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Ming Xie,
Teresa L. Coons,
Joshua G. Hermann,
Steven J. Dutton,
Jana B. Milford,
Jennifer L. Peel,
Shelly L. Miller,
Sun-Young Kim, Sverre Vedal,
Lianne Sheppard,
Michael P. Hannigan
Atmospheric Environment 12/2012; 60:305-315. · 3.46 Impact Factor
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ABSTRACT: To evaluate the utility and consistency of different speciation data sets in source apportionment of PM(2.5), positive matrix factorization (PMF) coupled with a bootstrap technique for uncertainty assessment was applied to four different 1-year data sets composed of bulk species, bulk species and water-soluble elements (WSE), bulk species and organic molecular markers (OMM), and all species. The five factors resolved by using only the bulk species best reproduced the observed concentrations of PM(2.5) components. Combining WSE with bulk species as PMF inputs also produced five factors. Three of them were linked to soil, road dust, and processed dust, and together contributed 26.0% of reconstructed PM(2.5) mass. A 7-factor PMF solution was identified using speciated OMM and bulk species. The EC/sterane and summertime/selective aliphatic factors had the highest contributions to EC (39.0%) and OC (53.8%), respectively. The nine factors resolved by including all species as input data are consistent with those from the previous two solutions (WSE and bulk species, OMM and bulk species) in both factor profiles and contributions (r = 0.88-1.00). The comparisons across different solutions indicate that the selection of input data set may depend on the PM components or sources of interest for specific source-oriented health study.
Environmental Science & Technology 09/2012; · 4.80 Impact Factor
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ABSTRACT: Background: In air pollution time-series studies, the temporal pattern of the association of fine particulate matter (PM2.5; particulate matter ≤ 2.5 µm in aerodynamic diameter) and health end points has been observed to vary by disease category. The lag pattern of PM2.5 chemical constituents has not been well investigated, largely because daily data have not been available.Objectives: We explored the lag structure for hospital admissions using daily PM2.5 chemical constituent data for 5 years in the Denver Aerosol Sources and Health (DASH) study.Methods: We measured PM2.5 constituents, including elemental carbon, organic carbon, sulfate, and nitrate, at a central residential site from 2003 through 2007 and linked these daily pollution data to daily hospital admission counts in the five-county Denver metropolitan area. Total hospital admissions and subcategories of respiratory and cardiovascular admissions were examined. We assessed the lag structure of relative risks (RRs) of hospital admissions for PM2.5 and four constituents on the same day and from 1 to 14 previous days from a constrained distributed lag model; we adjusted for temperature, humidity, longer-term temporal trends, and day of week using a generalized additive model.Results: RRs were generally larger at shorter lags for total cardiovascular admissions but at longer lags for total respiratory admissions. The delayed lag pattern was particularly prominent for asthma. Elemental and organic carbon generally showed more immediate patterns, whereas sulfate and nitrate showed delayed patterns.Conclusion: In general, PM2.5 chemical constituents were found to have more immediate estimated effects on cardiovascular diseases and more delayed estimated effects on respiratory diseases, depending somewhat on the constituent.
Environmental Health Perspectives 05/2012; 120(8):1094-9. · 7.04 Impact Factor
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ABSTRACT: To investigate chronic obstructive pulmonary disease (COPD) mortality among textile workers.
A total of 267,400 Chinese female textile employees were monitored for COPD mortality from 1989 to 2000. Textile factories in the cohort were classified into 10 industrial sectors. Age-adjusted mortality, standardized mortality ratios (SMRs) and 95% CIs were calculated by sector. In addition, RRs (HRs) adjusted for smoking and age were calculated for exposure to cotton and silk textile work compared with the other sectors in the cohort.
A majority of textile sectors had lower or similar COPD mortality (age-adjusted SMRs=0.58-1.15) compared with the general female population in the city of Nanjing, China. SMRs for cotton and silk workers were, respectively, 1.02 (95% CI: 0.81 to 1.28) and 2.03 (95% CI: 1.13 to 3.34). Compared with all other textile sectors in the cohort, there was greater COPD mortality among cotton workers (HR=1.40, 95% CI: 1.03 to 1.89) and silk workers (HR=2.54, 95% CI: 1.47 to 4.39).
Elevated COPD mortality among cotton workers is consistent with previous reports of adverse respiratory effects of cotton dust. The higher rate of COPD deaths among silk workers was unexpected.
Occupational and environmental medicine 04/2011; 68(12):883-7. · 3.64 Impact Factor
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ABSTRACT: A pilot study tested the feasibility of conducting occupational health research in Bangladesh while examining prevalence of asbestos-related diseases including asbestosis, work-related respiratory symptoms, and attitudes to occupational health and safety among a group of internal migrant ship breakers. Data was collected on clinical and work history, respiratory symptoms, and occupational health and safety practices in Bengali. A B-reader read all postero-anterior chest x-rays. In the 104 male ship breakers studied, prevalence of asbestos-related disease was 12 %, of which asbestosis accounted for 6%. Knowledge of asbestos and occupational health and safety measures were almost nonexistent. The prevalence of asbestos-related diseases is low compared to studies in shipbuilders and repairers, but a risk underestimate could have resulted from challenges identified during study design and implementation including: industry noncooperation and a culture of corruption; technological and language barriers; and a regional lack of physician knowledge and research on occupational diseases.
International journal of occupational and environmental health 03/2011; 17(2):144-153. · 1.03 Impact Factor
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ABSTRACT: Particulate air pollution is associated with cardiovascular morbidity. One hypothesized mechanism involves oxidative stress, systemic inflammation, and endothelial dysfunction.
To assess an intervention's impact on particle exposures and endothelial function among healthy adults in a woodsmoke-impacted community. We also investigated the underlying role of oxidative stress and inflammation in relation to exposure reductions.
Portable air filters were used in a randomized crossover intervention study of 45 healthy adults exposed to consecutive 7-day periods of filtered and nonfiltered air.
Reactive hyperemia index was measured as an indicator of endothelial function via peripheral artery tonometry, and markers of inflammation (C-reactive protein, interleukin-6, and band cells) and lipid peroxidation (malondialdehyde and 8-iso-prostaglandin F(2α)) were quantified. Air filters reduced indoor fine particle concentrations by 60%. Filtration was associated with a 9.4% (95% confidence interval, 0.9-18%) increase in reactive hyperemia index and a 32.6% (4.4-60.9%) decrease in C-reactive protein. Decreases in particulate matter and the woodsmoke tracer levoglucosan were associated with reduced band cell counts. There was limited evidence of more pronounced effects on endothelial function and level of systemic inflammation among males, overweight participants, younger participants, and residents of wood-burning homes. No associations were noted for oxidative stress markers.
Air filtration was associated with improved endothelial function and decreased concentrations of inflammatory biomarkers but not markers of oxidative stress. Our results support the hypothesis that systemic inflammation and impaired endothelial function, both predictors of cardiovascular morbidity, can be favorably influenced by reducing indoor particle concentrations.
American Journal of Respiratory and Critical Care Medicine 01/2011; 183(9):1222-30. · 11.08 Impact Factor
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ABSTRACT: Particulate matter less than 2.5 microns in diameter (PM(2.5)) has been linked with a wide range of adverse health effects. Determination of the sources of PM(2.5) most responsible for these health effects could lead to improved understanding of the mechanisms of such effects and more targeted regulation. This has provided the impetus for the Denver Aerosol Sources and Health (DASH) study, a multi-year source apportionment and health effects study relying on detailed inorganic and organic PM(2.5) speciation measurements.In this study, PM(2.5) source apportionment is performed by coupling positive matrix factorization (PMF) with daily speciated PM(2.5) measurements including inorganic ions, elemental carbon (EC) and organic carbon (OC), and organic molecular markers. A qualitative comparison is made between two models, PMF2 and ME2, commonly used for solving the PMF problem. Many previous studies have incorporated chemical mass balance (CMB) for organic molecular marker source apportionment on limited data sets, but the DASH data set is large enough to use multivariate factor analysis techniques such as PMF.Sensitivity of the PMF2 and ME2 models to the selection of speciated PM(2.5) components and model input parameters was investigated in depth. A combination of diagnostics was used to select an optimum, 7-factor model using one complete year of daily data with pointwise measurement uncertainties. The factors included 1) a wintertime/methoxyphenol factor, 2) an EC/sterane factor, 3) a nitrate/polycyclic aromatic hydrocarbon (PAH) factor, 4) a summertime/selective aliphatic factor, 5) an n-alkane factor, 6) a middle oxygenated PAH/alkanoic acid factor and 7) an inorganic ion factor. These seven factors were qualitatively linked with known PM(2.5) emission sources with varying degrees of confidence. Mass apportionment using the 7-factor model revealed the contribution of each factor to the mass of OC, EC, nitrate and sulfate. On an annual basis, the majority of OC and EC mass was associated with the summertime/selective aliphatic factor and the EC/sterane factor, respectively, while nitrate and sulfate mass were both dominated by the inorganic ion factor. This apportionment was found to vary substantially by season. Several of the factors identified in this study agree well with similar assessments conducted in St. Louis, MO and Pittsburgh, PA using PMF and organic molecular markers.
Atmospheric Environment 07/2010; 44(23):2731-2741. · 3.46 Impact Factor
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ABSTRACT: Ambient air pollution is always encountered as a complex mixture, but past regulatory and research strategies largely focused on single pollutants, pollutant classes, and sources one-at-a-time. There is a trend toward managing air quality in a progressively "multipollutant" manner, with the idealized goal of controlling as many air contaminants as possible in an integrated manner to achieve the greatest total reduction of adverse health and environmental impacts. This commentary considers the current ability of the environmental air pollution exposure and health research communities to provide evidence to inform the development of multipollutant air quality management strategies and assess their effectiveness. The commentary is not a literature review, but a summary of key issues and information gaps, strategies for filling the gaps, and realistic expectations for progress that could be made during the next decade. The greatest need is for researchers and sponsors to address air quality health impacts from a truly multipollutant perspective, and the most limiting current information gap is knowledge of personal exposures of different subpopulations, considering activities and microenvironments. Emphasis is needed on clarifying the roles of a broader range of pollutants and their combinations in a more forward-looking manner; that is not driven by current regulatory structures. Although advances in research tools and outcome data will enhance progress, the greater need is to direct existing capabilities toward strategies aimed at placing into proper context the contributions of multiple pollutants and their combinations to the health burdens, and the relative contributions of pollutants and other factors influencing the same outcomes. The authors conclude that the research community has very limited ability to advise multipollutant air quality management and assess its effectiveness at this time, but that considerable progress can be made in a decade, even at current funding levels, if resources and incentives are shifted appropriately.
Inhalation Toxicology 06/2010; 22 Suppl 1:1-19. · 1.92 Impact Factor
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ABSTRACT: Airborne particulate matter less than 2.5 μm in aerodynamic diameter (PM2.5) has been linked to a wide range of adverse health effects and as a result is currently regulated by the U.S. Environmental Protection Agency. PM2.5 originates from a multitude of sources and has heterogeneous physical and chemical characteristics. These features complicate the link between PM2.5 emission sources, ambient concentrations and health effects. The goal of the Denver Aerosol Sources and Health (DASH) study is to investigate associations between sources and health using daily measurements of speciated PM2.5 in Denver. The datxa set being collected for the DASH study will be the longest daily speciated PM2.5 data set of its kind covering 5.5 years of daily inorganic and organic speciated measurements. As of 2008, 4.5 years of bulk measurements (mass, inorganic ions and total carbon) and 1.5 years of organic molecular marker measurements have been completed. Several techniques were used to reveal long-term and short-term temporal patterns in the bulk species and the organic molecular marker species. All species showed a strong annual periodicity, but their monthly and seasonal behavior varied substantially. Weekly periodicities appear in many compound classes with the most significant weekday/weekend effect observed for elemental carbon, cholestanes, hopanes, select polycyclic aromatic hydrocarbons (PAHs), heavy n-alkanoic acids and methoxyphenols. Many of the observed patterns can be explained by meteorology or anthropogenic activity patterns while others do not appear to have such obvious explanations. Similarities and differences in these findings compared to those reported from other cities are highlighted.
Atmospheric Environment 03/2010; 44(7):987-998. · 3.46 Impact Factor
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Sverre Vedal
Occupational and environmental medicine 12/2009; 66(12):787-8. · 3.64 Impact Factor
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Sverre Vedal
Epidemiology (Cambridge, Mass.) 10/2009; 20(5):687-8. · 5.51 Impact Factor
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ABSTRACT: Particulate matter less than 2.5 microns in diameter (PM(2.5)) has been shown to have a wide range of adverse health effects and consequently is regulated in accordance with the US-EPA's National Ambient Air Quality Standards. PM(2.5) originates from multiple primary sources and is also formed through secondary processes in the atmosphere. It is plausible that some sources form PM(2.5) that is more toxic than PM(2.5) from other sources. Identifying the responsible sources could provide insight into the biological mechanisms causing the observed health effects and provide a more efficient approach to regulation. This is the goal of the Denver Aerosol Sources and Health (DASH) study, a multi-year PM(2.5) source apportionment and health study.The first step in apportioning the PM(2.5) to different sources is to determine the chemical make-up of the PM(2.5). This paper presents the methodology used during the DASH study for organic speciation of PM(2.5). Specifically, methods are covered for solvent extraction of non-polar and semi-polar organic molecular markers using gas chromatography-mass spectrometry (GC-MS). Vast reductions in detection limits were obtained through the use of a programmable temperature vaporization (PTV) inlet along with other method improvements. Results are presented for the first 1.5 years of the DASH study revealing seasonal and source-related patterns in the molecular markers and their long-term correlation structure. Preliminary analysis suggests that point sources are not a significant contributor to the organic molecular markers measured at our receptor site. Several motor vehicle emission markers help identify a gasoline/diesel split in the ambient data. Findings show both similarities and differences when compared with other cities where similar measurements and assessments have been made.
Atmospheric Environment 04/2009; 43(12):2018-2030. · 3.46 Impact Factor
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ABSTRACT: Many studies have identified associations between adverse health effects and short-term exposure to particulate matter less than 2.5 microns in diameter (PM(2.5)). These effects, however, are not consistent across geographical regions. This may be due in part to variations in the chemical make-up of PM(2.5) resulting from unique combinations of sources, both primary and secondary, in different regions. The Denver Aerosol Sources and Health (DASH) study is a multi-year time series study designed to characterize the daily chemical composition of PM(2.5) in Denver, identify the major contributing sources, and investigate associations between sources and a broad array of adverse health outcomes.Measurement methodology, field blank correction, pointwise uncertainty estimation and detection limit consideration are discussed in the context of bulk speciation for the DASH study. Results are presented for the first 4.5 years of mass, inorganic ion and bulk carbon speciation. The derived measurement uncertainties were propagated using the root sum of squares method and show good agreement with precision estimates derived from bi-weekly duplicate samples collected on collocated samplers. Gravimetric mass has the most uncertainty of any measurement and reconstructed mass generated from the sum of the individual species shows less uncertainty than measured mass on average. The methods discussed provide a good framework for PM(2.5) speciation measurements and are generalizable to analysis of other environmental measures.
Atmospheric Environment 02/2009; 43(5):1136-1146. · 3.46 Impact Factor
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ABSTRACT: The Clean Air Act mandates the U.S. Environmental Protection Agency to periodically reassess existing and new science that underlie the regulation of major ambient pollutants -- particulate matter (PM) and tropospheric ozone being most notable. While toxic effects have been ascribed individually to these and other pollutants in the air, it is clear that mixtures of these contaminants have the potential to interact and thereby influence their overall toxic outcomes. It follows that a more comprehensive assessment of the potential health effects of the air pollution complex might better protect human health; however, traditional regulatory drivers and funding constraints have impeded progress to such a goal. Despite difficulties in empirically conducting studies of complex mixtures of air pollutants and acquiring relevant exposure data, there remains a need to develop integrated, interdisciplinary research and analytical strategies to provide more comprehensive (and relevant) assessments of associated health outcomes and risks. The research and assessment communities are endeavoring to dissect this complexity using varied approaches Here we present five interdisciplinary perspectives of this evolving line of thought among researchers and those who use such data in assessment: (1) analyses that coordinate air quality-health analyses utilizing representative polluted U.S. air sheds to apportion source and component-specific health risks; (2) novel approaches to characterize air quality in terms of emission sources and how emission reduction strategies might effectively impact pollutant levels; (3) insights from present-day studies of effects of single ambient pollutants in animal and controlled clinical toxicology studies and how these are evolving to address air pollution; (4) refinements in epidemiologic health assessments that take advantage of the complexities of existent air quality conditions; and (5) new approaches to integrative analyses to establish the criteria for regulation of PM and other criteria pollutants. As these examples illustrate, implementing multidisciplined and integrative strategies offer the promise of more realistic and relevant science, greater reductions in uncertainty, and improved overall air pollution assessment. The regulatory mandate may lag behind the science, but real gains both in public health benefit and the science to dissect complex problems will result.
Toxicological Sciences 01/2008; 100(2):318-27. · 4.65 Impact Factor
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ABSTRACT: Various methods have been developed recently to estimate personal exposures to ambient particulate matter less than 2.5 microm in diameter (PM2.5) using fixed outdoor monitors as well as personal exposure monitors. One class of estimators involves extrapolating values using ambient-source components of PM2.5, such as sulfate and iron. A key step in extrapolating these values is to correct for differences in infiltration characteristics of the component used in extrapolation (such as sulfate within PM2.5) and PM2.5. When this is not done, resulting health effect estimates will be biased. Another class of approaches involves factor analysis methods such as positive matrix factorization (PMF). Using either an extrapolation or a factor analysis method in conjunction with regression calibration allows one to estimate the direct effects of ambient PM2.5 on health, eliminating bias caused by using fixed outdoor monitors and estimated personal ambient PM2.5 concentrations. Several forms of the extrapolation method are defined, including some new ones. Health effect estimates that result from the use of these methods are compared with those from an expanded PMF analysis using data collected from a health study of asthmatic children conducted in Denver, Colorado. Examining differences in health effect estimates among the various methods using a measure of lung function (forced expiratory volume in 1 s) as the health indicator demonstrated the importance of the correction factor(s) in the extrapolation methods and that PMF yielded results comparable with the extrapolation methods that incorporated correction factors.
Journal of Exposure Science and Environmental Epidemiology 10/2007; 17(6):549-58. · 2.93 Impact Factor
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Judith C Chow,
John G Watson,
Joe L Mauderly,
Daniel L Costa,
Ronald E Wyzga, Sverre Vedal,
George M Hidy,
Sam L Altshuler,
David Marrack,
Jon M Heuss,
George T Wolff,
C Arden Pope,
Douglas W Dockery
Journal of the Air & Waste Management Association 11/2006; 56(10):1368-80. · 1.67 Impact Factor
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ABSTRACT: The use of biomass as a cooking fuel is commonplace in developing countries and has been associated with chronic bronchitis and obstructive airway disease.
A cross-sectional survey was done in the village of Solis, close to Mexico City. Lifelong nonsmoking women 38 yr of age or older (n=841) completed a questionnaire on respiratory symptoms and illnesses and on cooking fuel use, and performed spirometry in their homes. Particulate matter concentration was measured with a nephelometer in the kitchen for 1 h, while the subject was cooking.
The peak indoor concentration of particulate matter (PM10, particles with a diameter of 10 microm or less) often exceeded 2 mg/m3. Compared with those cooking with gas, current use of a stove burning biomass fuel was associated with increased reporting of phlegm (27 vs. 9%) and reduced FEV1/FVC (79.9 vs. 82.8%). Levels of FEV1 were 81 ml lower and cough was more common (odds ratio, 1.7; 95% confidence interval, 1.0-2.8) in women from homes with higher PM10 concentrations. All women found with moderate airflow obstruction (Global Initiative for Chronic Obstructive Lung Disease stage II and above) were cooking with biomass stoves.
Women cooking with biomass fuels have increased respiratory symptoms and a slight average reduction in lung function compared with those cooking with gas.
American Journal of Respiratory and Critical Care Medicine 11/2006; 174(8):901-5. · 11.08 Impact Factor
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ABSTRACT: Unusual air pollution episodes, such as when smoke from wildfires covers a large urban area, can be used to attempt to detect associations between short-term increases in particulate matter (PM) concentrations and subsequent mortality without relying on the sophisticated statistical models that are typically required in the absence of such episodes. The objective of this study was to explore whether acute increases in PM concentrations from wildfire smoke cause acute increases in daily mortality. The temporal patterns of daily nonaccidental deaths and daily cardiorespiratory deaths for June of 2002 in the Denver metropolitan area were examined and compared to those in two nearby counties in Colorado that were not affected by the wildfire smoke and to daily deaths in Denver in June of 2001. Abrupt increases in PM concentrations in Denver occurred on 2 days in June of 2002 as a result of wildfire smoke drifting over the Denver area. Small peaks in mortality corresponded to both of the PM peaks, but the first mortality peak also corresponded to a peak of mortality in the control counties, and cardiorespiratory deaths began to increase on the day before the second peak. Further, there was no detectable increase in cardiorespiratory deaths in the hours immediately following the PM peaks. Although the findings from this study do not rule out the possibility of small increases in mortality due to abrupt and dramatic increases in PM concentrations from wildfire smoke, in a population of over 2 million people no perceptible increases in daily mortality could be attributed to such events.
Environmental Research 10/2006; 102(1):29-35. · 3.40 Impact Factor
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ABSTRACT: Most air pollution and health studies conducted in recent years have examined how a health outcome is related to pollution concentrations from a fixed outdoor monitor. The pollutant effect estimate in the health model used indicates how ambient pollution concentrations are associated with the health outcome, but not how actual exposure to ambient pollution is related to health. In this article, we propose a method of estimating personal exposures to ambient PM(2.5) (particulate matter less than 2.5 microm in diameter) using sulfate, a component of PM(2.5) that is derived primarily from ambient sources. We demonstrate how to use regression calibration in conjunction with these derived values to estimate the effects of personal ambient PM(2.5) exposure on a continuous health outcome, forced expiratory volume in 1 s (FEV(1)), using repeated measures data. Through simulation, we show that a confidence interval (CI) for the calibrated estimator based on large sample theory methods has an appropriate coverage rate. In an application using data from our health study involving children with moderate to severe asthma, we found that a 10 microg/m3 increase in PM(2.5) was associated with a 2.2% decrease in FEV(1) at a 1-day lag of the pollutant (95% CI: 0.0-4.3% decrease). Regressing FEV(1) directly on ambient PM(2.5) concentrations from a fixed monitor yielded a much weaker estimate of 1.0% (95% CI: 0.0-2.0% decrease). Relatively small amounts of personal monitor data were needed to calibrate the estimate based on fixed outdoor concentrations.
Journal of Exposure Science and Environmental Epidemiology 02/2006; 16(1):30-8. · 2.93 Impact Factor
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ABSTRACT: Most air pollution and health studies conducted in recent years have examined how a health outcome is related to pollution concentrations from a fixed outdoor monitor. The pollutant effect estimate in the health model used indicates how ambient pollution concentrations are associated with the health outcome, but not how actual exposure to ambient pollution is related to health. In this article, we propose a method of estimating personal exposures to ambient PM2.5 (particulate matter less than 2.5 m in diameter) using sulfate, a component of PM2.5 that is derived primarily from ambient sources. We demonstrate how to use regression calibration in conjunction with these derived values to estimate the effects of personal ambient PM2.5 exposure on a continuous health outcome, forced expiratory volume in 1 s (FEV1), using repeated measures data. Through simulation, we show that a confidence interval (CI) for the calibrated estimator based on large sample theory methods has an appropriate coverage rate. In an application using data from our health study involving children with moderate to severe asthma, we found that a 10 g/m3 increase in PM2.5 was associated with a 2.2% decrease in FEV1 at a 1-day lag of the pollutant (95% CI: 0.0–4.3% decrease). Regressing FEV1 directly on ambient PM2.5 concentrations from a fixed monitor yielded a much weaker estimate of 1.0% (95% CI: 0.0–2.0% decrease). Relatively small amounts of personal monitor data were needed to calibrate the estimate based on fixed outdoor concentrations.Keywords: sulfate, asthma, measurement error, air pollution, particulate matter.
Journal of Exposure Science and Environmental Epidemiology 07/2005; 16(1):30-38. · 2.93 Impact Factor
