Years of life lost due to premature deaths associated with air pollution: an ecological time-series study

ABSTRACT BACKGROUND: Exposure to air pollutants is associated with hospital admissions due to cardiovascular diseases and premature deaths. OBJECTIVE: To estimate years of life lost (YLL) due to premature deaths and their financial costs. DESIGN AND SETTING: Ecological time-series study carried out in São José dos Campos, Brazil, in 2016. METHODS: Data on deaths among residents of this city in 2016 were assessed to estimate the financial cost of premature deaths associated with air pollution. The diagnoses studied were ischemic heart disease, congestive heart failure and cerebrovascular disease, according to YLL. The fractions attributable to deaths associated with air pollutant exposure and to each potential year of life lost were calculated using negative binomial regression with lags of 0-7 days between exposure and outcome. Nitrogen dioxide, particulate matter (PM10) and ozone concentrations were included in the model and adjusted for temperature, humidity and seasonality. RESULTS: Exposure to particulate matter was significant at lag 3 days. There were 2177 hospitalizations over the study period, with 201 deaths (9.2%). Premature deaths led to 2035.69 years of life lost. A 10 μg/m3 increase in PM10 concentrations was correlated with 8.0% of the hospitalizations, which corresponded to 152.67 YLL (81.67 for males and 71.00 for females). The cost generated was approximately US$ 9.1 million in 2016. CONCLUSION: In this first study conducted in a medium-sized Brazilian city, using the YLL methodology, we identified an excess expense attributable to air pollution.

Years of life lost due to premature deaths associated with air pollution: an ecological time-series study.

BACKGROUND: Exposure to air pollutants is associated with hospital admissions due to cardiovascular diseases and premature deaths. OBJECTIVE: To estimate years of life lost (YLL) due to premature deaths and their financial costs. DESIGN AND SETTING: Ecological time-series study carried out in São José dos Campos, Brazil, in 2016. METHODS: Data on deaths among residents of this city in 2016 were assessed to estimate the financial cost of premature deaths associated with air pollution. The diagnoses studied were ischemic heart disease, congestive heart failure and cerebrovascular disease, according to YLL. The fractions attributable to deaths associated with air pollutant exposure and to each potential year of life lost were calculated using negative binomial regression with lags of 0-7 days between exposure and outcome. Nitrogen dioxide, particulate matter (PM10) and ozone concentrations were included in the model and adjusted for temperature, humidity and seasonality. RESULTS: Exposure to particulate matter was significant at lag 3 days. There were 2177 hospitalizations over the study period, with 201 deaths (9.2%). Premature deaths led to 2035.69 years of life lost. A 10 µg/m3 increase in PM10 concentrations was correlated with 8.0% of the hospitalizations, which corresponded to 152.67 YLL (81.67 for males and 71.00 for females). The cost generated was approximately US$ 9.1 million in 2016. CONCLUSION: In this first study conducted in a medium-sized Brazilian city, using the YLL methodology, we identified an excess expense attributable to air pollution.

Fuzzy logic and hospital admission due to respiratory diseases using estimated values by mathematical model.

Hospitalizations due to respiratory diseases generate financial costs for the Health System in addition to social costs. Objective of this study was to develop and validate a fuzzy linguistic model for prediction of hospitalization due to respiratory diseases. We constructed a fuzzy model for prediction of hospitalizations due to pneumonia, bronchitis, bronchiolitis and asthma second exposure to fine particulate matter (PM2.5) in residents of Volta Redonda, RJ, in 2012. The model contains two inputs, PM2.5 and temperature, with three membership functions for each input, and an output with three membership functions for admissions, which were obtained from DATASUS. There were 752 hospitalizations in the period, the average concentration of PM2.5 was 17.1 µg/m3 (SD = 4.4). The model showed a good accuracy with PM2.5, the result was between 90% and 76.5% for lags 1, 2 and 3, a sensitivity of up to 95%. This study provides support for creating executable software with a low investment, along with the use of a portable instrument could allow number of hospital admission due to respiratory diseases and provide support to local health managers. Furthermore, the fuzzy model is very simple and involves low computational costs, an implementation making possible.

Fuzzy logic and hospital admission due to respiratory diseases using estimated values by mathematical model / Lógica fuzzy e internações por doenças respiratórias usando dados estimados por modelo matemático

Abstract Hospitalizations due to respiratory diseases generate financial costs for the Health System in addition to social costs. Objective of this study was to develop and validate a fuzzy linguistic model for prediction of hospitalization due to respiratory diseases. We constructed a fuzzy model for prediction of hospitalizations due to pneumonia, bronchitis, bronchiolitis and asthma second exposure to fine particulate matter (PM2.5) in residents of Volta Redonda, RJ, in 2012. The model contains two inputs, PM2.5 and temperature, with three membership functions for each input, and an output with three membership functions for admissions, which were obtained from DATASUS. There were 752 hospitalizations in the period, the average concentration of PM2.5 was 17.1 µg/m3 (SD = 4.4). The model showed a good accuracy with PM2.5, the result was between 90% and 76.5% for lags 1, 2 and 3, a sensitivity of up to 95%. This study provides support for creating executable software with a low investment, along with the use of a portable instrument could allow number of hospital admission due to respiratory diseases and provide support to local health managers. Furthermore, the fuzzy model is very simple and involves low computational costs, an implementation making possible.

Resumo Internações por doenças respiratórias geram custos financeiros para o Sistema de Saúde além de custos sociais. O objetivo deste estudo foi elaborar e validar um modelo linguístico "fuzzy" para previsão do número de internações por doenças respiratórias. Foi construído um modelo "fuzzy" para predição de internações por pneumonias, bronquite, bronquiolite e asma segundo exposição ao material particulado fino (PM2,5) em residentes de Volta Redonda, RJ, em 2012. O modelo contém duas entradas PM2,5 e temperatura, com três funções de pertinência para cada entrada, e uma saída com três funções de pertinência para internações, que foram obtidas do DATASUS. Foram 752 internações no período, a concentração média do PM2,5 foi 17,1 µg/m3 (dp = 4,4). O modelo mostrou uma boa acurácia com PM2,5, o resultado foi entre 90% e 76,5% para os lags 1, 2 e 3, com sensibilidade de até 95%. Este estudo fornece subsídios para a criação de programa executável, que não exige um grande investimento, juntamente com o uso de um instrumento portátil pode permitir uma estimativa do número de internações e prestar apoio aos gestores municipais de saúde. Além disso, o modelo "fuzzy" é muito simples e implica em baixas despesas computacionais, tornando possível uma implementação.

Air pollution and respiratory diseases: ecological time series.

CONTEXT AND OBJECTIVE: Exposure to air pollutants is one of the factors responsible for hospitalizations due to respiratory diseases. The objective here was to estimate the effect of exposure to particulate matter (such as PM2.5) on hospitalizations due to certain respiratory diseases among residents in Volta Redonda (RJ). DESIGN AND SETTING: Ecological time series study using data from Volta Redonda (RJ). METHODS: Data on hospital admissions among residents of Volta Redonda (RJ), between January 1, 2012, and December 31, 2012, due to pneumonia, acute bronchitis, bronchiolitis and asthma, were analyzed. Daily data on PM2.5 concentrations were estimated through the CCATT-BRAMS model. The generalized additive Poisson regression model was used, taking the daily number of hospitalizations to be the dependent variable and the PM2.5 concentration to be the independent variable, with adjustment for temperature, relative humidity, seasonality and day of the week, and using lags of zero to seven days. Excess hospitalization and its cost were calculated in accordance with increases in PM2.5 concentration of 5 µg/m3. RESULTS: There were 752 hospitalizations in 2012; the average concentration of PM2.5 was 17.2 µg/m3; the effects of exposure were significant at lag 2 (RR = 1.017), lag 5 (RR = 1.022) and lag 7 (RR = 1,020). A decrease in PM2.5 concentration of 5 µg/m3 could reduce admissions by up to 76 cases, with a decrease in spending of R$ 84,000 a year. CONCLUSION: The findings from this study provide support for implementing public health policies in this municipality, which is an important steelmaking center.

Air pollution and respiratory diseases: ecological time series / Poluição do ar e doenças respiratórias: estudo ecológico de série temporal

ABSTRACT CONTEXT AND OBJECTIVE: Exposure to air pollutants is one of the factors responsible for hospitalizations due to respiratory diseases. The objective here was to estimate the effect of exposure to particulate matter (such as PM2.5) on hospitalizations due to certain respiratory diseases among residents in Volta Redonda (RJ). DESIGN AND SETTING: Ecological time series study using data from Volta Redonda (RJ). METHODS: Data on hospital admissions among residents of Volta Redonda (RJ), between January 1, 2012, and December 31, 2012, due to pneumonia, acute bronchitis, bronchiolitis and asthma, were analyzed. Daily data on PM2.5 concentrations were estimated through the CCATT-BRAMS model. The generalized additive Poisson regression model was used, taking the daily number of hospitalizations to be the dependent variable and the PM2.5 concentration to be the independent variable, with adjustment for temperature, relative humidity, seasonality and day of the week, and using lags of zero to seven days. Excess hospitalization and its cost were calculated in accordance with increases in PM2.5 concentration of 5 µg/m3. RESULTS: There were 752 hospitalizations in 2012; the average concentration of PM2.5 was 17.2 µg/m3; the effects of exposure were significant at lag 2 (RR = 1.017), lag 5 (RR = 1.022) and lag 7 (RR = 1,020). A decrease in PM2.5 concentration of 5 µg/m3 could reduce admissions by up to 76 cases, with a decrease in spending of R$ 84,000 a year. CONCLUSION: The findings from this study provide support for implementing public health policies in this municipality, which is an important steelmaking center.

RESUMO CONTEXTO E OBJETIVO: A exposição aos poluentes do ar é um dos fatores responsáveis por internações por doenças respiratórias; o objetivo foi estimar o efeito da exposição a material particulado (como PM2,5) sobre as hospitalizações devido a certas doenças respiratórias em moradores de Volta Redonda (RJ). TIPO DE ESTUDO E LOCAL: Estudo ecológico de séries temporais utilizando dados de Volta Redonda (RJ). MÉTODOS: Foram analisados dados de internação hospitalar, entre 1 de janeiro de 2012 e 31 de dezembro de 2012, devida a pneumonia, bronquite aguda, bronquiolite e asma, em residentes em Volta Redonda (RJ), e dados diários das concentrações de PM2,5 obtidos a partir do modelo CCATT-BRAMS. Utilizou-se o modelo aditivo generalizado de regressão de Poisson, sendo o número diário de internações a variável dependente e a concentração PM2,5 a variável independente, ajustado para temperatura, umidade relativa, sazonalidade e dia da semana e defasagens entre zero e sete dias. Excesso de internação hospitalar e seu custo, de acordo com o aumento de 5 ug/m3 na concentração de PM2,5, foram calculados. RESULTADOS: Ocorreram 752 internações em 2012; a concentração média de PM2,5 foi de 17,2 ug/m3; os efeitos da exposição foram significativos em lag 2 (RR = 1,017), lag 5 (RR = 1,022) e lag 7 (RR = 1,020). A redução em 5 ug/m3 na concentração de PM2,5 poderia reduzir até 76 casos as internações com diminuição nos gastos de R$ 84 mil/ano. CONCLUSÃO: Os achados deste estudo fornecem subsídios para implantar políticas públicas de saúde neste município, que é importante polo siderúrgico.

Air pollutants and hospital admissions due to cardiovascular diseases in São José do Rio Preto, Brazil.

This study aimed to estimate the effects of environmental pollutants on the increase of hospitalizations due to cardiovascular diseases. This was an ecological study conducted in the city of São José do Rio Preto, São Paulo, Brazil, with data from hospital admissions with diagnoses in the categories of I-00 to I-99, from October, 1, 2011, to September 30, 2012. Fineparticulate matter (PM2,5), ozone, carbon monoxide, nitrogen oxide and nitrogen dioxide were the pollutants studied; they were estimated by CATT-BRAMs model. The use of an additive Poisson regression model showed association between exposure to PM2,5 and hospital admission due to cardiovascular diseases. In the fifth day after exposure to this pollutant (lag 5), the relative risk for hospitalization due to cardiovascular diseases increased 15 percent in according to 10 µg/m3 increase on PM2,5 concentrations. There were 650 avoidable hospital admissions and an excess of R$ 1.9 million in hospital expenses. Thus, it was possible to identify the association between exposure to PM2,5 and hospital admission due cardiovascular diseases in medium-sized cities, like São José do Rio Preto.

Poluentes do ar e internações devido a doenças cardiovasculares em São José do Rio Preto, Brasil / Air pollutants and hospital admissions due to cardiovascular diseases in São José do Rio Preto, Brazil

Resumo O presente estudo teve como objetivo estimar os efeitos de poluentes ambientais sobre o número de internações por doenças cardiovasculares. Foi um estudo ecológico com dados de internações hospitalares de residentes em São José do Rio Preto, São Paulo, Brasil, com diagnóstico nas categorias de I-00 a I-99, entre 01/10/11 e 30/09/12. Os poluentes analisados foram partículas finas (PM2,5), ozônio, monóxido de carbono, óxido de nitrogênio e dióxido de nitrogênio. Foram estimados pelo modelo CCATT-BRAMS. O uso do modelo aditivo de regressão de Poisson foi utilizado para estimar associação entre a exposição ao PM2,5 e internação por doença cardiovascular. Foram calculados os excessos de internação e os gastos por estas doenças. Observou-se que a exposição ao PM2,5 no quinto dia após a exposição (lag 5) foi significativo para internação e aumentou em 15 ppts segundo incremento de 10µg /m3 na concentração de PM2,5. Foram identificadas 650 internações evitáveis com custos da ordem de R$ 1,9 milhão. Desse modo, foi possível identificar associação entre exposição ao PM2,5 e internações devido a doenças cardiovasculares em cidades de médio porte como São José do Rio Preto fornecendo subsídios aos gestores municipal e regional de Saúde.

Abstract This study aimed to estimate the effects of environmental pollutants on the increase of hospitalizations due to cardiovascular diseases. This was an ecological study conducted in the city of São José do Rio Preto, São Paulo, Brazil, with data from hospital admissions with diagnoses in the categories of I-00 to I-99, from October, 1, 2011, to September 30, 2012. Fineparticulate matter (PM2,5), ozone, carbon monoxide, nitrogen oxide and nitrogen dioxide were the pollutants studied; they were estimated by CATT-BRAMs model. The use of an additive Poisson regression model showed association between exposure to PM2,5 and hospital admission due to cardiovascular diseases. In the fifth day after exposure to this pollutant (lag 5), the relative risk for hospitalization due to cardiovascular diseases increased 15 percent in according to 10 µg/m3 increase on PM2,5 concentrations. There were 650 avoidable hospital admissions and an excess of R$ 1.9 million in hospital expenses. Thus, it was possible to identify the association between exposure to PM2,5 and hospital admission due cardiovascular diseases in medium-sized cities, like São José do Rio Preto.