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Submitted by Ana Maria Fiscina Sampaio (fiscina@bahia.fiocruz.br) on 2014-09-18T14:01:56Z No. of bitstreams: 1 Ciro Oliveira Queiroz Padrões de atividades... 2013.pdf: 1277176 bytes, checksum: a198eee940e5fba7bc389f439dc5b358 (MD5) / Made available in DSpace on 2014-09-18T14:01:56Z (GMT). No. of bitstreams: 1 Ciro Oliveira Queiroz Padrões de atividades... 2013.pdf: 1277176 bytes, checksum: a198eee940e5fba7bc389f439dc5b358 (MD5) Previous issue date: 2013 / Fundação Oswaldo Cruz. Centro de Pesquisa Gonçalo Moniz. Salvador, BA, Brasil / Introdução: A proteína C reativa (PCR) é um biomarcador conhecido da inflamação sistêmica e está associado à predição de doenças cardiovasculares. A atividade física regular tem muitos benefícios, uma vez que reduz o risco do desenvolvimento de diversas doenças crônicas, incluindo as doenças cardiovasculares. Alguns estudos tem mostrado que a atividade física pode estar inversamente associada aos níveis de PCR, entretanto, ainda não se tem um consenso sobre a quantidade de atividade física necessária para manter os níveis de PCR normais. Objetivo: identificar o poder discriminatório e a quantidade de atividade física necessária para discriminar níveis de PCR em adultos. Métodos: estudo transversal com amostra de 14.250 adultos de 35 a 74 anos de idade, participantes do Estudo Longitudinal de Saúde do Adulto. Foram construídas curvas Receiver Operating Characteristic (ROC) para identificar o poder preditivo e os pontos de corte da quantidade de atividade física em dois domínios (tempo livre e deslocamento) e níveis de PCR. Para testar as diferenças entre as áreas sob a curva ROC utilizou-se o teste qui-quadrado considerando-se 5% de nível de significância estatística. Verificou-se a sensibilidade e especificidade para identificar os melhores pontos de corte de atividade física necessários para manter níveis normais de PCR (<3mg/L). Resultados: a maior parte dos participantes tem nível superior completo (53,1%), são da cor branca (52,4%) e tem sobrepeso (40,7%). Com relação a PCR, um quarto da amostra se encontra com níveis elevados (25,2%) e quando comparado por sexo, as mulheres apresentam uma maior proporção. Quando se avaliou a quantidade de atividade física realizada por semana, 57,5% dos participantes do estudo não praticavam no mínimo 10 minutos de atividade física no tempo livre. Encontrou-se significância estatística das áreas sob a curva ROC na soma dos dois domínios investigados e no domínio do tempo livre isoladamente. A atividade física acumulada nos dois domínios durante 200 minutos/semana apresentou o melhor equilíbrio para discriminar os níveis normais de PCR em adultos de ambos os sexos. Conclusão: a prática de atividade física combinada nos domínios do tempo livre e deslocamento podem contribuir para manter os níveis de PCR normais. Esses achados podem contribuir também para a construção de políticas públicas em relação à promoção da atividade física e da saúde. / Background: C-reactive protein (CRP) is a known biomarker of systemic inflammation and is associated with the prediction of cardiovascular disease. Regular physical activity has many benefits, as it reduces the risk of developing several chronic diseases, including cardiovascular disease. Some studies have shown that physical activity may be inversely associated with levels of CRP, however, there isn’t still consensus on the amount of physical activity required to maintain levels of CRP normal. Purpose: Identify the discriminatory power and amount of physical activity required to discriminate levels of CRP in adults. Methods: Cross-sectional study with a sample of 14.250 adults age 35 to 74 years, participating in the Brazilian Longitudinal Study of Adult Health. Receiver Operating Characteristic (ROC) curves was constructed to identify the predictive power and the cutoff of physical activity in two domains (leisure time and displacement) and levels of CRP. To test the differences between the areas under the ROC curve was used the chi-square test considering a 5% significance level. Sensitivity and specificity were observed to identify the best cut-off of physical activity to keep normal levels CRP (<3mg/L). Results: The most participants have completed college (53.1%) are white (52.4%) and is overweight (40.7%). With respect to CRP, a quarter of participants meets high levels (25.2%) and compared by sex, women have a higher proportion. When assessing the amount of physical activity per week, 57.5% of study participants did not practice at least 10 minutes of physical activity during leisure time It was found a statistical significance of the areas under the ROC curve of the sum of the two domains investigated and in the leisure time alone. Physical activity accumulated in the two domains during 200 minutes/week showed the best balance for discriminating normal levels of CRP in adults of both sexes. Conclusion: The physical activity combined in the domains of leisure time and displacement may contribute to keep the levels of CRP normal. These findings may also contribute to the development of public policies regarding promotion of physical activity and health.

The aim of this thesis is comparison of selected classification methods which are logistic regression (binary and multinominal), multilayer perceptron and classification trees, CHAID and CRT. The first part is reminiscent of the theoretical basis of these methods and explains the nature of parameters of the models. The next section applies the above classification methods to the six data sets and then compares the outputs of these methods. Particular emphasis is placed on the discriminatory power rating models, which a separate chapter is devoted to. Rating discriminatory power of the model is based on the overall accuracy, F-measure and size of the area under the ROC curve. The benefit of this work is not only a comparison of selected classification methods based on statistical models evaluating discriminatory power, but also an overview of the strengths and weaknesses of each method.

The growing need for fast sampling of explosives in high throughput areas has increased the demand for improved technology for the trace detection of illicit compounds. Detection of the volatiles associated with the presence of the illicit compounds offer a different approach for sensitive trace detection of these compounds without increasing the false positive alarm rate. This study evaluated the performance of non-contact sampling and detection systems using statistical analysis through the construction of Receiver Operating Characteristic (ROC) curves in real-world scenarios for the detection of volatiles in the headspace of smokeless powder, used as the model system for generalizing explosives detection. A novel sorbent coated disk coined planar solid phase microextraction (PSPME) was previously used for rapid, non-contact sampling of the headspace containers. The limits of detection for the PSPME coupled to IMS detection was determined to be 0.5-24 ng for vapor sampling of volatile chemical compounds associated with illicit compounds and demonstrated an extraction efficiency of three times greater than other commercially available substrates, retaining >50% of the analyte after 30 minutes sampling of an analyte spike in comparison to a non-detect for the unmodified filters. Both static and dynamic PSPME sampling was used coupled with two ion mobility spectrometer (IMS) detection systems in which 10-500 mg quantities of smokeless powders were detected within 5-10 minutes of static sampling and 1 minute of dynamic sampling time in 1-45 L closed systems, resulting in faster sampling and analysis times in comparison to conventional solid phase microextraction-gas chromatography-mass spectrometry (SPME-GC-MS) analysis. Similar real-world scenarios were sampled in low and high clutter environments with zero false positive rates. Excellent PSPME-IMS detection of the volatile analytes were visualized from the ROC curves, resulting with areas under the curves (AUC) of 0.85-1.0 and 0.81-1.0 for portable and bench-top IMS systems, respectively. Construction of ROC curves were also developed for SPME-GC-MS resulting with AUC of 0.95-1.0, comparable with PSPME-IMS detection. The PSPME-IMS technique provides less false positive results for non-contact vapor sampling, cutting the cost and providing an effective sampling and detection needed in high-throughput scenarios, resulting in similar performance in comparison to well-established techniques with the added advantage of fast detection in the field.