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Revista da Associação Médica Brasileira

versión impresa ISSN 0104-4230

Rev. Assoc. Med. Bras. vol.58 no.3 São Paulo mayo/un. 2012

http://dx.doi.org/10.1590/S0104-42302012000300009 

ORIGINAL ARTICLE

 

Asthma and ambient pollutants: a time series study

 

 

Camila Trolez AmâncioI; Luiz Fernando Costa NascimentoII

IMedical Student, Department of Medicine, Universidade de Taubaté (Unitau), Taubaté, SP, Brazil
IIPhD in Public Health; Assistant Professor, Unitau, Taubaté, SP, Brazil

Correspondence to

 

 


SUMMARY

OBJECTIVE: To estimate the risk of hospitalization for asthma in children after exposure to air pollutants in a medium-sized city in Southeast Brazil.
METHODS: An ecological time series study was carried out with hospitalization data for asthma in children under 10 years of age living in São José dos Campos, SP, Brazil, and concentrations of particulate matter with aerodynamic diameter < 10 microns, sulfur dioxide, and ozone; data were also obtained on relative humidity and temperatures. Pearson's coefficient correlation was used for the study variables. To estimate the association between hospitalizations due to asthma and air pollutants, Poisson regression generalized additive models were built, according to lags of up to seven days.
RESULTS: There was a strong correlation between hospitalizations and the pollutants particulate matter and sulfur dioxide. Exposure to particulate matter and sulfur dioxide were associated with significant relative risks of 1.01 to 1.04 of hospitalization due to asthma on the same day and within three days after exposure. Increases in the concentrations of these pollutants increase the risk of hospitalization between 8% and 19%.
CONCLUSION: There is evidence of the effect of air pollutants on asthma hospitalization in a medium-sized city in Southeast Brazil.

Keywords: asthma; air pollutants; particulate material; sulfur dioxide; children's health; time series study.


 

 

INTRODUCTION

Air pollution is defined as the presence of foreign substances in the air that affect the health and well-being of living beings1. This problem is likely to have adverse effects on health, even when pollutant levels are within the standards required by legislation.

The groups that are most susceptible to its adverse effects are children and the elderly2,3. For children, the fact is due to greater exposure to pollutants, increased minute ventilation, and higher levels of physical activity4. Among the effects of chronic exposure to air pollution in children and adolescents, one can highlight stunted development and decreased lung function, as well as the increased number of episodes of respiratory illness and hospitalizations5,6.

The air pollutants associated with outcomes such as chronic diseases in children and increases in the risk of death are mainly particulate matter (PM10), sulfur dioxide (SO2), and ozone (O3)7. In spite of evidence showing the association between exposure to air pollutants and damage to health, the mechanisms by which they cause these diseases are yet to be elucidated, but it is believed that the histological lesions caused by pollutants in the lung parenchyma may increase the harmful effects of viruses and/or allergens8.

Exposure to PM10 is associated with increased morbidity through different mechanisms of action, including local inflammation, injury by oxidative stress, and endothelial dysfunction9. SO2 is a respiratory irritant that has the capacity to deposit in the distal regions of the upper airways and lung parenchyma. Exposure to O3, in turn, is associated with a decrease in lung function, increased reactivity and inflammation of airways, and altered macrophage function10.

It is believed that the adverse effects caused by exposure to environmental pollutants have a performance lag, i.e., an individual exposed to a pollutant on a given day may present with an acute asthma attack a few days later2.

Asthma, a chronic disease of genetic nature and environmental component, very common among children, is the main cause for the prolonged impairment of their health in developed countries, and shows a high prevalence in developing countries11,12. The disease is characterized by resulting from bronchial inflammation, with an exaggerated response of the lower airways and limited airflow in these airways13. It is estimated that about 10% of the world's population and 20% of the population of Latin America have the disease14; approximately 24% of Brazilian schoolchildren15, with predominance of the male gender16. In addition to being a disease that poses a public health problem, asthma has a high socioeconomic impact17. The financial cost due to hospitalization for asthma in children and adolescents is around R$ 6 million for the federal and state government18.

The present study aims to estimate the association between exposure to the air pollutants PM10, SO2, and O3 and hospital admissions for asthma in children in São Jose dos Campos, state of São Paulo, Brazil.

 

METHODS

The study was carried out in São José dos Campos, a midsize city in the countryside of the state of São Paulo, Brazil. It is located at coordinates 23 0 10' S and 450 52' W, 600 m above sea level; its climate is altitude tropical humid. It has an important industrial sector and is transected by the most important and busiest highway in Brazil. It had an estimated population of just over 600,000 inhabitants in 2009. It is located between São Paulo and Rio de Janeiro, the two largest Brazilian cities, and is transected by Via Dutra, a highway with intense traffic19.

This is an ecological time series study, which assessed hospitalizations for asthma (ICD10: J45) in individuals aged zero to ten years living in the city of São José dos Campos, from January 1, 2004 to December 31, 2005. Data were obtained from the Department of Information and Informatics of the National Health System20. Data on levels of the environmental pollutants PM10 and SO2 were also selected, in their daily means, and O3, in its daily eighthour maximum levels, obtained from the Environmental Sanitation Technology Company, which has a measuring station in São José dos Campos21. PM10 was measured using a beta monitor, SO2 was measured through the coulometry technique, and O3, by chemiluminescence; all were quantified in µg/m3. The temperature and humidity data were obtained from the Science, Space Technology and Applications Foundation22.

Since there can be a gap behavior for the effects of pollutants, i.e., hospitalization occurs not only on the same day (lag 0), but also on subsequent days (lag 1, lag 2...), a lag template was constructed of zero to seven days for each of the pollutants in the study.

To estimate the risk of asthma hospitalization due to exposure to pollutants, Poisson regression generalized additive model was used. For this reason, the air pollutants were always analyzed together in a multipollutant model, adjusted for humidity, minimum temperature, and controlled by day of week and seasonality. The computer program used for this analysis was Statistica.

 

RESULTS

During the study period, there were 841 hospital admissions for bronchial asthma in individuals aged 0-19 years living in São Jose dos Campos. The daily mean was 1.15 hospitalizations (SD = 1.26), ranging from zero to seven.

A total of 49 data on temperature and humidity were missing (6.7% of days), 26 related to O3 (3.6%), 20 to SO2 values (2.7%), and 31 to PM10 (4.2%). There were no missing data regarding hospitalizations for asthma. These missing data did not affect the outcome of the study.

Mean values with their standard deviations, minimum, and maximum values and interquartile differences are shown in Table 1. Figure 1 shows that the PM10 and SO2 have a seasonal characteristic.

 

 

Table 2 presents the correlation matrix between variables of the study. Hospital admissions for asthma showed a positive correlation with PM10 and SO2, and a negative correlation with O3. Among the pollutants, positive correlations were observed. The meteorological variables showed negative correlations with pollutants, except for ozone, which was positively correlated with temperature; as for hospitalization, there was a positive correlation with humidity and a negative correlation with temperature.

The months with the highest numbers of admissions were April, May, and June in both years of study, respectively, 54, 106, and 51 admissions in 2004 and 53, 52, and 54 in 2005.

Based on Poisson regression, with the three pollutants analyzed together, adjusted for minimum temperature and humidity and controlled per day of week and seasonality, regression coefficients were obtained and the respective standard-errors for each pollutant in each lag structure (Table 3). The relative risks and their 95% confidence intervals are shown in Figure 2.

 

 

Noteworthy is the combination that occurs on the same, second, and third days of exposure to PM10 and on the first, third, and sixth days after exposure to SO2. The increase of 17 µg/m3 PM10 results in an increase in the relative risk of 16% and 19%; an increase in the concentration of SO2 of 3 µg/m3 leads to an increase in the relative risk between 8% and 14%.

 

DISCUSSION

There have been few studies on the effects of pollution as a cause of hospitalization due to asthma, and this is the first to be conducted in a mid-sized city such as São José dos Campos.

PM10 was the pollutant most often associated with hospitalizations for asthma, with statistical significance both on the same day of exposure and on the second and third days of exposure. In a study by Gouveia et al.23, conducted in São Paulo, Brazil, it was observed that an increase of 10 µg/m3 in the levels of inhalable PM10 is associated with an increase of 4.6% in hospitalizations for asthma in children.

The levels of annual mean concentration of PM10 observed in this study exceeded the levels considered acceptable by the World Health Organization (WHO), and annual exposure levels above 70 µg/m3 are associated with significant deleterious effects on health, leading to up 15% increase in mortality24.

The study by Gouveia et al.23 found a mean PM10 during the study period of 54.49 µg/m3, a much higher level than the one found in the present study, 24 µg/m3. The same occurred with the study conducted in Curitiba2, which showed a mean of 90.39 µg/m3 for PM10. A possible explanation for such differences would be the highest concentration of uncontrolled combustion in the cities of São Paulo and Curitiba, compared to São José dos Campos, as this is one reason for PM10 emission.

SO2 was the pollutant most often associated with hospitalizations for asthma, presenting as a risk factor on the same day of exposure and after the first, third, and sixth days. A study that used Poisson regression analysis and was conducted in São Paulo, found a statistically significant positive association between asthma and this pollutant23. Likewise, SO2 was also a risk factor, both when analyzed alone and when considered together with other pollutants on an average of four days, in the city of São Paulo25. The mean concentrations found in this study are within the range considered acceptable by the WHO, which accepts a maximum level of exposure of 20 µg/m3 for 24 hours24.

In a study conducted in São Paulo, a mean SO2 of 17.71 µg/m3 was observed, which differs from the value found in this study23. The same difference occurred when it was compared with a study carried out in the city of Rio de Janeiro, which showed a mean value of 18.59 µg/m3 for SO226. These facts can be explained by higher emissions of that pollutant in São Paulo and Rio de Janeiro, due to a larger vehicular fleet, one of the main sources of that air pollutant.

As for O3, it was observed that this pollutant was not a statistically significant risk factor in any of the analyzed lag structures. The study by Bakonyi et al.2 showed a statistically significant effect for O3 only with a moving average of three days. This statistical difference may be due to the fact that their study variable were subjects aged 0-14 years of age treated for all respiratory causes, not just asthma, and also to the fact that they used moving averages and not lag structures, as in the present study.

The maximum daily concentration of this pollutant was 232 µg/m3, with a mean of 74.27 µg/m3 during 2004 and 2005. The manual of the WHO accepts a maximum level of exposure of 100 µg/m3 for 8 hours, for 1 day24. Levels above 240 µg/m3 are associated with significant effects on health, such as decreased lung function, airway inflammation, and hyperreactivity.

A mean of 71.79 µg/m3 of ozone was observed between 1996 and 2000 in São Paulo, which is very close to the value found in this study23. In other studies, in the cities of Curitiba and Rio de Janeiro, mean O3 values of 63.71 µg/m3 and 81.08 µg/m3, were observed, respectively, and these are also relatively close to the levels in this study2,26.

In spite of the small magnitude of the RR found, the impact of air pollution on public health must be substantial, taking into account the large number of exposed individuals. The results shown here represent a quantitative approximation of the impact of air pollution on the population's health. It is important to emphasize that the outcome studied here, hospitalization, is just one of many effects caused by air pollution. Effects such as the occurrence of symptoms, medication use, school absenteeism, and reduced physical activity, among others, are not evaluated in this study. These, although considered to be minor effects to the individual's health, are of great importance to public health, given the high frequency at which they occur and due to their negative impact on quality of life and negative economic consequences, such as school and work absenteeism.

This study uses secondary data to calculate the coefficients and relative risks for hospitalizations resulting from increased levels of air pollution. These data come from very reliable and established sources27,28 and are widely used in technical and scientific studies. The fact that the records refer to hospitalizations in public hospitals, which belong to the Public Health System (SUS), is noteworthy. Thus, the results shown here reflect the effects of air pollution in the population that uses this type of healthcare service, which accounts for the majority of the population.

On the other hand, information from the hospital information system of SUS used in this study are produced with financial goals and not strictly for epidemiological studies, and may thus have some degree of inaccuracy. They may have underestimated the frequency of certain diseases, considering the technological profile of the service network, as well as diagnostic coding errors. Another problem in this database is the possibility of counting the same patient twice, as the system does not identify hospitalizations. However, in ecological time series studies of daily basis, factors whose distribution does not vary daily do not act as potential confounders27.

The quality of information on hospital admissions and other potential problems with this database does not vary from day to day and is not correlated with levels of air pollution. Therefore, its implications regarding the estimation of the observed effects are minimal. As for the concentrations of pollutants, O3 exceeded the acceptable value of 160 mg/m3 in 16 occasions, those of PM10 exceeded the value of 50 mg/m3 in 21 days, and SO2 did not exceed the values recommended by the National Council for the Environment (Conselho Nacional do Meio Ambiente - Conama)29.

This study demonstrates that even populations of midsized cities may be affected by environmental pollution, resulting in an increasing incidence of hospitalizations for asthma and decreased quality of life of citizens.

 

CONCLUSION

The pollutants PM10 and SO2 were identified as associated with hospitalization caused by asthma in a mid-sized city, and this information may be useful in the implementation of public health policies in the municipality.

 

REFERENCES

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29. Brasil. Ministério do Meio Ambiente. Resolução Conama nº 03/1990. [citado 20 jan 2012]. Disponível em: http://www.mma.gov.br/port/conama/legipesq.cfm?tipo=3&numero=03&ano=1990&texto=.         [ Links ]

 

 

Correspondence to:
Luiz Fernando Costa Nascimento
Avenida Tiradentes, 500 Taubaté
SP, Brazil CEP: 12030-180
luiz.nascimento@unitau.br

Submitted on: 09/09/2011
Approved on: 02/10/2012
Financial Support: FAPESP grant # 2009/09487-4.
Conflict of interest: None.

 

 

Study conducted at Department of Medicine, Universidade de Taubaté (Unitau) Taubaté, SP, Brazil