Ozone and fine particulate matter association with CVD and COPD emergency room visits in Harris County, Texas: Spatiotemporal analysis

This study represents a secondary analysis of the merging of emergency room visits and daily ozone and PM2.5. Although the adverse health effects of ozone and fine particulate matter have been documented in the literature, evidence regarding the health risks of these two pollutants in Harris County, Texas, is limited. Harris County (Houston) has sufficiently unique characteristics that analysis of these relationships in this setting and with the ozone and industry issues in Houston is informative. The objective of this study was to investigate the association between the joint exposure to ozone and fine particulate matter, and emergency room diagnoses of chronic obstructive pulmonary disease and cardiovascular disease in Harris County, Texas, from 2004 to 2009, with zero and one day lags. ^ The study variables were daily emergency room visits for Harris County, Texas, from 2004 to 2009, temperature, relative humidity, east wind component, north wind component, ozone, and fine particulate matter. Information about each patient's age, race, and gender was also included. The two dichotomous outcomes were emergency room visits diagnoses for chronic obstructive pulmonary disease and cardiovascular disease. Estimates of ozone and PM2.5 were interpolated using kriging, in which estimates of the two pollutants were predicted from monitoring data for every case residence zip code for every day of the six years, over 3 million estimates (one of each pollutant for each case in the database). ^ Logistic regressions were conducted to estimate odds ratios of the two outcomes. Three analyses were conducted: one for all records, another for visits during the four months of April and September of 2005 and 2009, and a third one for visits from zip codes that are close to PM2.5 monitoring stations (east area of Harris County). The last two analyses were designed to investigate special temporal and spatial characteristics of the associations. ^ The dataset included all ER visits surveyed by Safety Net from 2004 to 2009, exceeding 3 million visits for all causes. There were 95,765 COPD and 96,596 CVD cases during this six year period. A 1-μg/m3 increase in PM2.5 on the same day was associated with a 1.0% increase in the odds of chronic obstructive pulmonary disease emergency room diagnoses, a 0.4% increase in the odds of cardiovascular disease emergency room diagnoses, and a 0.2% increase in the odds of cardiovascular disease emergency room diagnoses on the following day. A 1-ppb increase in ozone was associated with a 0.1% increase in the odds of chronic obstructive pulmonary disease emergency room diagnoses on the same day. These four percentages add up to 1.7% of ER visits. That is, over the period of six years, one unit increase for both ozone and PM2.5 (joint increase), resulted in about 55,286 (3,252,102 * 0.017) extra ER visits for CVD or COPD, or 9,214 extra ER visits per year. ^ After adjustment for age, race, gender, day of the week, temperature, relative humidity, east wind component, north wind component, and wind speed, there were statistically significant associations between emergency room chronic obstructive pulmonary disease diagnosis in Harris County, Texas, with joint exposure to ozone and fine particulate matter for the same day; and between emergency room cardiovascular disease diagnosis and exposure to PM2.5 of the same day and the previous day. ^ Despite the small association between the two air pollutants and the health outcomes, this study points to important findings. Namely, the need to identify reasons for the increase of CVD and COPD ER visits over the course of the project, the statistical association between humidity (or whatever other variables for which it may serve as a surrogate) and CVD and COPD cases, and the confirmatory finding that males and blacks have higher odds for the two outcomes, as consistent with other studies. ^ An important finding of this research suggests that the number and distribution of PM2.5 monitors in Harris County - although not evenly spaced geographically—are adequate to detect significant association between exposure and the two outcomes. In addition, this study points to other potential factors that contribute to the rising incidence rates of CVD and COPD ER visits in Harris County such as population increases, patient history, life style, and other pollutants. Finally, results of validation, using a subset of the data demonstrate the robustness of the models.^

Fossil versus contemporary sources of fine elemental and organic carbonaceous particulate matter during the DAURE campaign in Northeast Spain

We present results from the international field campaign DAURE (Detn. of the sources of atm. Aerosols in Urban and Rural Environments in the Western Mediterranean), with the objective of apportioning the sources of fine carbonaceous aerosols. Submicron fine particulate matter (PM1) samples were collected during Feb.-March 2009 and July 2009 at an urban background site in Barcelona (BCN) and at a forested regional background site in Montseny (MSY). We present radiocarbon (14C) anal. for elemental and org. carbon (EC and OC) and source apportionment for these data. We combine the results with those from component anal. of aerosol mass spectrometer (AMS) measurements, and compare to levoglucosan-based ests. of biomass burning OC, source apportionment of filter data with inorg. compn. + EC + OC, submicron bulk potassium (K) concns., and gaseous acetonitrile concns. At BCN, 87 % and 91 % of the EC on av., in winter and summer, resp., had a fossil origin, whereas at MSY these fractions were 66 % and 79 %. The contribution of fossil sources to org. carbon (OC) at BCN was 40 % and 48 %, in winter and summer, resp., and 31 % and 25 % at MSY. The combination of results obtained using the 14C technique, AMS data, and the correlations between fossil OC and fossil EC imply that the fossil OC at Barcelona is ∼47 % primary whereas at MSY the fossil OC is mainly secondary (∼85 %). Day-to-day variation in total carbonaceous aerosol loading and the relative contributions of different sources predominantly depended on the meteorol. transport conditions. The estd. biogenic secondary OC at MSY only increased by ∼40 % compared to the order-of-magnitude increase obsd. for biogenic volatile org. compds. (VOCs) between winter and summer, which highlights the uncertainties in the estn. of that component. Biomass burning contributions estd. using the 14C technique ranged from similar to slightly higher than when estd. using other techniques, and the different estns. were highly or moderately correlated. Differences can be explained by the contribution of secondary org. matter (not included in the primary biomass burning source ests.), and/or by an over-estn. of the biomass burning OC contribution by the 14C technique if the estd. biomass burning EC/OC ratio used for the calcns. is too high for this region. Acetonitrile concns. correlate well with the biomass burning EC detd. by 14C. K is a noisy tracer for biomass burning. [on SciFinder(R)]

Characterization of Metal and Trace Element Contents of Particulate Matter (PM10) Emitted by Vehicles Running on Brazilian FuelsHydrated Ethanol and Gasoline with 22% of Anhydrous Ethanol

Emission of fine particles by mobile sources has been a matter of great concern due to its potential risk both to human health and the environment. Although there is no evidence that one sole component may be responsible for the adverse health outcomes, it is postulated that the metal particle content is one of the most important factors, mainly in relation to oxidative stress. Data concerning the amount and type of metal particles emitted by automotive vehicles using Brazilian fuels are limited. The aim of this study was to identify inhalable particles (PM10) and their trace metal content in two light-duty vehicles where one was fueled with ethanol while the other was fueled with gasoline mixed with 22% of anhydrous ethanol (gasohol); these engines were tested on a chassis dynamometer. The elementary composition of the samples was evaluated by the particle-induced x-ray emission technique. The experiment showed that total emission factors ranged from 2.5 to 11.8 mg/km in the gasohol vehicle, and from 1.2 to 3 mg/km in the ethanol vehicle. The majority of particles emitted were in the fine fraction (PM2.5), in which Al, Si, Ca, and Fe corresponded to 80% of the total weight. PM10 emissions from the ethanol vehicle were about threefold lower than those of gasohol. The elevated amount of fine particulate matter is an aggravating factor, considering that these particles, and consequently associated metals, readily penetrate deeply into the respiratory tract, producing damage to lungs and other tissues.

A QUANTITATIVE INVESTIGATION OF SOURCE AND ELEMENTAL COMPOSITION OF INDOOR AND OUTDOOR FINE PARTICULATE AIR POLLUTION IN HOUSTON (TEXAS)

An investigation was undertaken to determine the chemical characterization of inhalable particulate matter in the Houston area, with special emphasis on source identification and apportionment of outdoor and indoor atmospheric aerosols using multivariate statistical analyses.^ Fine (<2.5 (mu)m) particle aerosol samples were collected by means of dichotomous samplers at two fixed site (Clear Lake and Sunnyside) ambient monitoring stations and one mobile monitoring van in the Houston area during June-October 1981 as part of the Houston Asthma Study. The mobile van allowed particulate sampling to take place both inside and outside of twelve homes.^ The samples collected for 12-h sampling on a 7 AM-7 PM and 7 PM-7 AM (CDT) schedule were analyzed for mass, trace elements, and two anions. Mass was determined gravimetrically. An energy-dispersive X-ray fluorescence (XRF) spectrometer was used for determination of elemental composition. Ion chromatography (IC) was used to determine sulfate and nitrate.^ Average chemical compositions of fine aerosol at each site were presented. Sulfate was found to be the largest single component in the fine fraction mass, comprising approximately 30% of the fine mass outdoors and 12% indoors, respectively.^ Principal components analysis (PCA) was applied to identify sources of aerosols and to assess the role of meteorological factors on the variation in particulate samples. The results suggested that meteorological parameters were not associated with sources of aerosol samples collected at these Houston sites.^ Source factor contributions to fine mass were calculated using a combination of PCA and stepwise multivariate regression analysis. It was found that much of the total fine mass was apparently contributed by sulfate-related aerosols. The average contributions to the fine mass coming from the sulfate-related aerosols were 56% of the Houston outdoor ambient fine particulate matter and 26% of the indoor fine particulate matter.^ Characterization of indoor aerosol in residential environments was compared with the results for outdoor aerosols. It was suggested that much of the indoor aerosol may be due to outdoor sources, but there may be important contributions from common indoor sources in the home environment such as smoking and gas cooking. ^

Impact on human health of particulate matter emitted from burnings in the Brazilian Amazon region

OBJECTIVE: To analyze the impact on human health of exposure to particulate matter emitted from burnings in the Brazilian Amazon region. METHODS: This was an ecological study using an environmental exposure indicator presented as the percentage of annual hours (AH%) of PM2.5 above 80 μg/m3. The outcome variables were the rates of hospitalization due to respiratory disease among children, the elderly and the intermediate age group, and due to childbirth. Data were obtained from the National Space Research Institute and the Ministry of Health for all of the microregions of the Brazilian Amazon region, for the years 2004 and 2005. Multiple regression models for the outcome variables in relation to the predictive variable AH% of PM2.5 above 80 μg/m3 were analyzed. The Human Development Index (HDI) and mean number of complete blood counts per 100 inhabitants in the Brazilian Amazon region were the control variables in the regression analyses. RESULTS: The association of the exposure indicator (AH%) was higher for the elderly than for other age groups (β = 0.10). For each 1% increase in the exposure indicator there was an increase of 8% in child hospitalization, 10% in hospitalization of the elderly, and 5% for the intermediate age group, even after controlling for HDI and mean number of complete blood counts. No association was found between the AH% and hospitalization due to childbirth. CONCLUSIONS: The indicator of atmospheric pollution showed an association with occurrences of respiratory diseases in the Brazilian Amazon region, especially in the more vulnerable age groups. This indicator may be used to assess the effects of forest burning on human health.

Impact on human health of particulate matter emitted from burnings in the Brazilian Amazon region

OBJECTIVE: To analyze the impact on human health of exposure to particulate matter emitted from burnings in the Brazilian Amazon region. METHODS: This was an ecological study using an environmental exposure indicator presented as the percentage of annual hours (AH%) of PM2.5 above 80 μg/m3. The outcome variables were the rates of hospitalization due to respiratory disease among children, the elderly and the intermediate age group, and due to childbirth. Data were obtained from the National Space Research Institute and the Ministry of Health for all of the microregions of the Brazilian Amazon region, for the years 2004 and 2005. Multiple regression models for the outcome variables in relation to the predictive variable AH% of PM2.5 above 80 μg/m3 were analyzed. The Human Development Index (HDI) and mean number of complete blood counts per 100 inhabitants in the Brazilian Amazon region were the control variables in the regression analyses. RESULTS: The association of the exposure indicator (AH%) was higher for the elderly than for other age groups (β = 0.10). For each 1% increase in the exposure indicator there was an increase of 8% in child hospitalization, 10% in hospitalization of the elderly, and 5% for the intermediate age group, even after controlling for HDI and mean number of complete blood counts. No association was found between the AH% and hospitalization due to childbirth. CONCLUSIONS: The indicator of atmospheric pollution showed an association with occurrences of respiratory diseases in the Brazilian Amazon region, especially in the more vulnerable age groups. This indicator may be used to assess the effects of forest burning on human health.

Association between particulate matter from biomass burning and respiratory diseases in the southern region of the Brazilian Amazon

Objective. To investigate the short-term effects of exposure to particulate matter from biomass burning in the Amazon on the daily demand for outpatient care due to respiratory diseases in children and the elderly. Methods. Epidemiologic study with ecologic time series design. Daily consultation records were obtained from the 14 primary health care clinics in the municipality of Alta Floresta, state of Mato Grosso, in the southern region of the Brazilian Amazon, between January 2004 and December 2005. Information on the daily levels of fine particulate matter was made available by the Brazilian National Institute for Spatial Research. To control for confounding factors ( situations in which a non-causal association between exposure and disease is observed due to a third variable), variables related to time trends, seasonality, temperature, relative humidity, rainfall, and calendar effects ( such as occurrence of holidays and weekends) were included in the model. Poisson regression with generalized additive models was used. Results. A 10 mu g/m(3) increase in the level of exposure to particulate matter was associated with increases of 2.9% and 2.6% in outpatient consultations due to respiratory diseases in children on the 6th and 7th days following exposure. Significant associations were not observed for elderly individuals. Conclusions. The results suggest that the levels of particulate matter from biomass burning in the Amazon are associated with adverse effects on the respiratory health of children.

Burnt sugarcane harvesting: Particulate matter exposure and the effects on lung function, oxidative stress, and urinary 1-hydroxypyrene

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Real-time Sampling of Particulate Matter Smaller than 2.5 µm from Amazon Forest Biomass Combustion

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Burnt sugarcane harvesting: Particulate matter exposure and the effects on lung function, oxidative stress, and urinary 1-hydroxypyrene

Non-mechanised sugarcane harvesting preceded by burning exposes workers and the people of neighbouring towns to high concentrations of pollutants. This study was aimed to evaluate the respiratory symptoms, lung function and oxidative stress markers in sugarcane workers and the residents of Mendonca, an agricultural town in Brazil, during the non-harvesting and harvesting periods and to assess the population and individual exposures to fine particulate matter (PM2.5). Sugarcane workers and healthy volunteers were evaluated with two respiratory symptom questionnaires, spirometry, urinary 1-hydroxypyrene levels, and the measurement of antioxidant enzymes and plasma malonaldehyde during the non-harvesting and harvesting periods. The environmental assessment was determined from PM2.5 concentration. PM2.5 level increased from 8 mu g/m(3) during the non-harvesting period to 23.5 mu g/m(3) in the town and 61 mu g/m(3) on the plantations during the harvesting period. Wheezing, coughing, sneezing, and breathlessness increased significantly in both groups during the harvesting period, but more markedly in workers. A decrease in lung function and antioxidant enzyme activity was observed in both populations during harvesting; this decrease was greater among the sugarcane workers. The urinary 1-hydroxypyrene levels only increased in the sugarcane workers during the harvesting period. The malonaldehyde levels were elevated in both groups, with a higher increase observed in the workers. This research demonstrates the exposure of sugarcane workers and the inhabitants of a neighbouring town to high PM2.5 concentrations during the sugarcane harvest period. This exposure was higher among the sugarcane workers, as illustrated by both higher PM2.5 concentrations in the sugarcane fields and higher urinary 1-hydroxypyrene levels in the volunteers in this group. The higher incidence of respiratory symptoms, greater decrease in lung function and more marked elevation of oxidative stress markers among the sugarcane workers during the harvest confirms the greater effect magnitude in this population and a dose-dependent relationship between pollution and the observed effects. (C) 2012 Elsevier B.V. All rights reserved.

TRENDS IN PARTICULATE MATTER AND MORTALITY: AN APPROACH TO THE ASSESSMENT OF UNMEASURED CONFOUNDING

We propose a method for diagnosing confounding bias under a model which links a spatially and temporally varying exposure and health outcome. We decompose the association into orthogonal components, corresponding to distinct spatial and temporal scales of variation. If the model fully controls for confounding, the exposure effect estimates should be equal at the different temporal and spatial scales. We show that the overall exposure effect estimate is a weighted average of the scale-specific exposure effect estimates. We use this approach to estimate the association between monthly averages of fine particles (PM2.5) over the preceding 12 months and monthly mortality rates in 113 U.S. counties from 2000-2002. We decompose the association between PM2.5 and mortality into two components: 1) the association between “national trends” in PM2.5 and mortality; and 2) the association between “local trends,” defined as county-specificdeviations from national trends. This second component provides evidence as to whether counties having steeper declines in PM2.5 also have steeper declines in mortality relative to their national trends. We find that the exposure effect estimates are different at these two spatio-temporalscales, which raises concerns about confounding bias. We believe that the association between trends in PM2.5 and mortality at the national scale is more likely to be confounded than is the association between trends in PM2.5 and mortality at the local scale. If the association at the national scale is set aside, there is little evidence of an association between 12-month exposure to PM2.5 and mortality.

MORTALITY IN THE MEDICARE POPULATION AND CHRONIC EXPOSURE TO FINE PARTICULATE AIR POLLUTION

Prospective cohort studies have provided evidence on longer-term mortality risks of fine particulate matter (PM2.5), but due to their complexity and costs, only a few have been conducted. By linking monitoring data to the U.S. Medicare system by county of residence, we developed a retrospective cohort study, the Medicare Air Pollution Cohort Study (MCAPS), comprising over 20 million enrollees in the 250 largest counties during 2000-2002. We estimated log-linear regression models having as outcome the age-specific mortality rate for each county and as the main predictor, the average level for the study period 2000. Area-level covariates were used to adjust for socio-economic status and smoking. We reported results under several degrees of adjustment for spatial confounding and with stratification into by eastern, central and western counties. We estimated that a 10 µg/m3 increase in PM25 is associated with a 7.6% increase in mortality (95% CI: 4.4 to 10.8%). We found a stronger association in the eastern counties than nationally, with no evidence of an association in western counties. When adjusted for spatial confounding, the estimated log-relative risks drop by 50%. We demonstrated the feasibility of using Medicare data to establish cohorts for follow-up for effects of air pollution. Particulate matter (PM) air pollution is a global public health problem (1). In developing countries, levels of airborne particles still reach concentrations at which serious health consequences are well-documented; in developed countries, recent epidemiologic evidence shows continued adverse effects, even though particle levels have declined in the last two decades (2-6). Increased mortality associated with higher levels of PM air pollution has been of particular concern, giving an imperative for stronger protective regulations (7). Evidence on PM and health comes from studies of acute and chronic adverse effects (6). The London Fog of 1952 provides dramatic evidence of the unacceptable short-term risk of extremely high levels of PM air pollution (8-10); multi-site time-series studies of daily mortality show that far lower levels of particles are still associated with short-term risk (5)(11-13). Cohort studies provide complementary evidence on the longer-term risks of PM air pollution, indicating the extent to which exposure reduces life expectancy. The design of these studies involves follow-up of cohorts for mortality over periods of years to decades and an assessment of mortality risk in association with estimated long-term exposure to air pollution (2-4;14-17). Because of the complexity and costs of such studies, only a small number have been conducted. The most rigorously executed, including the Harvard Six Cities Study and the American Cancer Society’s (ACS) Cancer Prevention Study II, have provided generally consistent evidence for an association of long- term exposure to particulate matter air pollution with increased all-cause and cardio-respiratory mortality (2,4,14,15). Results from these studies have been used in risk assessments conducted for setting the U.S. National Ambient Air Quality Standard (NAAQS) for PM and for estimating the global burden of disease attributable to air pollution (18,19). Additional prospective cohort studies are necessary, however, to confirm associations between long-term exposure to PM and mortality, to broaden the populations studied, and to refine estimates by regions across which particle composition varies. Toward this end, we have used data from the U.S. Medicare system, which covers nearly all persons 65 years of age and older in the United States. We linked Medicare mortality data to (particulate matter less than 2.5 µm in aerodynamic diameter) air pollution monitoring data to create a new retrospective cohort study, the Medicare Air Pollution Cohort Study (MCAPS), consisting of 20 million persons from 250 counties and representing about 50% of the US population of elderly living in urban settings. In this paper, we report on the relationship between longer-term exposure to PM2.5 and mortality risk over the period 2000 to 2002 in the MCAPS.

Vehicle emissions and PM2.5 mass concentrations in six Brazilian cities

In Brazil, the principal source of air pollution is the combustion of fuels (ethanol, gasohol, and diesel). In this study, we quantify the contributions that vehicle emissions make to the urban fine particulate matter (PM2.5) mass in six state capitals in Brazil, collecting data for use in a larger project evaluating the impact of air pollution on human health. From winter 2007 to winter 2008, we collected 24-h PM2.5 samples, employing gravimetry to determine PM2.5 mass concentrations; reflectance to quantify black carbon concentrations; X-ray fluorescence to characterize elemental composition; and ion chromatography to determine the composition and concentrations of anions and cations. Mean PM2.5 concentrations in the cities of Sao Paulo, Rio de Janeiro, Belo Horizonte, Curitiba, Porto Alegre, and Recife were 28, 17.2, 14.7, 14.4, 13.4, and 7.3 mu g/m(3), respectively. In Sao Paulo and Rio de Janeiro, black carbon explained approximately 30% of the PM2.5 mass. We used receptor models to identify distinct source-related PM2.5 fractions and correlate those fractions with daily mortality rates. Using specific rotation factor analysis, we identified the following principal contributing factors: soil and crustal material; vehicle emissions and biomass burning (black carbon factor); and fuel oil combustion in industries (sulfur factor). In all six cities, vehicle emissions explained at least 40% of the PM2.5 mass. Elemental composition determination with receptor modeling proved an adequate strategy to identify air pollution sources and to evaluate their short- and long-term effects on human health. Our data could inform decisions regarding environmental policies vis-a-vis health care costs.