Climate changes and their effects in the public health: use of poisson regression models

CNPQ - CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICOCAPES - COORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL E NÍVEL SUPERIORFAPESP - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULOIn this paper, we analyze the daily number of hospitalizations in São Paulo City, Brazil, in the period of January 01, 2002 to December 31, 2005. This data set relates to pneumonia, coronary ischemic diseases, diabetes and chronic diseases in different age categories. In order to verify the effect of climate changes the following covariates are considered: atmosphere pressure, air humidity, temperature, year season and also a covariate related to the week day when the hospitalization occurred. The possible effects of the assumed covariates in the number of hospitalization are studied using a Poisson regression model in the presence or not of a random effect which captures the possible correlation among the hospitalization accounting for the different age categories in the same day and the extra-Poisson variability for the longitudinal data. The inferences of interest are obtained using the Bayesian paradigm and MCMC (Markov chain Monte Carlo) methods.Neste artigo, analisamos os dados relativos aos números diários de hospitalizações na cidade de São Paulo, Brasil no período de 01/01/2002 a 31/12/2005 devido a pneumonia, doenças isquêmicas, diabetes e doenças crônicas e de acordo com a faixa etária. Com o objetivo de estudar o efeito de mudanças climáticas são consideradas algumas covariáveis climáticas os índices diários de pressão atmosférica, umidade do ar, temperatura e estação do ano, e uma covariável relacionada ao dia da semana da ocorrência de hospitalização. Para verificar os efeitos das covariáveis nas respostas dadas pelo numero de hospitalizações, consideramos um modelo de regressão de Poisson na presença ou não de um efeito aleatório que captura a possível correlação entre as contagens para as faixas etárias de um mesmo dia e a variabilidade extra-poisson para os dados longitudinais. As inferências de interesse são obtidas usando o paradigma bayesiano e métodos de simulação MCMC (Monte Carlo em Cadeias de Markov).In this paper, we analyze the daily number of hospitalizations in São Paulo City, Brazil, in the period of January 01, 2002 to December 31, 2005. This data set relates to pneumonia, coronary ischemic diseases, diabetes and chronic diseases in different age categories. In order to verify the effect of climate changes the following covariates are considered: atmosphere pressure, air humidity, temperature, year season and also a covariate related to the week day when the hospitalization occurred. The possible effects of the assumed covariates in the number of hospitalization are studied using a Poisson regression model in the presence or not of a random effect which captures the possible correlation among the hospitalization accounting for the different age categories in the same day and the extra-Poisson variability for the longitudinal data. The inferences of interest are obtained using the Bayesian paradigm and MCMC (Markov chain Monte Carlo) methods.302427442CNPQ - CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICOCAPES - COORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL E NÍVEL SUPERIORFAPESP - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULOCNPQ - CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICOCAPES - COORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL E NÍVEL SUPERIORFAPESP - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULOsem informaçãosem informaçãosem informaçãoNeste artigo, analisamos os dados relativos aos números diários de hospitalizações na cidade de São Paulo, Brasil no período de 01/01/2002 a 31/12/2005 devido a pneumonia, doenças isquêmicas, diabetes e doenças crônicas e de acordo com a faixa etária. Com o objetivo de estudar o efeito de mudanças climáticas são consideradas algumas covariáveis climáticas os índices diários de pressão atmosférica, umidade do ar, temperatura e estação do ano, e uma covariável relacionada ao dia da semana da ocorrência de hospitalização. Para verificar os efeitos das covariáveis nas respostas dadas pelo numero de hospitalizações, consideramos um modelo de regressão de Poisson na presença ou não de um efeito aleatório que captura a possível correlação entre as contagens para as faixas etárias de um mesmo dia e a variabilidade extra-poisson para os dados longitudinais. As inferências de interesse são obtidas usando o paradigma bayesiano e métodos de simulação MCMC (Monte Carlo em Cadeias de Markov)

Survival time among patients who were diagnosed with tuberculosis, the precocious deaths and associated factors in southern Brazil

Background: A diagnosis of tuberculosis (TB) does not mean that the disease will be treated successfully, since death may occur even among those who are known to the health services. Here, we aimed to analyze patient survival time from the diagnosis of TB to death, precocious deaths, and associated factors in southern Brazil. Methods: We conducted a longitudinal study with patients who were diagnosed with TB and who died due to the disease between 2008 and 2015 in southern Brazil. The starting point for measuring survival time was the patient’s diagnosis date. Techniques for survival analysis were employed, including the Kaplan-Meier test and Cox’s regression. A mixed-effect model was applied for identifying the associated factors to precocious deaths. Hazard ratio (HR) and odds ratio (OR) with 95% confidence intervals (95% CI) were estimated. We defined p value <0.05 as statistically significant for all statistics applied. Results: One hundred forty-six patients were included in the survival analysis, observing a median survival time of 23.5 days. We observed that alcoholism (HR=1.55, 95% CI=1.04-2.30) and being male (HR=6.49, 95% CI=1.03-2.68) were associated with death. The chance of precocious death within 60 days was 10.48 times greater than the chance of early death within 30 days. Conclusion: Most of the deaths occurred within 2 months after the diagnosis, during the intensive phase of the treatment. The use of alcohol and gender were associated with death, revealing inequality between men and women. This study advanced knowledge regarding the vulnerability associated with mortality. These findings must be addressed to fill a gap in the care cascades for active TB and ensure equity in health.publishersversionpublishe

Psychometric assessment of the nursing outcome swallowing status : rasch model approach

To apply the Rasch model to test the psychometric assessment of the nursing outcome Swallowing status among poststroke patients. Cross‐sectional study was conducted with 227 poststroke patients, which were evaluated by a nurse. The Rasch model was used to examine psychometric properties. Indicators fit the Rasch model and presented good reliability and good ability for separation index. The 5‐point Likert scale did not present adequate discrimination and classification levels were compiled into three. Data evidenced the use of a robust method to perform a clinical validity of the Swallowing status, complementing previous validation studies. Using Rasch analysis serve as reference points to assess Swallowing status on a single scale304197202CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO - CNPQ501511/2013‐0Aplicar o modelo Rasch para testar as medidas psicométricas do resultado de enfermagem Estado da deglutição em pacientes acometidos por acidente vascular cerebral. Estudo transversal, realizado com 227 pacientes após AVC avaliados por um único enfermeiro. O modelo Rasch foi usado para examinar propriedades psicométricas. Os indicadores se ajustaram ao modelo Rasch e apresentam boa confiabilidade e boa capacidade de separação. A escala Likert de 5 pontos não apresentou discriminação adequada e os níveis de classificação foram compilados em três pontos. Os dados evidenciaram o uso de um método robusto para a validade clínica do Estado da deglutição, complementando os estudos de validação anteriores. O uso do modelo Rasch serve como ponto de referência para avaliar o Estado da deglutição em uma única escalaThis research was made possible by Grant Number 501511/2013‐0 from the National Council for Scientific and Technological Development (CNPq) for postdoctoral research of the principal author. The postdoctoral research was developed at Ribeirão Preto College of Nursing, University of São Paul

Acquired and Transmitted Multidrug-Resistant Tuberculosis among the Incarcerated Population and Its Determinants in the State of Paran&aacute;&mdash;Brazil

(1) Background: Tuberculosis remains a public health problem in the world. The study analyzed the factors associated with drug-resistant tuberculosis in the prison population of the state of Paran&aacute;. (2) Methods: Ecological study of drug-resistant tuberculosis cases registered in the Paran&aacute; Information System, Brazil (2008 to 2018). We performed descriptive statistics of quantitative parameters calculated with absolute frequencies. Additionally, we used binary regression logistics, where the odds ratio with its respective confidence interval was calculated. (3) Results: Of the 653 cases registered as cases of tuberculosis in the incarcerated population, 98 were drug-resistant tuberculosis. We observed that educational level of up to 8 to 11 years of schooling, negative bacterial culture (test outcome) and no tobacco use were factors associated with the non-development of drug-resistant tuberculosis, while clinically confirmed pulmonary TB and positive sputum smear microscopy in the fourth month of follow-up showed an association for the development of drug resistance. (4) Conclusions: The study showed that clinically confirmed pulmonary TB and a positive sputum smear microscopy in the fourth month of follow-up were associated with drug-resistant tuberculosis