Particulate matter originating from biomass burning and respiratory

[Burning of sugarcane biomass and hospitalizations of children and older adults for respiratory problems in Pernambuco State, Brazil]

This study aimed to analyze the relationship between hospitalizations for respiratory problems and the regular burning of sugarcane in Pernambuco State, Brazil. This is an ecological time series study corresponding to the period from 2008 to 2018. The rates of hospitalizations for respiratory diseases in children aged under 5 years and in adults older than 60 years in sugarcane-producing and non-producing municipalities were compared using nonparametric Mann-Whitney statistical analysis. Together, we observed the monthly distribution of the hot spots occurrences in the case and control municipalities and applied Pearson's correlation to analyze the association between both variables. For both age groups, hospitalization rates are higher in sugarcane-producing municipalities, with a statistically significant difference p < 0.005. The rate of hospitalization in older adults is 28% higher in the case municipalities, and is even higher in children aged under 5 years whose ratio of the medians is 40%. However, the seasonal behavior of hospitalizations for respiratory diseases differs from that observed in the monthly distribution of hot spots, without statistically significant correlation. These findings suggest a possible association with chronic exposure to particulates emitted by biomass burning, compromising the health of vulnerable groups, and endorse the need to replace fires in the monoculture of sugarcane and to structure public policies to protect human and environmental health.

New concentration-response functions for seven morbidity endpoints associated with short-term PM2.5 exposure and their implications for health impact assessment

BACKGROUND

Morbidity burdens from ambient air pollution are associated with market and non-market costs and are therefore important for policymaking. The estimation of morbidity burdens is based on concentration-response functions (CRFs). Most existing CRFs for short-term exposures to PM2.5 assume a fixed risk estimate as a log-linear function over an extrapolated exposure range, based on evidence primarily from Europe and North America.

OBJECTIVES

We revisit these CRFs by performing a systematic review for seven morbidity endpoints previously assessed by the World Health Organization, including data from all available regions. These endpoints include all cardiovascular hospital admission, all respiratory hospital admission, asthma hospital admission and emergency room visit, along with the outcomes that stem from morbidity, such as lost work days, respiratory restricted activity days, and child bronchitis symptom days.

METHODS

We estimate CRFs for each endpoint, using both a log-linear model and a nonlinear model that includes additional parameters to better fit evidence from high-exposure regions. We quantify uncertainties associated with these CRFs through randomization and Monte Carlo simulations.

RESULTS

The CRFs in this study show reduced model uncertainty compared with previous CRFs in all endpoints. The nonlinear CRFs produce more than doubled global estimates on average, depending on the endpoint. Overall, we assess that our CRFs can be used to provide policy analysis of air pollution impacts at the global scale. It is however important to note that improvement of CRFs requires observations over a wide range of conditions, and current available literature is still limited.

DISCUSSION

The higher estimates produced by the nonlinear CRFs indicates the possibility of a large underestimation in current assessments of the morbidity impacts attributable to air pollution. Further studies should be pursued to better constrain the CRFs studied here, and to better characterize the causal relationship between exposures to PM2.5 and morbidity outcomes.

Air pollution from forest burning as environmental risk for millions of inhabitants of the Brazilian Amazon: an exposure indicator for human health

In this study, we propose an indicator of air pollution exposure to identify potential hazardous areas for human health in the Amazon and Central-West Regions of Brazil from 2010 to 2019. This indicator aggregates both concentrations and time of exposure to fine particulate matter (PM2.5), according to the current limit recommended by the World Health Organization (WHO). We used daily PM2.5 averages obtained from the Brazilian Health Integrated Environmental Information System (SISAM) to calculate the percentages of days with PM2.5 concentrations exceeding the limit of 15µg/m³ per year and per month. From 2010 to 2019, the months from August to October presented the largest areas and the highest percentages of days with unacceptable pollution concentration values, harmful to human health. These areas were concentrated in the Arc of Deforestation. Therefore, 60% of the residents of the Amazon and Central-West regions were subjected to inadequate air quality for approximately six months per year. The proposed indicator is reproducible and appropriate to monitor areas of exposure and risk for human health.

Environmental air pollution: respiratory effects

Environmental air pollution is a major risk factor for morbidity and mortality worldwide. Environmental air pollution has a direct impact on human health, being responsible for an increase in the incidence of and number of deaths due to cardiopulmonary, neoplastic, and metabolic diseases; it also contributes to global warming and the consequent climate change associated with extreme events and environmental imbalances. In this review, we present articles that show the impact that exposure to different sources and types of air pollutants has on the respiratory system; we present the acute effects-such as increases in symptoms and in the number of emergency room visits, hospitalizations, and deaths-and the chronic effects-such as increases in the incidence of asthma, COPD, and lung cancer, as well as a rapid decline in lung function. The effects of air pollution in more susceptible populations and the effects associated with physical exercise in polluted environments are also presented and discussed. Finally, we present the major studies on the subject conducted in Brazil. Health care and disease prevention services should be aware of this important risk factor in order to counsel more susceptible individuals about protective measures that can facilitate their treatment, as well as promoting the adoption of environmental measures that contribute to the reduction of such emissions.

Avoiding hospital admissions for respiratory system diseases by complying to the final Brazilian air quality standard: an estimate for Brazilian southeast capitals

According to the World Health Organization (WHO), in 2016, 91% of the global population was living in places where guidelines on air quality were not met, which results in an estimated figure of seven million deaths annually. The new Brazilian air quality standards, CONAMA 491/2018, was the first revision in over two decades and has as final target the WHO guidelines for air quality, although no deadline has been established for implementation. The goal of this work was to quantify public health gains of this new policy based on hospitalizations due to respiratory diseases, the most studied outcome in Brazilian time series studies, in four Brazilian Southeast capitals: São Paulo (SP), Rio de Janeiro (RJ), Belo Horizonte (MG), and Vitória (ES) for PM₁₀, PM_2,5, SO₂, CO, and O₃. Population and hospitalizations data for all respiratory diseases for people under 5 years old, over 64 years old, most vulnerable populations, and all ages were analyzed. The air quality monitoring data was analyzed in two different periods: 2016 to 2018 for São Paulo and Vitória; and between 2015 and 2017 for Belo Horizonte and Rio de Janeiro, according to available monitoring data. A literature review was carried out to determine the appropriate relative risk to be used in the estimations, and the public health gains were calculated based on the selected relative risks for each city. The highest estimate was for São Paulo, with 3454 avoidable respiratory hospital admissions (all ages). In total, the four cities accounted for 4148 avoidable hospitalizations, which was associated to $1.1 million public health gains. Results considering the day of exposure (lag 0) were superior to those with the 5-day moving average (lag 5). The results highlighted the importance of adopting more restrictive standards and called for public policies, the necessity of expanding the air quality monitoring network, mapping emission sources, and improve the knowledge about the interaction between air pollution and health outcomes beyond respiratory disease for the region.

Respiratory Diseases, Malaria and Leishmaniasis: Temporal and Spatial Association with Fire Occurrences from Knowledge Discovery and Data Mining

The relationship between the fires occurrences and diseases is an essential issue for making public health policy and environment protecting strategy. Thanks to the Internet, today, we have a huge amount of health data and fire occurrence reports at our disposal. The challenge, therefore, is how to deal with 4 Vs (volume, variety, velocity and veracity) associated with these data. To overcome this problem, in this paper, we propose a method that combines techniques based on Data Mining and Knowledge Discovery from Databases (KDD) to discover spatial and temporal association between diseases and the fire occurrences. Here, the case study was addressed to Malaria, Leishmaniasis and respiratory diseases in Brazil. Instead of losing a lot of time verifying the consistency of the database, the proposed method uses Decision Tree, a machine learning-based supervised classification, to perform a fast management and extract only relevant and strategic information, with the knowledge of how reliable the database is. Namely, States, Biomes and period of the year (months) with the highest rate of fires could be identified with great success rates and in few seconds. Then, the K-means, an unsupervised learning algorithms that solves the well-known clustering problem, is employed to identify the groups of cities where the fire occurrences is more expressive. Finally, the steps associated with KDD is perfomed to extract useful information from mined data. In that case, Spearman's rank correlation coefficient, a nonparametric measure of rank correlation, is computed to infer the statistical dependence between fire occurrences and those diseases. Moreover, maps are also generated to represent the distribution of the mined data. From the results, it was possible to identify that each region showed a susceptible behaviour to some disease as well as some degree of correlation with fire outbreak, mainly in the drought period.

DIFFERENT RESPONSE TO EXPOSURE TO AIR POLLUTANTS IN GIRLS AND BOYS

Objective:

Identify the association between exposure to fine particulate matter and hospitalizations due to respiratory diseases in children up to ten years of age in the city of Cuiabá, Mato Grosso, stratifying the analysis by sex and calculating excess costs.

Methods:

Ecological study of time series. The dependent variable was daily hospitalizations according to the 10^th Revision of the International Classification of Diseases (ICD10): J04.0, J12.0 to J18.9, J20.0 to J21.9 and J45.0 to J45.0. The independent variables were the concentration of fine particulate, estimated by a mathematical model, temperature and relative air humidity, controlled by short and long-term trends. Generalized additive model of Poisson regression was used. Relative risks, proportional attributable risk (PAR) and excess hospitalizations and their respective costs by the population attributable fraction (PAF) were calculated.

Results:

1,165 children were hospitalized, 640 males and 525 females. The mean concentration, estimated by the mathematical model, was 15.1±2.9 mcg/m³ for PM_2.5. For boys, there was no significant association; for girls a relative risk of up to 1.04 of daily hospitalizations due to respiratory diseases was observed for exposure to PM 2.5 in lags 1, 2 and 6. Increase of 5 µg/m³ in these concentrations increased the percentage of the risk in 18%; with an excess 95 hospital admissions and with excess expenses in the order of US$ 35 thousand.

Conclusions:

Significant effect in daily hospitalizations due to respiratory diseases related to exposure to fine particulate matter was noted for girls, suggesting the need for stratification by sex in further studies.

Effects of exposure to fine particulate matter in elderly hospitalizations due to respiratory diseases in the South of the Brazilian Amazon

Exposure to air pollution is an important cause of hospital admissions due to respiratory diseases. Nevertheless, few studies use pollutant concentration data estimated by mathematical models. A time-series ecological study was developed, using data from hospitalizations due to respiratory diseases in people over 60 years of age, residents of Cuiabá, Brazil, during 2012, obtained from the Brazilian Ministry of Health. The independent variables were the concentrations of fine particulate matter (PM_2.5) and carbon monoxide (CO) estimated by mathematical modeling, minimum temperature, and relative humidity (obtained from the Brazilian Meteorological Agency), and the number of forest fires. The generalized linear regression model of Poisson was used, with lags of 0 to 7 days. The coefficients obtained were transformed into relative risk of hospitalization, with respective 95% confidence intervals; alpha=5% was adopted. In that year, 591 hospitalizations were evaluated, with a daily average of 1.61 (SD=1.49), the PM_2.5 average concentration was 15.7 µg/m³, and the CO average concentration was 144.2 ppb. Significant associations between exposure to these contaminants and hospitalizations in lags 3 and 4 in 2012 were observed. There was a hospitalization risk increase of 31.8%, with an increase of 3.5 µg/m³ of PM_2.5 concentrations and an increase of 188 in the total number of hospitalizations, with an expense of more than ≈US$ 96,000 for the Brazilian Public Health System. This study provided information on the cost of air pollution to the health system and the feasibility of using a mathematical model to estimate environmental concentration of air pollutants.

Effects of exposure to air pollutants on children's health in Cuiabá, Mato Grosso State, Brazil

Exposure to air pollutants, usually measured by environmental agencies that are not present in all states, may be associated with respiratory admissions in children. An ecological time series study was conducted with data on hospitalizations due to selected respiratory diseases in children under 10 years of age in 2012 in the city of Cuiabá, Mato Grosso State, Brazil. Mean levels of fine particulate matter (PM2.5) were estimated with a mathematical model, data on low temperatures and relative humidity were obtained from the Brazilian National Institute of Meteorology, and the numbers of brush burnings were obtained from the Environmental Information System. The statistical approach used the Poisson regression generalized additive model with lags of 0 to 7 days. The financial costs and increases in hospitalizations due to increments in PM2.5 were estimated. There were 565 hospitalizations (mean 1.54 admissions/day; SD = 1.52), and mean PM2.5 concentration was 15.7µg/m3 (SD = 3.2). Associations were observed between exposure and hospitalizations in the second semester at lags 2 and 3, and at lag 2 when the entire year was analyzed. An increment of 5µg/m3 in PM2.5 was associated with an increase of 89 hospitalizations and costs exceeding BRL 95,000 (≈ USD 38,000) for the Brazilian Unified National Health System. Data estimated by mathematical models can be used in locations where pollutants are not monitored.

Short-term effects of fine particulate matter pollution on daily health events in Latin America: a systematic review and meta-analysis

OBJECTIVES

Ambient air pollution is among the leading risks for health worldwide and by 2050 will largely overcome deaths due to unsafe sanitation and malaria, but local evidence from Latin America (LA) is scarce. We aimed to summarize the effect of short-term exposure to fine particulate air pollution (PM_2.5) on morbidity and mortality in Latin America and evaluate evidence coverage and quality, using systematic review and meta-analysis.

METHODS

The comprehensive search (six online databases and hand-searching) identified studies investigating the short-term associations between PM_2.5 and daily health events in LA. Two reviewers independently accessed the internal validity of the studies and used random-effect models in the meta-analysis.

RESULTS

We retrieved 1628 studies. Nine were elected for the qualitative analysis and seven for the quantitative analyses. Each 10 µg/m³ increments in daily PM_2.5 concentrations was significantly associated with increased risk for respiratory and cardiovascular mortality in all-ages (polled RR = 1.02, 95% CI, 1.02-1.02 and RR = 1.01, 95% CI , 1.01-1.02, respectively).

CONCLUSIONS

Short-term exposure to PM_2.5 in LA is significantly associated with increased risk for respiratory and cardiovascular mortality. Evidence is concentrated in few cities and some presented high risk of bias.

Exposure to fine particulate matter and hospital admissions due to pneumonia: Effects on the number of hospital admissions and its costs

Summary Objective: Given that respiratory diseases are a major cause of hospitalization in children, the objectives of this study are to estimate the role of exposure to fine particulate matter in hospitalizations due to pneumonia and a possible reduction in the number of these hospitalizations and costs. Method: An ecological time-series study was developed with data on hospitalization for pneumonia among children under 10 years of age living in São José do Rio Preto, state of São Paulo, using PM2.5 concentrations estimated using a mathematical model. We used Poisson regression with a dependent variable (hospitalization) associated with PM2.5 concentrations and adjusted for effective temperature, seasonality and day of the week, with estimates of reductions in the number of hospitalizations and costs. Results: 1,161 children were admitted to hospital between October 1st, 2011, and September 30th, 2013; the average concentration of PM2.5 was 18.7 µg/m3 (≈32 µg/m3 of PM10) and exposure to this pollutant was associated with hospitalization four and five days after exposure. Conclusion: A 10 µg/m3 decrease in concentration would imply 256 less hospital admissions and savings of approximately R$ 220,000 in a medium-sized city.

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.

[Fine particulate matter estimated by mathematical model and hospitalizations for pneumonia and asthma in children]

OBJECTIVE

To estimate the association between exposure to fine particulate matter with an aerodynamic diameter <2.5 microns (PM2.5) and hospitalizations for pneumonia and asthma in children.

METHODS

An ecological study of time series was performed, with daily indicators of hospitalization for pneumonia and asthma in children up to 10 years of age, living in Taubaté (SP) and estimated concentrations of PM2.5, between August 2011 and July 2012. A generalized additive model of Poisson regression was used to estimate the relative risk, with lag zero up to five days after exposure; the single pollutant model was adjusted by the apparent temperature, as defined from the temperature and relative air humidity, seasonality and weekday.

RESULTS

The values of the relative risks for hospitalization for pneumonia and asthma were significant for lag 0 (RR=1.051, 95%CI; 1.016 to 1.088); lag 2 (RR=1.066, 95%CI: 1.023 to 1.113); lag 3 (RR=1.053, 95%CI: 1.015 to 1.092); lag 4 (RR=1.043, 95%CI: 1.004 to 1.088) and lag 5 (RR=1.061, 95%CI: 1.018 to 1.106). The increase of 5mcg/m(3) in PM2.5 contributes to increase the relative risk for hospitalization from 20.3 to 38.4 percentage points; however, the reduction of 5μg/m(3) in PM2.5 concentration results in 38 fewer hospital admissions.

CONCLUSIONS

Exposure to PM2.5 was associated with hospitalizations for pneumonia and asthma in children younger than 10 years of age, showing the role of fine particulate matter in child health and providing subsidies for the implementation of preventive measures to decrease these outcomes.

[Fine particulate matter estimated by mathematical model and hospitalizations for pneumonia and asthma in children]

Objective:

To estimate the association between exposure to fine particulate matter with an aerodynamic diameter <2.5 microns (PM_2.5) and hospitalizations for pneumonia and asthma in children.

Methods:

An ecological study of time series was performed, with daily indicators of hospitalization for pneumonia and asthma in children up to 10 years of age, living in Taubaté (SP) and estimated concentrations of PM_2.5, between August 2011 and July 2012. A generalized additive model of Poisson regression was used to estimate the relative risk, with lag zero up to five days after exposure; the single pollutant model was adjusted by the apparent temperature, as defined from the temperature and relative air humidity, seasonality and weekday.

Results:

The values of the relative risks for hospitalization for pneumonia and asthma were significant for lag 0 (RR=1.051, 95%CI; 1.016 to 1.088); lag 2 (RR=1.066, 95%CI: 1.023 to 1.113); lag 3 (RR=1.053, 95%CI: 1.015 to 1.092); lag 4 (RR=1.043, 95%CI: 1.004 to 1.088) and lag 5 (RR=1.061, 95%CI: 1.018 to 1.106). The increase of 5mcg/m³ in PM_2.5 contributes to increase the relative risk for hospitalization from 20.3 to 38.4 percentage points; however, the reduction of 5µg/m³ in PM_2.5 concentration results in 38 fewer hospital admissions.

Conclusions:

Exposure to PM_2.5 was associated with hospitalizations for pneumonia and asthma in children younger than 10 years of age, showing the role of fine particulate matter in child health and providing subsidies for the implementation of preventive measures to decrease these outcomes.

Association between NOx exposure and deaths caused by respiratory diseases in a medium-sized Brazilian city

Exposure to nitrogen oxides (NOx) emitted by burning fossil fuels has been associated with respiratory diseases. We aimed to estimate the effects of NOx exposure on mortality owing to respiratory diseases in residents of Taubaté, São Paulo, Brazil, of all ages and both sexes. This time-series ecological study from August 1, 2011 to July 31, 2012 used information on deaths caused by respiratory diseases obtained from the Health Department of Taubaté. Estimated daily levels of pollutants (NOx, particulate matter, ozone, carbon monoxide) were obtained from the Centro de Previsão de Tempo e Estudos Climáticos Coupled Aerosol and Tracer Transport model to the Brazilian developments on the Regional Atmospheric Modeling System. These environmental variables were used to adjust the multipollutant model for apparent temperature. To estimate association between hospitalizations owing to asthma and air pollutants, generalized additive Poisson regression models were developed, with lags as much as 5 days. There were 385 deaths with a daily mean (±SD) of 1.05±1.03 (range: 0-5). Exposure to NOx was significantly associated with mortality owing to respiratory diseases: relative risk (RR)=1.035 (95% confidence interval [CI]: 1.008-1.063) for lag 2, RR=1.064 (95%CI: 1.017-1.112) lag 3, RR=1.055 (95%CI: 1.025-1.085) lag 4, and RR=1.042 (95%CI: 1.010-1.076) lag 5. A 3 µg/m³ reduction in NOx concentration resulted in a decrease of 10-18 percentage points in risk of death caused by respiratory diseases. Even at NOx concentrations below the acceptable standard, there is association with deaths caused by respiratory diseases.