Resumos

INTRODUCTION

Burning biomass releases carbon gaseous compounds particulates. In its final stage, products of incomplete combustion are released, such as organic particles, among them particulate material, which is the most associated with health problems. Fine particulate material has diameters ranging from 0.1 µm to smaller than 2.5 µm (PM_2.5) and represents between 60% and 70% of total particulate material.⁶6. Donaldson K, Stone V, Clouter A, MacNee W. Ultrafine particles. Occup Environ Med. 2001;58(3):211-6. DOI:http://dx.doi.org/10.1136/oem.58.3.211
http://dx.doi.org/10.1136/oem.58.3.211...

The groups most susceptible to the harmful effects of atmospheric pollution are children, the elderly and those with a history of respiratory (RD) and cardiovascular disease. Respiratory disease in children, especially acute respiratory infections, asthma and bronchitis are related to high levels of air pollution and are a common cause of mortality.^aa Organización Panamericana de la Salud. Evaluación de los efectos de la contaminación del aire en la salud de América. Latina y el Caribe. Washington (DC); 2005. Respiratory disease is still the main cause of hospital admission among the elderly. Susceptibility to atmospheric pollution in this age group may be exacerbated by physical debility, low physiological resilience and respiratory disease or other prevalent diseases.^bb Dawud Y. Smoke episodes and assessment of health impacts related to haze from forest fires: Indonesian experience health guidelines for vegetation fire events, Lima, Peru. Lima: World Health Organization; 1999.

The principal characteristic of air pollution originating from burning biomass is its well defined seasonality, with high levels of smoke produced in short, restricted periods, varying between three and six months.^cc Carmo CN, Hacon S, Longo KM, Freitas S, Mourão D, Louzano F, et al. Queima de biomassa e doenças respiratórias na região amazônica: uma aplicação de modelos aditivos generalizados. XLI Simpósio Brasileiro de Pesquisa Operacional 2009 - Pesquisa Operacional na Gestão do Conhecimento. Bahia, BR. Bahia: SOBRAPO; 2009. p.1472-77. These peaks often occur during the dry season between June and November.

Brazil contributes a significant part of the global atmospheric pollutants due to burning biomass. The Amazon region is the most critical region in the country. The pattern of atmospheric circulation means that emissions from the Amazon rainforest are dispersed toward the Northeast and North of the South America continent, over the tropical Pacific Ocean and the South Atlantic, reaching as far as the Caribbean region. ⁷ 7. Freitas SR, Longo KM, Dias MAFS, Chatfield R, Dias PLS, Artaxo P, et al. The coupled aerosol and tracer transport model to the Brazilian developments on the Regional Atmospheric Modeling System (CATT-BRAMS). Part 1: model description and evaluation. Atmos Chem Phys Discuss. 2007;7(3):8525-69. DOI: http://dx.doi.org/10.5194/acpd-7-8525-2007
http://dx.doi.org/10.5194/acpd-7-8525-20... Smoke from biomass burning in the Mato Grosso state of the Amazon, in the north and northeast of the state, moves toward the other municipalities of the south and central regions of the state. In addition to the effects of burning on the Amazon ecosystem, the pollutant emissions contribute to increased respiratory morbidity in municipalities in the Amazonian deforestation arc. ⁸ 8. Ignotti E, Hacon S, Silva AMC, Junger WL, Castro HA. Efeitos das queimadas na Amazônia: método de seleção de municípios segundo indicadores de saúde. Rev Bras Epidemiol. 2007;10(4):453-64. DOI:http://dx.doi.org/10.1590/S1415-790X2007000400003
http://dx.doi.org/10.1590/S1415-790X2007...

Global concerns about climate change and the large scale deforestation have awakened interest in controlling the biomass burning in South America. Although evidence exists demonstrating the risks posed by smoke from burning tropical forests on the health of the exposed population groups, the few epidemiological studies which have been carried out in this region are very recent. ¹⁰ 10. Rodrigues PCO, Ignotti E, Rosa AM, Hacon SS. Distribuição espacial das internações por asma em idosos na Amazônia Brasileira. Rev Bras Epidemiol. 2010;13(3):523-32. DOI: http://dx.doi.org/10.1590/S1415-790X2010000300015
http://dx.doi.org/10.1590/S1415-790X2010...

This study aimed to analyze the effects of exposure to fine particles from burning biomass on hospitalizations for respiratory disease in children and the elderly.

METHODS

This was an epidemiological study, with an ecological time series design, of daily records of hospitalizations for respiratory disease in children aged 5 and elderly aged 65 in hospitals affiliated with the Brazilian Unified Health System (SUS) in the city of Cuiabá, Mato Grosso state, Midwestern Brazil, between 1^st January and 31^st December 2005. These age groups were selected as they are the most vulnerable to the effects of atmospheric pollution.^aa Organización Panamericana de la Salud. Evaluación de los efectos de la contaminación del aire en la salud de América. Latina y el Caribe. Washington (DC); 2005.

Data on hospitalizations due to respiratory causes, according to the International Classification of Diseases (ICD-10), categories JOO to JNN and to place of residence, were obtained from the Ministry of Health, database using SUS Hospital Admission Authorizations (HAAs) for 2005.^dd Ministério da Saúde. DATASUS. Informações em Saúde. Brasília (DF); 2011 {cited 2010 Nov 21}. Available from: http://w3.datasus.gov.br/datasus/datasus.php

Estimates of daily PM_2.5 concentrations, meteorological and calendar (days of the week and holidays) variables were used. Estimates of PM_2.5 were produced based on the Coupled Aerosol and Tracer Transport model to the Brazilian Developments on the Regional Atmospheric Modeling System (CATT-BRAMS), developed by the National Institute of Space Research (INPE), which provided measurements every three hours. ⁴ 4. Cançado JED, Saldiva PHN, Pereira LAA, Lara LBLS, Artaxo P, Martinelli LA, et al. The impact of sugar cane-burning emissions on the respiratory system of children and the elderly. Environ Health Perspect. 2006;14(5):725-9. DOI:http://dx.doi.org/10.1289/ehp.8485
http://dx.doi.org/10.1289/ehp.8485... Daily arithmetic means of PM_2.5 concentrations were calculated. Data on temperature and relative humidity were provided by the National Meteorological Institute (Inmet) in the city of Cuiabá.^ee Ministério da Agricultura. Normais climatológicas 2001-2009. Brasília (DF); 2010.

The municipality of Cuiabá has a population of 550,562^ff Ministério da Saúde. DATASUS. População Residente - Mato Grosso. Brasília (DF); 2010 {cited 2010 Dec 4}. Available from: http://tabnet.datasus.gov.br/cgi/deftohtm.exe?ibge/cnv/popMT.def and is located in the geomorphological unit called the Cuiabana Depression, considered the gateway to the Amazon rainforest. The rainy season is between December and April. During the rest of the year the masses of dry air above the center of Brazil inhibit the formation of rain. During these months, cold fronts from the south of the country are common, making the climate milder and humid. The heat means that the relative humidity falls to low levels when these fronts dissipate. Mean annual precipitation is 1,469.4 mm³ reaching maximum intensity in January, February and March. The maximum mean temperature reaches 34.1ºC, but absolute maximums can rise to above 40ºC and the minimum mean in July, the coldest month, is 16.7ºC.^gg Universidade Federal de Mato Grosso. Departamento de Geografia. Laboratório de Climatologia. Médias calculadas com base em dados de 1970 a 2002 do 9º Distrito de Meteorologia. Cuiabá; 2004. Available from: http://www.cuiaba.mt.gov.br/upload/arquivo/perfil_socioeconomico _de_cuiaba_Vol_III.pdf

To analyze the data, the generalized additive model technique was used. ¹³ 13. Hastie T, Tibshirani R. Generalized additive models. Londres: Chapman & Hall; 1990.The strategy of analysis consisted in modelling the trends and seasonality of the series using the spline functions for time; days of the weeks and holidays using dummy variables; meteorological conditions using the splines of temperature and relative humidity. Diagnostics were performed analyzing regression in order to evaluate the inclusion or exclusion of terms in the model and the final model's quality of fit. The terms corresponding to the daily concentrations of pollutants were added to the model, assuming that the association with the dependent variable is linear. Two periods were analyzed: the whole of 2005 and the dry period including the months of July and December. According to meteorological data for 2005, the year can be characterized as atypical. Associations between exposure on the same day with time lags of up to seven days, and moving averages from two to seven days before the outcome were investigated. The moving averages represented accumulated exposure in the days prior to the event. Thus, it was possible to calculate excess hospitalizations.

Relative risks (RR) for hospital admissions corresponded to an increase of 10 µg/m³ in PM_2.5 levels, which is an internationally accepted parameter. The analyses were carried out using the R version 2.11 and the Ares library programs,^hh Junger WL. Análise, imputação de dados e interfaces computacionais em estudos de séries temporais epidemiológicas {tese de doutorado}. Rio de Janeiro: Universidade do Estado do Rio de Janeiro; 2008. a collection of routines for analyzing time series in the R statistical program. A level of significance of 5% was adopted in the analyses.

This study was approved by the Research Ethics Committee of the Escola Nacional de Saúde Pública/FIOCRUZ (Protocol nº 164/08).

RESULTS

There were 1,020 elderly people and 1,152 children admitted to hospital with respiratory disease in the city of Cuiabá during 2005. The daily mean of hospitalizations for respiratory disease was 3.1 for children and 2.8 for the elderly. The daily PM_2.5 mean was 50% higher in the dry season than in the year overall (Table 1).

The series for PM_2.5, temperature and relative humidity for 2005 are shown in Figure 1. There was an increase in PM_2.5, characteristic of the burning season in the Amazon and began at the end of July and beginning of August, persisting until the end of November, small oscillations in temperature and typical reduction in relative humidity characteristic of the dry season.

Analysis of correlation did not show an association between pollution and the outcome variables. There was a statistically significant correlation between temperature and children's hospitalizations with RD and an inverse correlation between humidity and PM_2.5 and humidity and temperature, both statistically significant (Table 2). This justifies the use of such measures as variables in the models' fit.

Exposure to PM_2.5 was associated with hospitalization for RD in children throughout the year of 2005 and the dry season, for both lagged and moving averages. Throughout the entire period of 2005, there was an increase in hospitalizations in relation to the moving averages, this being 9.1% in one day (95%CI 1.8;18.1), 9.2% in two days (95%CI 0.1;19.4) and 12.0% in five days (95%CI 0.2;25.5) (Figure 2a). The associations were greater in the dry period. In this latter period there was increase in the moving averages of 11.4%, in one day (95%CI 1.7;22.2), 21.6%, in five days (95%CI 4.9;41.1) and of 22.0% in six days (95%CI 4.3;42.8) (Figure 2b). No statistically significant associations were found between exposure to PM_2.5 and hospitalization for RD in the elderly in any of the periods (Figures 2a and 2b).

DISCUSSION

The link between atmospheric pollution and higher occurrence of respiratory disease in populations of different countries has appeared in the literature since the middle of the last century. Episodes such as those in Donora (USA) in 1948 and London, England in 1952 constitute examples of these relationshipsⁱi World Health Organization. Health Guidelines for Vegetation Fire Events. Geneva; 1999. ^{, j}j Shrenk HH, Heimann H, Clayton GD, Gafafer WM, Wexler H. Air pollution in Donora, PA: epidemiology of the unusual smog episode of October 1948: preliminary report. Washington (DC): United States Public Health Service; 1949. (Public Health Bulletin, 306). and led to the formulation of laws aiming to control air pollution, especially in the United States in the 1970s.⁵5. Committee of the Environmental and Occupational Health Assembly of the American Thoracic Society. Health effects of outdoor air pollution. Am J Respir Crit Care Med. 1996;153(1):3-50.

Air pollution resulting from biomass burning occurs in a different way to that in urban centers. In these centers, it is characterized by long periods of exposure and low levels of pollutants, whereas biomass burning is characterized mainly by having well defined seasons¹¹11. Santos JS, Barros MDA. Idosos do Município do Recife, Estado de Pernambuco, Brasil: uma análise da morbimortalidade hospitalar. Epidemiol Serv Saude. 2008;7(3):177-86. DOI: http://dx.doi.org/10.5123/S1679-49742008000300003
http://dx.doi.org/10.5123/S1679-49742008... and high levels of fine particulate material, reaching up to 91.4 µg/m³ in 2005 (Table 1).

Using fire in natural areas and forests is criticized by environmentalists, scientists and society in general. However, in reality it is a common practice in tropical and subtropical regions, especially in those characterized by a pronounced dry season. This situation is common in various regions of the country, especially in the Brazilian Amazon. In Mato Grosso state, it is also common to observe forest affected by fire close to pastures, encouraged by land owners to renew the soil. This habit leads to large forest fires in times of severe drought and to the intense exacerbation of the population's health problems.³3. Botelho C, Correia AL, Silva AMC, Macedo AG, Silva COS. Fatores ambientais e Hospitalizações em crianças menores de cinco anos com infecção respiratória aguda. Cad Saude Publica. 2003;19(6):1771-80. DOI: http://dx.doi.org/10.1590/S0102-311X2003000600021
http://dx.doi.org/10.1590/S0102-311X2003...

A INPE survey^kk Instituto Nacional de Pesquisas Espaciais. Projeto PRODES. Monitoramento da floresta amazônica brasileira por satélite. Brasília (DF); 2010 {cited 2010 Dec 5}. Available from: http://www.obt.inpe.br/prodes/index.html identified 9,070 fires set in Brazil between 16 and 17^thAugust 2010, and more than three million tons of Carbon Monoxide were released into the atmosphere in the state of Mato Grosso alone between the beginning of the year and mid-August 2010. This situation means that in the city of Cuiabá, in 2010, the numbers seeking outpatient care for respiratory disease was double the mean for the preceding years.^ll Ministério da Saúde. DATASUS. Produção ambulatorial do SUS - Mato Grosso - por local de atendimento. Brasília (DF); 2010 {cited 2010 Dec 26}. Available from: http://tabnet.datasus.gov.br/cgi/deftohtm.exe?sia/cnv/qamt.def The rate of hospitalizations for respiratory disease in Cuiabá, was four times higher than that of the metropolitan region of the city of São Paulo, SP, Southeastern Brazil, during the same period.^mm Ministério da Saúde. DATASUS. Morbidade hospitalar do SUS - por local de residência. Brasília (DF); 2010 {cited 2010 Dec 26}. Available from: http://tabnet.datasus.gov.br/cgi/deftohtm.exe?sih/cnv/nrmt.def

Exposure to PM_2.5 from burning biomass is associated with an increase in hospital admissions for respiratory disease in children aged 5 in Cuiabá, in the south of the Mato Grosso region of the Amazon. These results are in concordance with those found in other studies of biomass burning.⁴4. Cançado JED, Saldiva PHN, Pereira LAA, Lara LBLS, Artaxo P, Martinelli LA, et al. The impact of sugar cane-burning emissions on the respiratory system of children and the elderly. Environ Health Perspect. 2006;14(5):725-9. DOI:http://dx.doi.org/10.1289/ehp.8485
http://dx.doi.org/10.1289/ehp.8485... ^{, 12}12. Silva AMC, Mattos IE, Freitas SR, Longo KM, Hacon SS. Particulate matter (PM2.5) of biomass burning emissions and respiratory diseases in the South of the Brazilian Amazon. Rev Bras Epidemiol. 2010;13(2):337-351. DOI: http://dx.doi.org/10.1590/S1415-790X2010000200015
http://dx.doi.org/10.1590/S1415-790X2010...

A time series analysis study carried out in the city of Piracicaba, SP, Southeastern Brazil, in 1997 and 1998 quantified daily hospital admissions for RD in children, adolescents and elderly aged 65.⁴4. Cançado JED, Saldiva PHN, Pereira LAA, Lara LBLS, Artaxo P, Martinelli LA, et al. The impact of sugar cane-burning emissions on the respiratory system of children and the elderly. Environ Health Perspect. 2006;14(5):725-9. DOI:http://dx.doi.org/10.1289/ehp.8485
http://dx.doi.org/10.1289/ehp.8485... There was a 32.05 increase in the number of hospitalizations for RD in children and adolescents, associated with interquartile variation of PM₁₀ and PM_2.5. Lopes & Ribeiro⁹9. Lopes FS, Ribeiro H. Mapeamento de internações hospitalares por problemas respiratórios e possíveis associações à exposição humana aos produtos da queima da palha de cana-de-açúcar no estado de São Paulo. Rev Bras Epidemiol. 2006;9(2):215-25. DOI: http://dx.doi.org/10.1590/S1415-790X2006000200008 (2006), using geoprocessing techniques, verified the correlation between products of burning sugar cane and incidence of respiratory problems in affected regions from 2000 to 2004 in the state of São Paulo. There were more cases of respiratory disease in regions where burning took place. Arbex et al¹1. Arbex MA, Cançado JED, Pereira LAA. Queima de biomassa e efeitos sobre a saúde. J Bras Pneumol. 2004;30(2):158-75. DOI: http://dx.doi.org/10.1590/S1806-37132004000200015
http://dx.doi.org/10.1590/S1806-37132004... (2004) studied the effect of burning sugar cane on outpatient care in the municipality of Araraquara, SP, Southeastern Brazil, in 1995, using time series analysis, and found a higher rate of hospitalization in the periods when most sugar cane was burnt. Carmo et al^cc Carmo CN, Hacon S, Longo KM, Freitas S, Mourão D, Louzano F, et al. Queima de biomassa e doenças respiratórias na região amazônica: uma aplicação de modelos aditivos generalizados. XLI Simpósio Brasileiro de Pesquisa Operacional 2009 - Pesquisa Operacional na Gestão do Conhecimento. Bahia, BR. Bahia: SOBRAPO; 2009. p.1472-77. (2009) found 2.9% and 2.6% increases in outpatient care for respiratory disease in children on the sixth and seventh days following exposure to PM_2.5 but found no significant associations between hospitalizations in the elderly, in the municipality of Alta Floresta, situated in the Mato Grosso area of the Amazon. Botelho et al³3. Botelho C, Correia AL, Silva AMC, Macedo AG, Silva COS. Fatores ambientais e Hospitalizações em crianças menores de cinco anos com infecção respiratória aguda. Cad Saude Publica. 2003;19(6):1771-80. DOI: http://dx.doi.org/10.1590/S0102-311X2003000600021
http://dx.doi.org/10.1590/S0102-311X2003... (2003) found higher rates of hospital admission among children aged 5 in the dry season compared to the rainy season when analyzing emergency care for respiratory disease in Cuiabá. Silva et al¹²12. Silva AMC, Mattos IE, Freitas SR, Longo KM, Hacon SS. Particulate matter (PM2.5) of biomass burning emissions and respiratory diseases in the South of the Brazilian Amazon. Rev Bras Epidemiol. 2010;13(2):337-351. DOI: http://dx.doi.org/10.1590/S1415-790X2010000200015
http://dx.doi.org/10.1590/S1415-790X2010... (2010), in a study which used the same estimates as the Coupled Aerosol and Tracer Transport Model to the Brazilian Developments on the Regional Atmospheric Modeling System (CATT-BRAMS) spatially analyzed the effect of exposure to PM_2.5 in respiratory disease in children aged between one and four years old and in the elderly aged 65 in Mato Grosso in 2004. Statistically significant associations were found between the occurrence of hospitalizations for respiratory disease and the percentage of annual critical hours of particulate material.

Cases requiring hospitalization are at higher risk than those which require medical consultation in the primary care network. In this study, it was not possible to conduct a survey of outpatient care, which impedes evaluation of the risks which pollution from PM_2.5 may present for respiratory disease requiring less complex levels of care.

There is accumulated risk between the moving averages of exposure from the first to the seventh day in the dry season, due to the permanent association between them and the risk of children being hospitalized for respiratory disease, despite some comparisons not showing statistical significance (Figure 2a). This data indicates the distinctive and persistent effect of PM_2.5 on these morbidities in this age group in Cuiabá. The associations found in this study were greater than those found in similar studies. This suggests that the seriousness of the Cuiabá children's cases of respiratory disease is greater than that of cases which occur in metropolitan regions and in other cities belonging to the Amazon. The study design used did not allow individual exposure to PM_2.5 to be measured, preventing the joint analysis of other factors and outcomes which may contribute to explaining this phenomenon.

No association was observed between exposure to PM_2.5 and hospitalization for respiratory disease in the elderly. In this segment of the population, in addition to the respiratory damage caused by pollutants from the biomass burning, there are also associated comorbidities which may contribute to the lack of association.¹¹11. Santos JS, Barros MDA. Idosos do Município do Recife, Estado de Pernambuco, Brasil: uma análise da morbimortalidade hospitalar. Epidemiol Serv Saude. 2008;7(3):177-86. DOI: http://dx.doi.org/10.5123/S1679-49742008000300003
http://dx.doi.org/10.5123/S1679-49742008... However, the different methodologies used in studies for analyzing the levels of exposure cannot be ruled out, in addition to differences in the studied populations.

In this study, data on hospitalizations for respiratory disease were used. In the study by Bittencurt et al²2. Bittencourt AS, Camacho LB, Leal MC O Sistema de Informação Hospitalar e sua aplicação na saúde coletiva. Cad Saude Publica. 2006;22(1):19-30. DOI: http://dx.doi.org/10.1590/S0102-311X2006000100003
http://dx.doi.org/10.1590/S0102-311X2006... (2006) it is notable that the Hospital Information System (SIH), which provided the data on the hospitalizations, used HAAs and not the individual patients as the unit of analysis. Thus, the use of hospitalizations to estimate the number of cases of illness is a weakness. However, this is still regarded as one of the best indicators of respiratory health problems.¹⁴14. Veras CMT, Martins MS. A confiabilidade dos dados nos formulários de autorização de internação hospitalar (AIH). Cad Saude Publica. 1994;10(3):339-55. DOI: http://dx.doi.org/10.1590/S0102-311X1994000300014
http://dx.doi.org/10.1590/S0102-311X1994...

Cuiabá is located in the Amazon, in the middle of the Mato Grosso savannah. It is known that air pollutants partially come from anthropogenic sources (mobile and stationary) and other from burning pasture, forest and yards. The intense burning which takes place in the south of the Amazon is located in a region adjacent and close to Cuiabá. The CATT-BRAMS produces modelling of pollutants using a computational system created to simulate and study the atmospheric transport of products originating from burning biomass. Thus, it can predict the concentration of PM_2.5 in the Amazon region and in Cuiabá with a good degree of accuracy, considering the influence of the additional effect of these diverse sources of pollutants. Comparison of estimates of this model with actual measurements of PM_2.5 made in situ were evaluated and deemed satisfactory.⁷7. Freitas SR, Longo KM, Dias MAFS, Chatfield R, Dias PLS, Artaxo P, et al. The coupled aerosol and tracer transport model to the Brazilian developments on the Regional Atmospheric Modeling System (CATT-BRAMS). Part 1: model description and evaluation. Atmos Chem Phys Discuss. 2007;7(3):8525-69. DOI: http://dx.doi.org/10.5194/acpd-7-8525-2007
http://dx.doi.org/10.5194/acpd-7-8525-20... This model does not consider direct exposure to PM_2.5 from other anthropogenic sources, as no chemical analysis of the particulate was carried out. Other particulates, as well as those from burning biomass, are probably present albeit in smaller quantities.

The results of this investigation showed the influence of PM_2.5 on the occurrence of hospitalizations for respiratory disease in children 5 in the city of Cuiabá. It is probable that this is also occurring in other cities and regions which experience large scale biomass burning.

REFERÊNCIAS

Datas de Publicação

Histórico