Modelo de conjuntos fuzzy e de regressão logística para dados de obesidade

Obesidade e comumente definida como um excesso de gordura corporal, porém diante da dificuldade em mensurar tal gordura diretamente, esta tem sido definida como um excesso de peso mais do que um excesso de gordura corporal, que tem como desdobramento a ocorrência de doenças associadas e/ou prejuízos a saúde do indivíduo (4). Atualmente, o excesso de massa corpórea e verificado por meio de um Indice de Massa Corpórea (IMC), que considera o quociente entre o peso corporal (kg) e a estatura elevada ao quadrado (m2). Indivíduos com sobrepeso apresentam IMC de 25 at e 29; 9 kg=m2, e com obesidade apresentam IMC de 30 Kg=m2 ou mais, de acordo com a OMS (1). A identificação das causas da obesidade não é trivial e objetiva. Especialistas reconhecem que a obesidade e uma doença crônica, de difícil tratamento, denominada multifatorial, envolvendo em sua gênese diversos aspectos, entre eles: o consumo alimentar, aspectos ambientais, genéticos, psicossociais, entre outros. objetivo deste trabalho foi desenvolver um modelo baseado em teoria dos conjuntos Fuzzy para a classificação de obesidade levando em consideração as suas causas, e compará-lo com um modelo de regressão logística através da curva ROC. Para estudar as causas da obesidade na população de moradores da região do Distrito Sul de Campinas, foram coletados dados de uma amostra aleatória de 651 indivíuos, por meio de entrevista domiciliar. No primeiro estágio amostral, a partir do cadastro de domicílios residenciais dos agentes comunitários de saúde, foram aleatoriamente sorteados 920 domicílios (15% a mais do inicialmente previsto para cobrir perdas). Foram coletados dados de identificação geral, como: nome, idade, sexo, anos de escolaridade, tipo de ocupação e dados de consumo alimentar. O diagnóstico foi observado através do IMC. Num estudo preliminar, no modelo fuzzy foram consideradas como variáveis... (Resumo completo, clicar acesso eletrônico abaixo)

Fatores associados com a regressão da hipertrofia esquerda em diálise e impacto com mortalidade cardiovascular

Pós-graduação em Fisiopatologia em Clínica Médica - FMB

Institucionalização da velhice e regressão: um olhar psicanalítico sobre os asilos dos velhos

Even with several technologies, politics, laws and to knowledge that looks to secure the worthiest conditions of aging, the asylum of olds still marks presence in the contemporaneousness, like a sign of the aging badly succeeded. The present work is the result of practices carried out in institutions of long permanence and, among the effects of the institutionalization of the old age, the most attention was given here to the mechanism of the regression, analyzed through the light of the psychoanalysis.

A non-homogeneous poisson model with spatial anisotropy applied to ozone data from Mexico City

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Aplicação de modelos de regressão aleatória utilizando diferentes estruturas de dados

A total of 3.035 lactations of Holstein cows from four farms in the Southeast, to check the influence of data structure of milk yield on the genetic parameters. Four dataset with different structures were tested, weekly controls (CW) with 122.842 controls, monthly controls (CM) 30.883, bimonthly controls (CB) with 15,837 and quarterly controls (CQ) with 12,702. The random regression model was used and was considered as random additive genetic and permanent environment effects, fixed effects of the contemporary groups (herd-year-month of test-day) and age of cow (linear and quadratic effects). Heritability estimates showed similar trends among the data files analyzed, with the greatest similarity between dataset CS, CM and CB. The dataset submitted all the CB estimates of genetic parameters analyzed with the same trend and similar magnitude to the CS and CM dataset, allowing the claim that there was no influence of the data structure on estimates of covariance components for the dataset CS, CM and CB. Thus, milk recording could be accomplished in a CB structure.

A linguagem do consenso nos marcos da regressão cultural: o fim da consciência e a construção do neocontratualismo de Jürgen Habermas

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Doenças respiratórias e fatores associados: estudo de base populacional em São Paulo, 2008-2009

OBJETIVO: Estimar a prevalência de bronquite aguda, rinite e sinusite em crianças e adolescentes e identificar fatores associados. MÉTODOS: Estudo transversal, de base populacional. Foi realizado inquérito domiciliar com 1.185 crianças e adolescentes de São Paulo, SP, de 2008 a 2009. Os participantes foram selecionados a partir de amostragem probabilística, estratificada por sexo e idade e por conglomerados em dois estágios. Para análise ajustada foi realizada regressão múltipla de Poisson. RESULTADOS: Dos entrevistados, 7,3% referiram bronquite aguda, 22,6% rinite e 15,3% sinusite. Após análise ajustada, associaram-se à bronquite aguda auto-referida: idade de zero a quatro anos (RP = 17,86; IC95%: 3,65;90,91), cinco a nove anos (RP = 37,04; IC95%: 8,13;166,67), dez a 14 anos (RP = 20,83; IC95%: 4,93;90,91), referir ter alergia (RP = 3,12; IC95%: 1,70;5,73), cor da pele preta/parda (RP = 2,29; IC95%: 1,21;4,35) e morar em domicílio com um a três cômodos (RP = 1,85; IC95%: 1,17;2,94); à rinite auto-referida: idade dez a 14 anos (RP = 2,77; IC95%: 1,60;4,78), 15 a 19 anos (RP = 2,58; IC95%: 1,52;4,39), referir ter alergia (RP = 4,32; IC95%: 2,79;6,70), referir ter asma (RP = 2,30; IC95%: 1,30;4,10) e morar em apartamento (RP = 1,70; IC95%: 1,06;2,73); à sinusite auto-referida: idade cinco a nove anos (RP = 2,44; IC95%: 1,09;5,43), dez a 14 anos (RP = 2,99; IC95%: 1,36;6,58), 15 a 19 anos (RP = 3,62; IC95%: 1,68;7,81), referir ter alergia (RP = 2,23; IC95%: 1,41;3,52) e apresentar obesidade (RP = 4,42; IC95%: 1,56;12,50). CONCLUSÕES: As doenças respiratórias foram mais prevalentes em grupos populacionais com características definidas, como grupo etário, doenças auto-referidas, tipo de moradia e obesidade.

Aplicação da distribuição de poisson para determinação de estoque mínimo de itens de MRO de baixo giro aplicados em manutenção de ativos industriais

Pós-graduação em Engenharia de Produção - FEB

Dinâmica populacional, distribuição espacial e plano de amostragem sequencial de Euschistus heros (Fabricius, 1794) (Heteroptera: Pentatomidae) em cultivares de soja

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Avaliação das ações de alimentação e nutrição na atenção primária a saúde no estado de São Paulo

Pós-graduação em Alimentos e Nutrição - FCFAR

Previsão de demanda de veículos automotores através do modelo de regressão linear múltipla

This study aimed to model a equation for the demand of automobiles and light commercial vehicles, based on the data from February 2007 to July 2014, through a multiple regression analysis. The literature review consists of an information collection of the history of automotive industry, and it has contributed to the understanding of the current crisis that affects this market, which consequence was a large reduction in sales. The model developed was evaluated by a residual analysis and also was used an adhesion test - F test - with a significance level of 5%. In addition, a coefficient of determination (R2) of 0.8159 was determined, indicating that 81.59% of the demand for automobiles and light commercial vehicles can be explained by the regression variables: interest rate, unemployment rate, broad consumer price index (CPI), gross domestic product (GDP) and tax on industrialized products (IPI). Finally, other ten samples, from August 2014 to May 2015, were tested in the model in order to validate its forecasting quality. Finally, a Monte Carlo Simulation was run in order to obtain a distribution of probabilities of future demands. It was observed that the actual demand in the period after the sample was in the range that was most likely to occur, and that the GDP and the CPI are the variable that have the greatest influence on the developed model

Previsão de demanda de veículos automotores através do modelo de regressão linear múltipla

This study aimed to model a equation for the demand of automobiles and light commercial vehicles, based on the data from February 2007 to July 2014, through a multiple regression analysis. The literature review consists of an information collection of the history of automotive industry, and it has contributed to the understanding of the current crisis that affects this market, which consequence was a large reduction in sales. The model developed was evaluated by a residual analysis and also was used an adhesion test - F test - with a significance level of 5%. In addition, a coefficient of determination (R2) of 0.8159 was determined, indicating that 81.59% of the demand for automobiles and light commercial vehicles can be explained by the regression variables: interest rate, unemployment rate, broad consumer price index (CPI), gross domestic product (GDP) and tax on industrialized products (IPI). Finally, other ten samples, from August 2014 to May 2015, were tested in the model in order to validate its forecasting quality. Finally, a Monte Carlo Simulation was run in order to obtain a distribution of probabilities of future demands. It was observed that the actual demand in the period after the sample was in the range that was most likely to occur, and that the GDP and the CPI are the variable that have the greatest influence on the developed model

The exponential COM-Poisson distribution

The Conway-Maxwell Poisson (COMP) distribution as an extension of the Poisson distribution is a popular model for analyzing counting data. For the first time, we introduce a new three parameter distribution, so-called the exponential-Conway-Maxwell Poisson (ECOMP) distribution, that contains as sub-models the exponential-geometric and exponential-Poisson distributions proposed by Adamidis and Loukas (Stat Probab Lett 39:35-42, 1998) and KuAY (Comput Stat Data Anal 51:4497-4509, 2007), respectively. The new density function can be expressed as a mixture of exponential density functions. Expansions for moments, moment generating function and some statistical measures are provided. The density function of the order statistics can also be expressed as a mixture of exponential densities. We derive two formulae for the moments of order statistics. The elements of the observed information matrix are provided. Two applications illustrate the usefulness of the new distribution to analyze positive data.

Prevalence of asthma and risk factors associated: population based study in Sao Paulo, Southeastern Brazil, 2008-2009

OBJECTIVE: To assess the prevalence of asthma and risk factors associated in children and adolescents. METHODS: Population-based cross-sectional study with 1,185 female and male children and adolescents carried out in the city of Sao Paulo, Southeastern Brazil, from 2008 to 2009. Data were collected through home interviews. Respondents were selected from two-stage (census tract, household) cluster random sampling stratified by gender and age. Multiple Poisson regression was used in the adjusted analysis between the outcome and socioeconomic, demographic, lifestyle and health condition variables. RESULTS: Of all respondents, 9.1% (95%CI 7.0; 11.7) reported asthma. After adjustment, the following variables were found independently associated with asthma: age (0 to 4 years vs. 15 to 19) (PR 3.18, 95%CI 1.20;8.42); age (5 to 9 years vs. 15 to 19) (PR 6.37, 95%CI 2.64;15.39); age (10 to 14 years vs. 15 to 19) (PR 4.51,95%CI 1.95;10.40); allergy (yes vs. no) (PR 2.22, 95%CI 1.24;4.00); rhinitis (yes vs. no) (PR 2.13, 95%CI 1.22;3.73); health conditions in the 15 days preceding the interview (yes vs. no) (PR 1.96, 95%CI 1.23;3.11); number of rooms in the household (1 to 3 vs. 4 and more) (PR 1.67, 95%CI 1.05;2.66); and skin color (black and mixed vs. white) (PR 2.00, 95%CI 1.14;3.49). CONCLUSIONS: This study showed the importance of factors associated with asthma including rhinitis and allergy; age between 5 to 9 years old; black and mixed skin color; and household with few rooms. Frequent health problems are seen as a common consequence of asthma.

A Bayesian analysis of the Conway-Maxwell-Poisson cure rate model

The purpose of this paper is to develop a Bayesian analysis for the right-censored survival data when immune or cured individuals may be present in the population from which the data is taken. In our approach the number of competing causes of the event of interest follows the Conway-Maxwell-Poisson distribution which generalizes the Poisson distribution. Markov chain Monte Carlo (MCMC) methods are used to develop a Bayesian procedure for the proposed model. Also, some discussions on the model selection and an illustration with a real data set are considered.