica / Made available in DSpace on 2018-08-26T18:03:59Z (GMT). No. of bitstreams: 1 Caetano_Mateus_M.pdf: 1249293 bytes, checksum: f8adb755363291250261872ea756f58c (MD5) Previous issue date: 2015 / Resumo: Técnicas para solucionar problemas de classificação têm aplicações em diversas áreas, como concessão de crédito, reconhecimento de imagens, detecção de SPAM, entre outras. É uma área de intensa pesquisa, para a qual diversos métodos foram e continuam sendo desenvolvidos. Dado que não há um método que apresente o melhor desempenho para qualquer tipo de aplicação, diferentes métodos precisam ser comparados para que possamos encontrar o melhor ajuste para cada aplicação em particular. Neste trabalho estudamos seis diferentes métodos aplicados em problemas de classificação supervisionada (onde há uma resposta conhecida para o treinamento do modelo): Regressão Logística, Árvore de Decisão, Naive Bayes, KNN (k-Nearest Neighbors), Redes Neurais e Support Vector Machine. Aplicamos os métodos em três conjuntos de dados referentes à problemas de concessão de crédito e seleção de clientes para campanha de marketing bancário. Realizamos o pré-processamento dos dados para lidar com observações faltantes e classes desbalanceadas. Utilizamos técnicas de particionamento do conjunto de dados e diversas métricas, como acurácia, F1 e curva ROC, com o objetivo de avaliar os desempenhos dos métodos/técnicas. Comparamos, para cada problema, o desempenho dos diferentes métodos considerando as métricas selecionadas. Os resultados obtidos pelos melhores modelos de cada aplicação foram compatíveis com outros estudos que utilizaram os mesmos bancos de dados / Abstract: Techniques for classification problems have applications on many areas, such as credit risk evaluation, image recognition, SPAM detection, among others. It is an area of intense research, for which many methods were and continue to be developed. Given that there is not a method whose performance is better across any type of problems, different methods need to be compared in order to select the one that provides the best adjustment for each application in particular. In this work, we studied six different methods applied to supervised classification problems (when there is a known response for the model training): Logistic Regression, Decision Tree, Naive Bayes, KNN (k-Nearest Neighbors), Neural Networks and Support Vector Machine. We applied these methods on three data sets related to credit evaluation and customer selection for a banking marketing campaign. We made the data pre-processing to cope with missing data and unbalanced classes. We used data partitioning techniques and several metrics, as accuracy, F1 and ROC curve, in order to evaluate the methods/techniques performances. We compared, for each problem, the performances of the different methods using the selected metrics. The results obtained for the best models on each application were comparable to other studies that have used the same data sources / Mestrado / Matematica Aplicada / Mestra em Matemática Aplicada

Från 1900-talets början har banker och låneinstitut använt nyckeltal som hjälpmedel vid bedömning och kvantifiering av kreditrisk. För dagens investerare är den ekonomiska miljön mer komplicerad än för bara 40 år sedan då teknologin och datoriseringen öppnade upp världens marknader mot varandra. Bedömning av kreditrisk idag kräver effektiv analys av kvantitativa data och modeller som med god träffsäkerhet kan förutse risker. Under 1900-talets andra hälft skedde en snabb utveckling av de verktyg som används för konkursprediktion, från enkla univariata modeller till komplexa data mining-modeller med tusentals observationer. Denna studie undersöker om det är möjligt att prediktera att svenska företag kommer att gå i konkurs och vilka variabler som innehåller relevant information för detta. Metoderna som används är diskriminantanalys, logistisk regression och överlevnadsanalys på 50 aktiva och 50 företag försatta i konkurs. Resultaten visar på en träffsäkerhet mellan 67,5 % och 75 % beroende på vald statistisk metod. Oavsett vald statistisk metod är det möjligt att klassificera företag som konkursmässiga två år innan konkursens inträffande med hjälp av finansiella nyckeltal av typerna lönsamhetsmått och solvensmått. Samhällskostnader reduceras av bättre konkursprediktion med hjälp av finansiella nyckeltal vilka bidrar till ökad förmåga för företag att tillämpa ekonomistyrning med relevanta nyckeltal i form av lager, balanserad vinst, nettoresultat och rörelseresultat. / From the early 1900s, banks and lending institutions have used financial ratios as an aid in the assessment and quantification of credit risk. For today's investors the economic environment is far more complicated than 40 years ago when the technology and computerization opened up the world's markets. Credit risk assessment today requires effective analysis of quantitative data and models that can predict risks with good accuracy. During the second half of the 20th century there was a rapid development of the tools used for bankruptcy prediction. We moved from simple univariate models to complex data mining models with thousands of observations. This study investigates if it’s possible to predict bankruptcy in Swedish limited companies and which variables contain information relevant for this cause. The methods used in the study are discriminant analysis, logistic regression and survival analysis on 50 active and 50 failed companies. The results indicate accuracy between 67.5 % and 75 % depending on the choice of statistical method. Regardless of the selected statistical method used, it’s possible to classify companies as bankrupt two years before the bankruptcy occurs using financial ratios which measures profitability and solvency. Societal costs are reduced by better bankruptcy prediction using financial ratios which contribute to increasing the ability of companies to apply financial management with relevant key ratios in the form of stock , retained earnings , net income and operating income.

Objective. Major depressive disorder (MDD) is a common condition following treatment in the Intensive Care Unit (ICU). Long-term data on MDD in chronically critically ill (CCI) patients are scarce. Hence, the primary aim of the present study was to investigate the frequency and predictors of MDD after intensive care of CCI patients. Materials and Methods. In a prospective cohort study, patients with long-term mechanical ventilation requirements () were assessed with respect to a diagnosis of MDD, using the Structured Clinical Interview for DSM-IV, three and six months after the transfer from acute ICU to post-acute ICU. Sociodemographic, psychological, and clinical risk factors with values ≤ 0.1 were identified in a univariate logistic regression analysis and entered in a multivariable logistic regression model. A mediator analysis was run using the bootstrapping method, testing the mediating effect of perceived helplessness during the ICU stay, between the recalled traumatic experience from the ICU and a post-ICU MDD. Results. 17.6% () of the patients showed a full- or subsyndromal MDD. Perceived helplessness, recalled experiences of a traumatic event from the ICU, symptoms of acute stress disorder, and the diagnosis of posttraumatic stress disorder (PTSD) after ICU could be identified as significant predictors of MDD. In a mediator analysis, perceived helplessness could be proved as a mediator. Conclusions. Every fifth CCI patient suffers from MDD up to six months after being discharged from ICU. Particularly, perceived helplessness during the ICU stay seems to mainly affect the long-term evolvement of MDD. CCI patients with symptoms of acute stress disorder/PTSD should also be screened for MDD.

Indiana University-Purdue University Indianapolis (IUPUI) / Epidemiologic studies suggest that depression is an independent risk factor for cardiovascular disease (CVD). Although several possible mediators of this association have been proposed, few studies have examined the role of moderators. Accordingly, I examined adverse childhood experiences (ACE) as a potential moderator of the depression-CVD association, given that individuals with a history of ACE show a greater inflammatory response to depression, and inflammation plays a role in the development of CVD. Data from Waves 1 and 2 of the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) were analyzed. Participants were 29,282 adults (58% female, 42% non–white) aged 18–97 years, free of CVD diagnoses at baseline. Lifetime depressive disorder (LDD) was assessed by the Alcohol Use Disorder and Associated Disabilities Interview Schedule–IV (AUDADIS–IV), and adverse childhood experiences (abuse, neglect, and household dysfunction), and CVD were assessed during separate interviews. The primary outcome was incident CVD (n = 1,255), defined as nonfatal arteriosclerosis, angina pectoris, myocardial infarction, and/or stroke reported during the Wave 2 interviews. All analyses were adjusted for demographic and traditional CVD risk factors. Logistic regression models revealed that both LDD (OR = 1.44, 95% CI: 1.28–1.62, p < .001) and any ACE (OR = 1.25, 95% CI: 1.16–1.35, p < .001) were independent predictors of incident CVD. Interactions between LDD x any ACE (p = .024), LDD x neglect (p = .003), and LDD x household dysfunction (p < .001), but not LDD x abuse (p = 0.16), were detected. Analyses stratified by the ACE variables revealed that LDD was a predictor of incident CVD among adults with a history of (1) any ACE (OR = 1.51, 95% CI: 1.32–1.73, p < .001), but not among those without a history (OR = 1.15, 95% CI: 0.87–1.50, p = .332); (2) neglect (OR = 1.59, 95% CI: 1.36–1.87, p < .001) and among those without a history (OR = 1.25, 95% CI: 1.07–1.62, p = .005); (3) household dysfunction (OR = 1.73, 95% CI: 1.46–2.04, p < .001), but not among those without a history (OR = 1.18, 95% CI: 0.96–1.43, p = .11). Overall, the present findings suggest that depression may be a stronger risk factor for CVD among adults with a history of ACE, especially neglect and household dysfunction, than among adults who did not have these experiences.

Introduction Colour codes are used extensively in railways to convey specific information governing movement of trains and equipment on the track. One such task is the railway traffic control display that uses colour coded video display terminals (VDTs) to convey information of the signal status, train movements and track status to the railway dispatcher. Because individuals with colour vision deficiencies (colour-defectives) may have problems with these colour-related tasks, questions were raised about the suitability of colour vision defectives to work as railway dispatchers. In order to answer that, a VDT based Dispatch Colour Vision Test based on the actual railway traffic display was developed previously. Purpose The main purpose of this thesis is to establish the pass/fail scores and repeatability of the VDT based Dispatch Colour Vision Test that resulted from the previous work. Secondly, the study will also examine whether clinical colour vision tests can predict the performance on the practical task. Methods The Dispatch colour vision test was divided into three parts based on the colour sets that the dispatcher had to recognize. The testing computer system used the the same RGB colour settings, graphics card and monitor as in railway dispatch centres. Subjects viewed the display colours and entered their responses by using a mouse. One hundred colour-normals and fifty two colour-defectives participated in the initial session. The test was repeated approximately after 10 days. Ninety three colour-normals (93%) and 44 (85%) colour-defectives participated in the second session. The total number of errors and time to complete the test was recorded. Results Pass/Fail on the VDT Dispatch colour vision test was based on colour-normal errors. Ignoring orange-red errors, two errors were allowed in the first session and one error was allowed in the second session. Based on this criterion, 42% of colour vision defectives could perform as well as colour normal subjects. The kappa coefficient of agreement between the sessions for the colour-defectives was 0.85. Detailed analysis between the colour differences and the errors showed only a weak correlation between the two. However, the general trend was that colour-defectives made more errors on colours that were near or along the same lines of confusions and the colours were nearly equal in luminance. Nevertheless, the interaction between luminance and location with respect to the lines of confusion was not easy to interpret. The time to complete the task for the colour-defectives who passed the test took 14% longer than colour-normals and colour-defectives who failed took 30% longer than colour-normals. All groups showed a similar learning effect with an 18% reduction in mean times to complete the task at the second session. There was no significant correlation between the number of errors and time to complete or the clinical tests and completion times for any of the groups. Clinical colour vision tests have limited value in predicting performance of colour-defectives on the Dispatch test. Logistic analysis results showed that the Farnsworth D-15 along with the Nagel was the best predictor of the VDT Dispatch colour test pass/fail results. However, these results were similar to using the Farnsworth D-15 test alone. Ninety-five percent of the individuals who failed the Farnsworth D-15 also failed the Dispatch test. However, approximately 25% of the individuals who passed the Farnsworth D-15 failed the VDT Dispatch colour test which is an unacceptable false negative rate. These results indicate the Farnsworth D-15 can only be used to predict who is likely to fail the dispatch test. Conclusions Forty two percent of colour vision defectives could perform as well as colour-normals in identifying VDT railway display colours and time to complete the task. Clinical colour vision tests were inadequate predictors of performance in practical task, overall. However, the Farnsworth D-15 was a very good predictor of who would fail the VDT Dispatch test. Hence a practical VDT Dispatch test may be needed to test individuals who would want to work as railway dispatchers.

Introduction Colour codes are used extensively in railways to convey specific information governing movement of trains and equipment on the track. One such task is the railway traffic control display that uses colour coded video display terminals (VDTs) to convey information of the signal status, train movements and track status to the railway dispatcher. Because individuals with colour vision deficiencies (colour-defectives) may have problems with these colour-related tasks, questions were raised about the suitability of colour vision defectives to work as railway dispatchers. In order to answer that, a VDT based Dispatch Colour Vision Test based on the actual railway traffic display was developed previously. Purpose The main purpose of this thesis is to establish the pass/fail scores and repeatability of the VDT based Dispatch Colour Vision Test that resulted from the previous work. Secondly, the study will also examine whether clinical colour vision tests can predict the performance on the practical task. Methods The Dispatch colour vision test was divided into three parts based on the colour sets that the dispatcher had to recognize. The testing computer system used the the same RGB colour settings, graphics card and monitor as in railway dispatch centres. Subjects viewed the display colours and entered their responses by using a mouse. One hundred colour-normals and fifty two colour-defectives participated in the initial session. The test was repeated approximately after 10 days. Ninety three colour-normals (93%) and 44 (85%) colour-defectives participated in the second session. The total number of errors and time to complete the test was recorded. Results Pass/Fail on the VDT Dispatch colour vision test was based on colour-normal errors. Ignoring orange-red errors, two errors were allowed in the first session and one error was allowed in the second session. Based on this criterion, 42% of colour vision defectives could perform as well as colour normal subjects. The kappa coefficient of agreement between the sessions for the colour-defectives was 0.85. Detailed analysis between the colour differences and the errors showed only a weak correlation between the two. However, the general trend was that colour-defectives made more errors on colours that were near or along the same lines of confusions and the colours were nearly equal in luminance. Nevertheless, the interaction between luminance and location with respect to the lines of confusion was not easy to interpret. The time to complete the task for the colour-defectives who passed the test took 14% longer than colour-normals and colour-defectives who failed took 30% longer than colour-normals. All groups showed a similar learning effect with an 18% reduction in mean times to complete the task at the second session. There was no significant correlation between the number of errors and time to complete or the clinical tests and completion times for any of the groups. Clinical colour vision tests have limited value in predicting performance of colour-defectives on the Dispatch test. Logistic analysis results showed that the Farnsworth D-15 along with the Nagel was the best predictor of the VDT Dispatch colour test pass/fail results. However, these results were similar to using the Farnsworth D-15 test alone. Ninety-five percent of the individuals who failed the Farnsworth D-15 also failed the Dispatch test. However, approximately 25% of the individuals who passed the Farnsworth D-15 failed the VDT Dispatch colour test which is an unacceptable false negative rate. These results indicate the Farnsworth D-15 can only be used to predict who is likely to fail the dispatch test. Conclusions Forty two percent of colour vision defectives could perform as well as colour-normals in identifying VDT railway display colours and time to complete the task. Clinical colour vision tests were inadequate predictors of performance in practical task, overall. However, the Farnsworth D-15 was a very good predictor of who would fail the VDT Dispatch test. Hence a practical VDT Dispatch test may be needed to test individuals who would want to work as railway dispatchers.

Indiana University-Purdue University Indianapolis (IUPUI) / Phytoestrogens that abound in soy products, legumes, and chickpeas can induce biologic responses in animals and humans due to structural similarity to 17β-estradiol. Although experimental studies suggest that phytoestrogen intake may alter the risk of cancer and cardiovascular disease, few epidemiologic studies have investigated this research question. This dissertation investigated the associations of intake of total and individual phytoestrogens and their urinary biomarkers with these chronic conditions using data previously collected from two US national cohort studies (NHANES and PLCO). Utilizing NHANES data with urinary phytoestrogen concentrations and follow-up mortality, Cox proportional hazards regression (HR; 95% CI) were performed to evaluate the association between total cancer, cardiovascular disease, and all-cause mortality and urinary phytoestrogens. After adjustment for confounders, it was found that higher concentrations of lignans were associated with a reduced risk of death from cardiovascular disease (0.48; 0.24-0.97), whereas higher concentrations of isoflavones (2.14; 1.03-4.47) and daidzein (2.05; 1.02-4.11) were associated with an increased risk. A reduction in all-cause mortality was observed for elevated concentrations of lignans (0.65; 0.43-0.96) and enterolactone (0.65; 0.44-0.97). Utilizing PLCO data and dietary phytoestrogens, Cox proportional hazards regression examined the associations between dietary phytoestrogens and the risk of prostate cancer incidence. After adjustment for confounders, a positive association was found between dietary intake of isoflavones (1.58; 1.11-2.24), genistein (1.42; 1.02-1.98), daidzein (1.62; 1.13-2.32), and glycitein (1.53; 1.09-2.15) and the risk of advanced prostate cancer. Conversely, an inverse association existed between dietary intake of genistein and the risk of non-advanced prostate cancer (0.88; 0.78-0.99) and total prostate cancer (0.90; 0.81-1.00). C-reactive protein (CRP) concentration levels rise in response to inflammation and higher levels are a risk factor for some cancers and cardiovascular disease reported in epidemiologic studies. Logistic regression performed on NHANES data evaluated the association between CRP and urinary phytoestrogen concentrations. Higher concentrations of total and individual phytoestrogens were associated with lower concentrations of CRP. In summary, dietary intake of some phytoestrogens significantly modulates prostate cancer risk and cardiovascular disease mortality. It is possible that these associations may be in part mediated through the influence of phytoestrogen intake on circulating levels of C-reactive protein.