Método de regressão de Poisson: metodologia para avaliação do impacto da poluição atmosférica na saúde populacional

Tadano, Yara de Souza; Ugaya, Cássia Maria Lie; Franco, A.

doi:10.1590/s1414-753x2009000200003

Cited by 32 publications

(24 citation statements)

References 3 publications

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“…The multivariate data analysis was conducted using the Poisson multiple regression analysis, to predict the response variable from a combination of explanatory variables, which should be non-negative and a count data, considering the total number of individuals with the disease or condition in a specific period of time. (12) For the analysis, a significance level of 5% was adopted.…”

Section: Methodsmentioning

confidence: 99%

Fatores de risco para infecção de corrente sanguínea associada ao cateter central de inserção periférica em neonatos

et al. 2016

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Objective: To identify the risk factors for bloodstream infection associated with peripherally inserted central catheters in neonates. Methods: A prospective cohort study conducted in the neonatal intensive care unit with newborns undergoing insertion of 401 peripherally inserted central catheters. Clinical characteristics of the newborn, catheter insertion technique, intravenous therapy and catheter dwell time were tested as risk factors for removal due to catheter associated bloodstream infection, using bivariate analysis and multivariate analysis with Poisson regression. Results: The data suggest that the lowest mean in weight and corrected gestational age, as well as the largest catheter dwell time time were associated with the occurrence of bloodstream infection associated with the catheters. The corrected gestational age, clinical diagnosis of transitional metabolic disorder or apnea, and the use of two-lumen catheters have been identified as risk factors. Conclusion: The lowest correct gestational age of the newborn, the clinical diagnosis of metabolic disorder or apnea, and the use of two-lumen catheters were identified as risk factors for bloodstream infection associated with peripherally inserted central catheters in neonates. ResumoObjetivo: Identificar os fatores de risco para infecção de corrente sanguínea associada ao cateter central de inserção periférica em neonatos. Métodos: Estudo de coorte prospectivo conduzido em unidade de terapia intensiva com recém-nascidos submetidos à instalação de 401 cateteres centrais de inserção periférica. Características clínicas do neonato, técnica de inserção do cateter, terapia intravenosa e tempo de permanência do cateter foram testados como fatores de risco para remoção por infecção de corrente sanguínea associada ao cateter, por meio de análise bivariada e análise multivariada com regressão de Poisson. Resultados: Os dados sugerem que as menores médias de peso e idade gestacional corrigida, bem como o maior tempo de permanência do cateter estiveram associados à ocorrência de infecção de corrente sanguínea associada ao cateter. A menor idade gestacional corrigida, os diagnósticos clínicos de transtorno transitório do metabolismo e apneia, e o uso do cateter de duas vias foram identificados como fatores de risco. Conclusão: A menor idade gestacional corrigida do neonato, os diagnósticos clínicos de transtorno transitório do metabolismo e apneia, e o uso do cateter de duas vias foram identificados como fatores de risco para infecção de corrente sanguínea associada ao cateter central de inserção periférica em neonatos.

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Section: Methodsmentioning

confidence: 99%

Fatores de risco para infecção de corrente sanguínea associada ao cateter central de inserção periférica em neonatos

et al. 2016

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“…These results agree with others studies, such as that of Angelici et al 16 , which demonstrated a positive relation between PM 10 and MS admissions in Lombardy, Italy, and that of Gregory et al 3 , which showed a positive relation between PM 10 and female patient admissions. o Adjustments of the multiple linear regression model with the stepwise method Before the development of multiple linear regression, residual analysis was performed to verify the adjustment of hospitalization data and PM 10 to the model, since residuals should follow a normal distribution for the model 11,17,24 . The independent temperature and humidity variables were also added to improve predictability.…”

Section: Resultsmentioning

confidence: 99%

“…The data available in this system involve the number of admissions by city, age, and gender. Although studies on the impact of pollution on population health recommend that daily values of meteorological variables should be used and that hospital admissions should be divided by age group 11 , in this work the average monthly admissions were used, since MS has low prevalence in Brazil, with 15 cases per 100,000 inhabitants 12 . o Statistical analysis…”

Section: Materials and Methods O Meteorological Datamentioning

confidence: 99%

“…Although many studies that correlate air pollution and meteorological variables with diseases use the Poisson family of generalized linear models (MLG), in this study we used multiple linear regression 3,16,17 . This model was chosen because the variables have a normal distribution and, according to the residue analysis, the model was adequate for our data 11,13,17 . The objective of regression analysis is to measure the relation between an answer variable (Y) and a set of independent explanatory variables (X1, X2,...), as shown in equation 1 18 .…”

Section: Materials and Methods O Meteorological Datamentioning

confidence: 99%

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Influence of particulate matter and meteorological conditions on multiple sclerosis relapse: a preliminary study in São Paulo, Brazil

Diniz¹,

Frony-Macedo²,

Piacenti-Silva³

2017

Arch Health Invest

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Introduction: Multiple sclerosis (MS) is a chronic, inflammatory, and demyelinating disease of the central nervous system, which in some cases may be characterized by recurrent relapses of inflammation that cause mild to severe neurological disability. Some studies around the world have associated the increase of systemic inflammatory responses and neuro-inflammation of patients with exposure to high levels of particulate matter (PM 10 ) and certain conditions of temperature and humidity. Materials and methods: The objective of this study was to verify the influence of the concentration of PM 10 and meteorological variables (air temperature and relative humidity) on the number of hospitalizations for MS in the city of São Paulo. Data from 2008 to 2016, which passed through descriptive statistics and inferences, were used as multiple linear regression models. Results: The models obtained indicated a positive relation (p < 0.01) in the number of hospitalizations with the increase of PM 10 and relative humidity, showing that 31.23% of hospital admissions can be explained by these variables. Conclusion: These results are important, since there are no other studies from Brazil that correlate meteorological and air quality variables with MS. Descriptors: Air Pollution; Multiple Sclerosis; Linear Models. ResumoIntrodução: A Esclerose Múltipla (EM) é uma doença crônica, inflamatória e desmielinizante do sistema nervoso central, que em alguns casos pode ser caracterizada por surtos recorrentes de inflamação que causam leve a grave deficiência neurológica. Alguns estudos em todo o mundo têm associado o aumento de respostas inflamatórias sistêmicas e neuroinflamação de pacientes quando expostos a altos níveis de material particulado (MP 10 ) e certas condições de temperatura e umidade. Material e Método: O objetivo deste estudo foi verificar a influência da concentração de material particulado (MP 10 ) e das variáveis meteorológicas (temperatura do ar e umidade relativa) sobre o número de internações por EM na cidade de São Paulo. Para isso foram utilizados dados destas no período de 2008 a 2016, os quais passaram por estatísticas descritivas e inferencias, como modelos de regressão linear múltipla. Resultados: Os modelos obtidos indicaram relação positiva (p <0,01) no número de internações com o aumento do material particulado MP 10 e umidade relativa, demonstrando que 31,23% das internações hospitalares podem ser explicadas por essas variáveis. Conclusão: Esses resultados são importantes, pois até agora, em nosso conhecimento, no Brasil não existem estudos que correlacionem as variáveis meteorológicas e de qualidade do ar com a Esclerose Múltipla. Descritores: Poluição do Ar; Esclerose Múltipla; Modelos Lineares. ResumenIntroducción: La esclerosis múltiple (EM) es una enfermedad del sistema crónica, inflamatoria y desmielinizante nervioso central, que en algunos casos puede ser caracterizada mediante recaídas recurrentes de inflamación causando leve a déficit neurológico grave. Algunos estudios de todo el mundo q...

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“…Subsequently, generalized linear models were performed using the Poisson multiple regression model. (17) In order to construct the models climate variables that showed p values < 0.25 in univariate Poisson regression model were selected, which were then used in Poisson multiple regression model by the following equation:…”

Section: Methodsmentioning

confidence: 99%

Potenciais impactos da variabilidade climática sobre a morbidade respiratória em crianças, lactentes e adultos

et al. 2012

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Objective: To determine whether climate variability influences the number of hospitalizations for respiratory diseases in infants, children, and adults in the city of Campo Grande, Brazil. Methods: We used daily data on admissions for respiratory diseases, precipitation, air temperature, humidity, and wind speed for the 2004-2008 period. We calculated the thermal comfort index, effective temperature, and effective temperature with wind speed (wind-chill or heat index) using the meteorological data obtained. Generalized linear models, with Poisson multiple regression, were used in order to predict hospitalizations for respiratory disease. Results: The variables studied were (collectively) found to show relatively high correlation coefficients in relation to hospital admission for pneumonia in children (R 2 = 68.4%), infants (R 2 = 71.8%), and adults (R 2 = 81.8%). Conclusions: Our results indicate a quantitative risk for an increase in the number of hospitalizations of children, infants, and adults, according to the increase or decrease in temperature, humidity, precipitation, wind speed, and thermal comfort index in the city under study. Keywords

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Método de regressão de Poisson: metodologia para avaliação do impacto da poluição atmosférica na saúde populacional

Cited by 32 publications

References 3 publications

Fatores de risco para infecção de corrente sanguínea associada ao cateter central de inserção periférica em neonatos

Fatores de risco para infecção de corrente sanguínea associada ao cateter central de inserção periférica em neonatos

Influence of particulate matter and meteorological conditions on multiple sclerosis relapse: a preliminary study in São Paulo, Brazil

Potenciais impactos da variabilidade climática sobre a morbidade respiratória em crianças, lactentes e adultos

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