| Literature DB >> 33567063 |
Ubiratan de Paula Santos1, Marcos Abdo Arbex2,3, Alfésio Luis Ferreira Braga3,4, Rafael Futoshi Mizutani5, José Eduardo Delfini Cançado6, Mário Terra-Filho7, José Miguel Chatkin8,9.
Abstract
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.Entities:
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Year: 2021 PMID: 33567063 PMCID: PMC7889311 DOI: 10.36416/1806-3756/e20200267
Source DB: PubMed Journal: J Bras Pneumol ISSN: 1806-3713 Impact factor: 2.624
Major risk factors for, and their impact on, morbidity and mortality worldwide in 2017 according to the Global Burden of Disease 2017 Risk Factor Collaborators.
| Risk factors | Deaths × 1,000 (95% CI) | DALYs × 1,000 (95% CI) | Global ranking |
|---|---|---|---|
| Diet (all causes) | 10,900 (10,100-11,700) | 255,000 (234,000-274,000) | 1 |
| Hypertension | 10,400 (9,400-11,500) | 218,000 (198,000-237,000) | 2 |
| Smoking (active + environmental + smokeless) | 8,100 (7,800-8,420) | 213,000 (201,000-227,000) | 3 |
| Elevated fasting blood glucose levels | 6,530 (5,230-8,230) | 171,000 (144,000-201,000) | 4 |
| Air pollution (total) | 4,900 (4,400-5,400) | 147,000 (132,000-162,000) | 5 |
| Environmental air pollution (PM2.5) | 2,940 (2,500-3,360) | 83,000 (71,400-94,300) | |
| Environmental air pollution (ozone) | 472 (177-768) | 7,370 (2,740-12,000) | |
| Household air pollution | 1,640 (1,400-1,930) | 59,500 (50,800-68,900) |
PM2.5: fine particulate matter < 2.5 µm in aerodynamic diameter; DALYs: disability-adjusted life years (the sum of the number of years of life lost due to premature death and the number of years lived with limitation/disability). In air pollution-related deaths and air pollution-related DALYs, the sum of the separate impacts of the pollutants is slightly higher than the sum of their combined impact.
Estimates of deaths and disease burden associated with air pollution: global data for 2017 according to the Global Burden of Disease 2017 Risk Factor Collaborators.
| Pollutants and diseases | Environmental air pollution: PM2.5 | Household air pollution | ||
|---|---|---|---|---|
| Deaths × 1,000 (95% CI) | DALYs × 1,000 (95% CI) | Deaths × 1,000 (95% CI) | DALYs × 1,000 (95% CI) | |
| COPDa | 1,105 (583-1,606) | 23,070 (13,040-32,800) | 362 (248-482) | 9,370 (6,480-12,400) |
| Ischemic heart disease | 977 (839-1,120) | 21,900 (18,900-25,400) | 410 (344- 490) | 10,200 (8,450-12,100) |
| Ischemic brain disease | 445 (343-552) | 10,510 (8,189-13,020) | 231 (178-293) | 5,761 (4,493-7,417) |
| Respiratory infections | 433 (343-527) | 18,500 (14,400-23,400) | 459 (367-552) | 25,900 (20,300-31,300) |
| Lung cancer | 265 (183-351) | 5,860 (4,050-7,730) | 85 (60-113) | 1,990 (1,410-2,640) |
| Type 2 diabetes | 184 (123-227) | 10,500 (6,700-13,900) | 92 (63-113) | 4,750 (3,110-6,190) |
| Cataracts | - | - | - | 1,440 (732-2,250) |
| Total | 3,412 (2,677-4,168) | 147,000 (132,000-162,000) | 1,640 (1,400-1,930) | 59,500 (50,800-68,900) |
PM2.5: fine particulate matter < 2.5 µm in aerodynamic diameter; DALYs: disability-adjusted life years (the sum of the number of years of life lost due to premature death and the number of years lived with limitation/disability). aOzone was responsible for 472,000 (95% CI: 177,000 to 768,000) deaths and 7.37 million (95% CI: 2.74 to 12.00 million) DALYs.
Figure 1A representation of diseases and changes associated with air pollution. Adapted from Peters et al.
Major studies on air pollution, predominantly from vehicular and industrial sources, and respiratory diseases conducted in Brazil.
| Authors | Population and setting | Outcome | Exposure | Results |
|---|---|---|---|---|
| Sobral | Children in the city of São Paulo, located in the state of São Paulo | Respiratory diseases | Air pollution | Increased respiratory diseases in more polluted areas |
| Saldiva et al. | Rats in the cities of São Paulo and Atibaia, both located in the state of São Paulo | Changes in the mucociliary system | Environmental air in the two cities | Changes in the mucus and cilia and increased mortality from respiratory diseases in the city of São Paulo |
| Saldiva et al. | Children aged 5 years or younger in the city of São Paulo | Mortality from respiratory diseases | Measured primary pollutants | An association between NOx and increased mortality |
| Saldiva et al. | Elderly individuals > 65 years old in the greater metropolitan area of São Paulo | Mortality from respiratory diseases | PM10, NOX, SO2, and CO | Increased deaths associated with increased air pollutant levels |
| Souza et al. | Autopsy in individuals who died a violent death. Smokers in the city of Ourinhos (mean, 31 years) and nonsmokers in the city of Guarulhos (mean, 26 years), both located in the state of São Paulo | Lung histopathologic changes | Tobacco and air pollution | Comparison of lung injury between nonsmokers in the more polluted city (Guarulhos) and smokers in the less polluted city (Ourinhos) |
| Lin et al. | Children and adolescents in the city São Paulo | Emergency room visits | Measured air pollutants | Increased visits associated with PM10 and O3 |
| Braga et al. | Children aged 12 years or younger in the city of São Paulo | Hospitalizations for respiratory diseases | PM10, SO2, NO2, CO, and O3 | An association between hospitalization and air pollutants |
| Braga et al. | Individuals aged 19 years or younger in the city of São Paulo | Hospitalizations for respiratory diseases | PM10, SO2, NO2, CO, and O3 | An increased risk in children ≤ 2 years and adolescents aged 14 to 19 years |
| Conceição et al. | Children aged 5 years or younger in the city of São Paulo | Mortality from respiratory diseases | Primary and secondary pollutants | A mortality increase associated with increases in CO, SO2, and PM10 |
| Martins et al. | Elderly individuals in the city of São Paulo | Mortality from respiratory diseases | Primary and secondary pollutants | An association between PM10 and increased numbers of deaths; more deaths in those with a lower socioeconomic status |
| Mauad et al. | Mice in the city of São Paulo | Lung development | Air pollution | Exposure to PM and decreases in inspiratory and expiratory lung volumes |
| Arbex et al. | Adults and elderly individuals in the city of São Paulo | Emergency room visits | Air pollutants | Increased visits by elderly individuals and women |
| Riva et al. | Mice (an experimental study) | Inflammatory changes in the lung | Inhaled fine PM | Low concentrations of PM2.5 induce oxidative stress and inflammation in the lung. |
| Santos et al. | Workers exposed to environmental air pollution | Lung function | Individual exposure to PM2.5 | Reduced FVC and increased FEF25-75% |
| Gouveia et al. | Individuals of all ages and children less than 5 years old | Hospitalizations for respiratory diseases | PM10 | Increased hospitalizations in all age groups and in children less than 5 years old |
| de Barros Mendes Lopes et al. | Mice: exposure during pregnancy and after birth (São Paulo) | Lung formation and growth | PM2.5 | Exposure leads to a reduced number of alveoli and impaired lung function in adult mice. |
PM10: particulate matter with an aerodynamic diameter less than 10 µm; PM2.5: particulate matter with an aerodynamic diameter less than 2.5 µm; and NOx: nitrogen oxides.
Major studies on air pollution, especially from biomass burning, and respiratory diseases conducted in Brazil.
| Authors | Population and setting | Outcome | Exposure | Results |
|---|---|---|---|---|
| Arbex et al. | Population in the city of Araraquara, located in the state of Sâo Paulo | Use of medication by the population (inhalation therapy) | TSP | Increased visits for inhalation therapy during the sugarcane burning season |
| Cançado et al. | Children and elderly individuals in the city of Piracicaba, located in the state of São Paulo | Hospitalization for respiratory disease | PM2.5, PM10 | Increased hospitalizations on more polluted days; major effects during the sugarcane burning season |
| Arbex et al. | Population in the city of Araraquara | Hospitalization for asthma | TSP | Increased hospitalizations on more polluted days and during the sugarcane burning season; a 50% increase in hospitalizations during the sugarcane burning season |
| do Carmo et al. | Children and elderly individuals in Alta Floresta, a town in the state of Mato Grosso | Outpatient treatment for respiratory disease | PM2.5 from forest burning | Increased visits by children but not by elderly individuals |
| Ignotti et al. | Children and elderly individuals in microregions of the Brazilian Amazon | Hospitalization for respiratory disease | PM2.5 > 80 µg/m3 | Increased hospitalizations in children and elderly individuals |
| Rodrigues et al. | Elderly individuals in the Brazilian Amazon | Hospitalization for asthma | Dry season vs. wet season | Hospitalization rates are three times higher during the dry season than during the wet season. |
| Riguera et al. | Schoolchildren aged 10 to 14 years in Monte Aprazível, a town in the state of São Paulo | Asthma and rhinitis symptoms, PEF | PM2.5 and black carbon | Increased symptoms of asthma and rhinitis; a higher prevalence of rhinitis during the sugarcane burning season; decreased PEF |
| Goto et al. | Sugarcane workers in Cerquilho, a town in the state of São Paulo | Mucociliary clearance | Sugarcane burning | Impaired clearance and changes in mucus properties |
| Prado et al. | Sugarcane workers and residents of Mendonça, a town in the state of São Paulo | Lung function, respiratory symptoms, oxidative stress markers | Sugarcane burning | Reduced lung function, increased respiratory symptoms, and increased oxidative stress during the harvest season |
| Silva et al. | Children and elderly individuals in the city of Cuiabá, located in the state of Mato Grosso | Hospitalization | PM2.5 | Increased hospitalizations in children but not in elderly individuals |
| Arbex et al. | Population in the city of Araraquara | Emergency room visit for pneumonia | TSP | An increased effect of exposure during the sugarcane burning season |
| Jacobson et al. | Schoolchildren aged 6 to 15 years in the city of Tangará da Serra, located in the state of Mato Grosso | Lung function | PM10 and PM2.5 | Decreases in PEF |
| Mazzoli-Rocha et al. | Mice, cities of São Paulo and Araraquara, both located in the state of São Paulo | Lung resistance, lung elastance, and lung inflammation | Repeated instillation of PM | PM from sugarcane burning is more toxic than is PM from vehicular sources. |
| de Oliveira Alves et al. | Lung cells, the Amazon region | Cell toxicity | PM during burning in the Amazon forest | Increased levels of reactive oxygen species, inflammatory cytokines, DNA damage, apoptosis, and necrosis |
TSP: total suspended particles; PM10: particulate matter with an aerodynamic diameter less than 10 µm; and PM2.5: particulate matter with an aerodynamic diameter less than 2.5 µm.