Residential traffic exposure and lymphohematopoietic malignancies among children in the city of São Paulo, Brazil: An ecological study.

BACKGROUND: Despite widespread evidence that air pollution is carcinogenic, there is little evidence from low-middle income countries, especially related to childhood malignancies. We examined the role of traffic related pollution on lymphohematopoietic malignancies among under-14 s in Sao Paulo. METHODS: All incident cases between 2002 and 2011 were collected from a population-based registry. Exposures were assigned on residential address at diagnosis via traffic density database (for the year 2008) and a satellite derived NO2 land use regression model (averaged between 1997 and 2011). Incidence rate ratios (IRRs) were calculated via Poisson Regression adjusted by age, gender and socioeconomic status (SES), with additional stratification by SES. RESULTS: A positive association between traffic and NO2 with some lymphohematopoietic malignancies was observed with the degree of effect differing by SES. For example, lymphoid leukemia IRRs in the lower SES group were 1.21 (95 % CI: 1.06, 1.39) for traffic density and 1.38 (95 % CI: 1.13, 1.68) for NO2. In the higher group they were 1.06 (95 % CI: 1.00, 1.14) and 1.37 (95 % CI: 1.16, 1.62). CONCLUSION: NO2 and traffic density were associated with Hodgkin lymphoma and lymphoid leukemia among children in São Paulo. Differing IRRs by gender and SES group indicate differences in underlying risk and/or exposure profiles.

Long-term exposure to outdoor and household air pollution and blood pressure in the Prospective Urban and Rural Epidemiological (PURE) study

Exposure to air pollution has been linked to elevated blood pressure (BP) and hypertension, but most research has focused on short-term (hours, days, or months) exposures at relatively low concentrations. We examined the associations between long-term (3-year average) concentrations of outdoor PM2.5 and household air pollution (HAP) from cooking with solid fuels with BP and hypertension in the Prospective Urban and Rural Epidemiology (PURE) study. Outdoor PM2.5 exposures were estimated at year of enrollment for 137,809 adults aged 35­70 years from 640 urban and rural communities in 21 countries using satellite and ground-based methods. Primary use of solid fuel for cooking was used as an indicator of HAP exposure, with analyses restricted to rural participants (n = 43,313) in 27 study centers in 10 countries. BP was measured following a standardized procedure and associations with air pollution examined with mixed-effect regression models, after adjustment for a comprehensive set of potential confounding factors. Baseline outdoor PM2.5 exposure ranged from 3 to 97 µg/m3 across study communities and was associated with an increased odds ratio (OR) of 1.04 (95% CI: 1.01, 1.07) for hypertension, per 10 µg/m3 increase in concentration. This association demonstrated non-linearity and was strongest for the fourth (PM2.5 > 62 µg/m3) compared to the first (PM2.5 < 14 µg/m3) quartiles (OR = 1.36, 95% CI: 1.10, 1.69). Similar non-linear patterns were observed for systolic BP (ß = 2.15 mmHg, 95% CI: −0.59, 4.89) and diastolic BP (ß = 1.35, 95% CI: −0.20, 2.89), while there was no overall increase in ORs across the full exposure distribution. Individuals who used solid fuels for cooking had lower BP measures compared to clean fuel users (e.g. 34% of solid fuels users compared to 42% of clean fuel users had hypertension), and even in fully adjusted models had slightly decreased odds of hypertension (OR = 0.93; 95% CI: 0.88, 0.99) and reductions in systolic (−0.51 mmHg; 95% CI: −0.99, −0.03) and diastolic (−0.46 mmHg; 95% CI: −0.75, −0.18) BP. In this large international multi-center study, chronic exposures to outdoor PM2.5 was associated with increased BP and hypertension while there were small inverse associations with HAP.

Health effects of household solid fuel use: findings from 11 countries within the prospective urban and rural epidemiology study

Approximately 2.5 billion individuals globally are exposed to household air pollution (HAP) from cooking with solid fuels such as coal, wood, dung, or crop residues (Smith et al. 2014). Concentrations of air pollutants, especially fine particulate matter [PM≤2:5 lminaerodynamicdiameterðPM2:5)], can be several orders of magnitude higher in homes cooking with solid fuels compared with those using clean fuels such as electricity or liquefied petroleum gas (LPG) (Clark et al. 2013; Shupler et al. 2018). PM2:5 in outdoor air has been linked to mortality, Address correspondence to Perry Hystad, School of Public Health and Human Sciences, Oregon State University, Milam Hall 10, 2520 SW Campus Way, Corvallis, OR 97331 USA. Telephone: (541) 737-4829. Email: Perry. hystad@oregonstate.edu SupplementalMaterialisavailableonline(https://doi.org/10.1289/EHP3915). The authors declared hey have no actual or potential competing financial interests. Received 16 May 2018; Revised 16 April 2019; Accepted 16 April 2019; Published 8 May 2019. Note to readers with disabilities: EHP strives to ensure that all journal content is accessible to all readers. However, some figures and Supplemental Material published in EHP articles may not conform to 508 standards due to the complexity of the information being presented. If you need assistance accessing journal content, please contact ehponline@niehs.nih.gov. Our staff will work with you to assess and meet your accessibility needs within 3 working days.is chemic heart disease (IHD), stroke, and respiratory diseases (Kim et al. 2015). Despite the large population exposed and the potential for adverse health effects, few prospective cohort studies have examined the health effects of HAP. Only four studies have examined HAP and mortality and reached contradictory conclusions (Alam et al. 2012; Kim et al. 2016; Mitter et al. 2016; Yu et al. 2018). Further, studies have not examined HAP and fatal as well as nonfatal cardiovascular disease (CVD) events. There is growing evidence of the adverse effects of HAP on respiratory diseases and lung cancer; however, most studies are cross sectional or case control in design, with relatively small sample sizes and limited geographic coverage (Gordon et al. 2014). To date, few prospective studies have examined HAP exposures and respiratory events in adults, and the existing studies have reported contradictory findings (Chanetal.2019; Ezzati and Kammen 2001; Mitter et al. 2016). Given the absence of direct epidemiological data, the Global Burden of Disease (GBD) study estimated the potential impact of HAP on health using exposure response relationships that pooled data from studies on outdoor air pollution, secondhand smoke, and active smoking (Burnett et al. 2014). These predictions indicated that 1.6 million deaths were attributable to HAP exposure in 2017, of which 39% were from IHD and stroke and 55% from respiratory outcomes [>90% from chronic obstructive pulmonary disease (COPD) and acute lower respiratory infections (ALRI)] (GBD 2017 Risk Factor Collaborators 2018). Given the lack of direct epidemiological evidence and this large predicted burden, there is an urgent need to directly characterize the health effects associated with HAP. Within the Prospective Urban and Rural Epidemiology (PURE) study, we conducted an analysis of 91,350 adults from 467 urban and rural communities in 11 low to middle-income countries (LMICs) where solid fuels are commonly used for cooking. We examined associations between cooking with solid fuels as a proxy indicator of HAP exposure and cause specific mortality, incident cases of CVD [ CVD death and incidence of nonfatal myocardial infarction (MI), stroke, and heart failure (HF)] and incident cases of respiratory disease [respiratory death, nonfatal COPD, pulmonary tuberculosis (TB), pneumonia, or lung cancer].We estimated associations between solid fuel use for cooking and these outcomes, controlling for extensive individual, household, and community covariates. (AU)

Incidence and mortality for respiratory cancer and traffic-related air pollution in São Paulo, Brazil.

BACKGROUND: Multiple lines of evidence have associated exposure to ambient air pollution with an increased risk of respiratory malignancies. However, there is a dearth of evidence from low-middle income countries, including those within South America, where the social inequalities are more marked. OBJECTIVES: To quantify the association between exposures to traffic related air pollution and respiratory cancer incidence and mortality within São Paulo, Brazil. Further, we aim to investigate the role of socioeconomic status (SES) upon these outcomes. METHODS: Cancer incidence between 2002 and 2011 was derived from the population-based cancer registry. Mortality data (between 2002 and 2013) was derived from the Municipal Health Department. A traffic density database and an annual nitrogen dioxide (NO2) land use regression model were used as markers of exposure. Age-adjusted Binomial Negative Regression models were developed, stratifying by SES and gender. RESULTS: We observed an increased rate of respiratory cancer incidence and mortality in association with increased traffic density and NO2 concentrations, which was higher among those regions with the lowest SES. For cancer mortality and traffic exposure, those in the most deprived region, had an incidence rate ratio (IRR) of 2.19 (95% CI: 1.70, 2.82) when comparing the highest exposure centile (top 90%) to the lowest (lowest 25%). By contrast, in the least deprived area, the IRR for the same exposure contrast was.1.07 (95% CI: 0.95, 1.20). For NO2 in the most deprived regions, the IRR for cancer mortality in the highest exposed group was 1.44 (95% CI: 1.10, 1.88) while in the least deprived area, the IRR for the highest exposed group was 1.11 (95% CI: 1.01, 1.23). CONCLUSIONS: Traffic density and NO2 were associated with an increased rate of respiratory cancer incidence and mortality in São Paulo. Residents from poor regions may suffer more from the impact of traffic air pollution.

Land use regression models to assess air pollution exposure in Mexico City using finer spatial and temporal input parameters.

The Mexico City Metropolitan Area (MCMA) is one of the largest and most populated urban environments in the world and experiences high air pollution levels. To develop models that estimate pollutant concentrations at fine spatiotemporal scales and provide improved air pollution exposure assessments for health studies in Mexico City. We developed finer spatiotemporal land use regression (LUR) models for PM2.5, PM10, O3, NO2, CO and SO2 using mixed effect models with the Least Absolute Shrinkage and Selection Operator (LASSO). Hourly traffic density was included as a temporal variable besides meteorological and holiday variables. Models of hourly, daily, monthly, 6-monthly and annual averages were developed and evaluated using traditional and novel indices. The developed spatiotemporal LUR models yielded predicted concentrations with good spatial and temporal agreements with measured pollutant levels except for the hourly PM2.5, PM10 and SO2. Most of the LUR models met performance goals based on the standardized indices. LUR models with temporal scales greater than one hour were successfully developed using mixed effect models with LASSO and showed superior model performance compared to earlier LUR models, especially for time scales of a day or longer. The newly developed LUR models will be further refined with ongoing Mexico City air pollution sampling campaigns to improve personal exposure assessments.

Global Land Use Regression Model for Nitrogen Dioxide Air Pollution.

Nitrogen dioxide is a common air pollutant with growing evidence of health impacts independent of other common pollutants such as ozone and particulate matter. However, the worldwide distribution of NO2 exposure and associated impacts on health is still largely uncertain. To advance global exposure estimates we created a global nitrogen dioxide (NO2) land use regression model for 2011 using annual measurements from 5,220 air monitors in 58 countries. The model captured 54% of global NO2 variation, with a mean absolute error of 3.7 ppb. Regional performance varied from R2 = 0.42 (Africa) to 0.67 (South America). Repeated 10% cross-validation using bootstrap sampling (n = 10,000) demonstrated a robust performance with respect to air monitor sampling in North America, Europe, and Asia (adjusted R2 within 2%) but not for Africa and Oceania (adjusted R2 within 11%) where NO2 monitoring data are sparse. The final model included 10 variables that captured both between and within-city spatial gradients in NO2 concentrations. Variable contributions differed between continental regions, but major roads within 100 m and satellite-derived NO2 were consistently the strongest predictors. The resulting model can be used for global risk assessments and health studies, particularly in countries without existing NO2 monitoring data or models.