A study of health effect estimates using competing methods to model personal exposures to ambient PM2.5

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.     

Personal and ambient air pollution exposures and lung function decrements in children with asthma

BACKGROUND: Epidemiologic studies have shown associations between asthma outcomes and outdoor air pollutants such as nitrogen dioxide and particulate matter mass < 2.5 mum in diameter (PM(2.5)). Independent effects of specific pollutants have been difficult to detect because most studies have relied on highly correlated central-site measurements. OBJECTIVES: This study was designed to evaluate the relationship of daily changes in percent-predicted forced expiratory volume in 1 sec (FEV(1)) with personal and ambient air pollutant exposures. METHODS: For 10 days each, we followed 53 subjects with asthma who were 9-18 years of age and living in the Los Angeles, California, air basin. Subjects self-administered home spirometry in themorning, afternoon, and evening. We measured personal hourly PM(2.5) mass, 24-hr PM(2.5) elemental and organic carbon (EC-OC), and 24-hr NO(2), and the same 24-hr average outdoor central-site(ambient) exposures. We analyzed data with transitional mixed models controlling for personal temperature and humidity, and as-needed beta(2)-agonist inhaler use. RESULTS: FEV(1) decrements were significantly associated with increasing hourly peak and daily average personal PM(2.5), but not ambient PM(2.5). Personal NO(2) was also inversely associated with FEV(1). Ambient NO(2) was more weakly associated. We found stronger associations among 37 subjects not taking controller bronchodilators as follows: Personal EC-OC was inversely associated with morning FEV(1); for an interquartile increase of 71 mug/m(3) 1-hr maximum personal PM(2.5), overall percent-predicted FEV(1) decreased by 1.32% [95% confidence interval (CI), -2.00 to -0.65%]; and for an interquartile increase of 16.8 ppb 2-day average personal NO(2), overall percent-predicted FEV(1) decreased by 2.45% (95% CI, -3.57 to -1.33%). Associations of both personal PM(2.5) and NO(2) with FEV(1) remained when co-regressed, and both confounded ambient NO(2). CONCLUSIONS: Independent pollutant associations with lung function might be missed using ambient data alone. Different sets of causal components are suggested by independence of FEV(1) associations with personal PM(2.5) mass from associations with personal NO(2).     

Exposure to fine particles (PM2.5 and PM1) and black smoke in the general population: personal, indoor, and outdoor levels

Personal exposure to PM(2.5) and PM(1), together with indoor and residential outdoor levels, was measured in the general adult population (30 subjects, 23-51 years of age) of Gothenburg, Sweden. Simultaneously, urban background concentrations of PM(2.5) were monitored with an EPA WINS impactor. The 24-h samples were gravimetrically analyzed for mass concentration and black smoke (BS) using a smokestain reflectometer. Median levels of PM(2.5) were 8.4 microg/m(3) (personal), 8.6 microg/m(3) (indoor), 6.4 microg/m(3) (residential outdoor), and 5.6 microg/m(3) (urban background). Personal exposure to PM(1) was 5.4 microg/m(3), while PM(1) indoor and outdoor levels were 6.2 and 5.2 microg/m(3), respectively. In non-smokers, personal exposure to PM(2.5) was significantly higher than were residential outdoor levels. BS absorption coefficients were fairly similar for all microenvironments (0.4-0.5 10(-5) m(-1)). Personal exposure to particulate matter (PM) and BS was well correlated with indoor levels, and there was an acceptable agreement between personal exposure and urban background concentrations for PM(2.5) and BS(2.5) (r(s)=0.61 and 0.65, respectively). PM(1) made up a considerable amount (70-80%) of PM(2.5) in all microenvironments. Levels of BS were higher outdoors than indoors and higher during the fall compared with spring. The correlations between particle mass and BS for both PM(2.5) vs. BS(2.5) and PM(1) versus BS(1) were weak for all microenvironments including personal exposure. The urban background station provided a good estimate of residential outdoor levels of PM(2.5) and BS(2.5) within the city (r(s)=0.90 and 0.77, respectively). Outdoor levels were considerably affected by long-range transported air pollution, which was not found for personal exposure or indoor levels. The within-individual (day-to-day) variability dominated for personal exposure to both PM(2.5) and BS(2.5) in non-smokers.     

Exposure of chronic obstructive pulmonary disease patients to particles: respiratory and cardiovascular health effects.

To examine hypotheses regarding air pollution health effects, we conducted an exploratory study to evaluate relationships between personal and ambient concentrations of particles with measures of cardiopulmonary health in a sample of patients with chronic obstructive pulmonary disease (COPD). Sixteen currently non-smoking COPD patients (mean age=74) residing in Vancouver were equipped with a particle (PM(2.5)) monitor for seven 24-h periods. Subjects underwent ambulatory heart monitoring, had their lung function and blood pressure (BP) measured, and recorded symptoms and medication use. Ambient PM(2.5), PM(10), sulfate, and gaseous pollutant concentrations were monitored at five sites within the study area. Although no associations between air pollution and lung function were statistically significant, an estimated effect of 3% and 1% declines in daily FEV(1) change (DeltaFEV(1)) for each 10 microg/m(3) increase in ambient PM(10) and PM(2.5), respectively, was observed. Increases of 1 microg/m(3) in personal or ambient sulfate were associated with 1.0% and 0.3% declines in DeltaFEV(1), respectively. Weak associations were observed between particle concentrations and increased supraventricular ectopic heartbeats and with decreased systolic BP. No consistent associations were observed between any particle metric and diastolic BP, heart rate, or heart rate variability (r-MSSD or SDNN), symptom severity, or bronchodilator use. Of the pollutants measured, ambient PM(10) was most consistently associated with health parameters; the use of personal exposures did not improve the strength of any associations or lead to increased effect estimates.     

Influence of ambient (outdoor) sources on residential indoor and personal PM2.5 concentrations: analyses of RIOPA data

The Relationship of Indoor, Outdoor and Personal Air (RIOPA) study was designed to investigate residential indoor, outdoor and personal exposures to several classes of air pollutants, including volatile organic compounds, carbonyls and fine particles (PM2.5). Samples were collected from summer, 1999 to spring, 2001 in Houston (TX), Los Angeles (CA) and Elizabeth (NJ). Indoor, outdoor and personal PM2.5 samples were collected at 212 nonsmoking residences, 162 of which were sampled twice. Some homes were chosen due to close proximity to ambient sources of one or more target analytes, while others were farther from sources. Median indoor, outdoor and personal PM2.5 mass concentrations for these three sites were 14.4, 15.5 and 31.4 microg/m3, respectively. The contributions of ambient (outdoor) and nonambient sources to indoor and personal concentrations were quantified using a single compartment box model with measured air exchange rate and a random component superposition (RCS) statistical model. The median contribution of ambient sources to indoor PM2.5 concentrations using the mass balance approach was estimated to be 56% for all study homes (63%, 52% and 33% for California, New Jersey and Texas study homes, respectively). Reasonable variations in model assumptions alter median ambient contributions by less than 20%. The mean of the distribution of ambient contributions across study homes agreed well for the mass balance and RCS models, but the distribution was somewhat broader when calculated using the mass balance model with measured air exchange rates.     

Gaseous pollutants in particulate matter epidemiology: confounders or surrogates?

Air pollution epidemiologic studies use ambient pollutant concentrations as surrogates of personal exposure. Strong correlations among numerous ambient pollutant concentrations, however, have made it difficult to determine the relative contribution of each pollutant to a given health outcome and have led to criticism that health effect estimates for particulate matter may be biased due to confounding. In the current study we used data collected from a multipollutant exposure study conducted in Baltimore, Maryland, during both the summer and winter to address the potential for confounding further. Twenty-four-hour personal exposures and corresponding ambient concentrations to fine particulate matter (PM(2.5)), ozone, nitrogen dioxide, sulfur dioxide, and carbon monoxide were measured for 56 subjects. Results from correlation and regression analyses showed that personal PM(2.5) and gaseous air pollutant exposures were generally not correlated, as only 9 of the 178 individual-specific pairwise correlations were significant. Similarly, ambient concentrations were not associated with their corresponding personal exposures for any of the pollutants, except for PM(2.5), which had significant associations during both seasons (p < 0.0001). Ambient gaseous concentrations were, however, strongly associated with personal PM(2.5) exposures. The strongest associations were shown between ambient O(3) and personal PM(2.5) (p < 0.0001 during both seasons). These results indicate that ambient PM(2.5) concentrations are suitable surrogates for personal PM(2.5) exposures and that ambient gaseous concentrations are surrogates, as opposed to confounders, of PM(2.5). These findings suggest that the use of multiple pollutant models in epidemiologic studies of PM(2.5) may not be suitable and that health effects attributed to the ambient gases may actually be a result of exposures to PM(2.5).     

Personal PM2.5 exposure and markers of oxidative stress in blood

Ambient particulate air pollution assessed as outdoor concentrations of particulate matter less than or equal to 2.5 micro m in diameter (PM(2.5)) in urban background has been associated with cardiovascular diseases at the population level. However, the significance of individual exposure and the involved mechanisms remain uncertain. We measured personal PM(2.5) and carbon black exposure in 50 students four times in 1 year and analyzed blood samples for markers of protein and lipid oxidation, for red blood cell (RBC) and platelet counts, and for concentrations of hemoglobin and fibrinogen. We analyzed protein oxidation in terms of gamma-glutamyl semialdehyde in hemoglobin (HBGGS) and 2-aminoadipic semialdehyde in hemoglobin (HBAAS) and plasma proteins (PLAAS), and lipid peroxidation was measured as malondialdehyde (MDA) in plasma. Median exposures were 16.1 micro g/m(3) for personal PM(2.5) exposure, 9.2 micro g/m(3) for background PM(2.5) concentration, and 8.1 X 10(-6)/m for personal carbon black exposure. Personal carbon black exposure and PLAAS concentration were positively associated (p < 0.01), whereas an association between personal PM(2.5) exposure and PLAAS was only of borderline significance (p = 0.061). A 3.7% increase in MDA concentrations per 10 micro g/m(3) increase in personal PM(2.5) exposure was found for women (p < 0.05), whereas there was no significant relationship for the men. Similarly, positive associations between personal PM(2.5)exposure and both RBC and hemoglobin concentrations were found only in women (p < 0.01). There were no significant relationships between background PM(2.5) concentration and any of the biomarkers. This suggests that exposure to particles in moderate concentrations can induce oxidative stress and increase RBCs in peripheral blood. Personal exposure appears more closely related to these biomarkers potentially related to cardiovascular disease than is ambient PM(2.5) background concentrations.     

Effects of exposure measurement error on particle matter epidemiology: a simulation using data from a panel study in Baltimore, MD

Ascertaining the true risk associated with exposure to particulate matter (PM) is difficult, given the fact that pollutant components are frequently correlated with each other and with other gaseous pollutants; relationships between ambient concentrations and personal exposures are often not well understood; and PM, unlike its gaseous co-pollutants, does not represent a single chemical. In order to examine differences between observed versus true health risk estimate from epidemiologic studies, we conducted a simulation using data from a recent multi-pollutant exposure assessment study in Baltimore, MD. The objectives of the simulation were twofold: (a) to estimate the distribution of personal air pollutant exposures one might expect to observe within a population, given the corresponding ambient concentrations found in that location and; (b) using an assumed true health risk with exposure to one pollutant, to estimate the distribution of health risk estimates likely to be observed in an epidemiologic study using ambient pollutant concentrations as a surrogate of exposure as compared with actual personal pollutant exposures. Results from the simulations showed that PM2.5 was the only pollutant where a true association with its total personal exposures resulted in a significant observed association with its ambient concentrations. The simulated results also showed that true health risks associated with personal exposure to O3 and NO2 would result in no significant observed associations with any of their respective ambient concentrations. Conversely, a true association with PM2.5 would result in a significant, observed association with NO2 (beta=0.0115, 95% confidence interval (CI): 0.0056, 0.0185) and a true association with exposure to SO4(2-) would result in an observed significant association with O3 (beta=0.0035, 95% CI: 0.0021, 0.0051) given the covariance of the ambient pollutant concentrations. The results provide an indication that, in Baltimore during this study period, ambient gaseous concentrations may not have been adequate surrogates for corresponding personal gaseous exposures to allow the question to be investigated using central site monitors. Alternatively, the findings may suggest that in some locations, observed associations with the gaseous pollutants should be interpreted with caution, as they may be reflecting associations with PM or one of its chemical components.     

大学生公寓内PM2.5暴露水平影响因素分析

探讨室外环境与室内人员活动/行为对大学生公寓内细颗粒物PM2.5污染的影响,为保护大学生身体健康提供科学依据.方法 对北京市大兴区某高校校园9间大学生公寓室内外PM2.5浓度实时连续监测7d,同时对大学生的时间一行为活动模式进行问卷调查.结果 公寓是大学生最主要的室内活动场所,每天在公寓内的时间为13.30h,占55.4%.公寓内PM2.5日均体积质量比范围为39.3 ~ 584.1μg/m3,超标率为66.7%~85.7%;室外PM2.5日均体积质量比范围为76.5~493.2 μg/m3,超标率为100%;室内外日均PM2.5体积质量比I/O比均值为0.84.相关分析结果表明,公寓内PM2.5浓度与室外浓度、室内外温差、室外相对湿度、风速的相关均有统计学意义(r值分别为0.792,-0.535,0.634,-0.547,P值均<0.01).公寓内人员活动/行为影响室内PM2.5浓度和I/O比(P值均<0.05).结论 在室外环境条件和室内人员的综合影响下,大学生公寓内PM2.5污染严重.应采取适当措施降低大学生公寓内PM2.5暴露水平.     

Fine particulate matter (PM2.5) air pollution and selected causes of postneonatal infant mortality in California

Studies suggest that airborne particulate matter (PM) may be associated with postneonatal infant mortality, particularly with respiratory causes and sudden infant death syndrome (SIDS). To further explore this issue, we examined the relationship between long-term exposure to fine PM air pollution and postneonatal infant mortality in California. We linked monitoring data for PM相似文献   

合肥市大气PM2.5污染与居民呼吸系统疾病住院量的关系

目的 探讨合肥市大气PM2.5暴露对居民呼吸系统疾病住院量的影响。方法 收集合肥市2019年逐日大气污染物监测资料、气象资料及呼吸系统疾病住院资料。采用基于Poisson分布的GAM模型,评估PM2.5暴露对居民呼吸系统疾病住院量的影响。计算PM2.5浓度每升高10 μg/m3,居民呼吸系统疾病住院量增加的超额风险(ER)及95%可信区间（95%CI）。结果 合肥市大气PM2.5污染对居民呼吸系统疾病住院量存在显著影响。PM2.5每升高10 μg/m3,单日滞后效应和累积滞后效应分别在lag5和lag07时达到最大,居民呼吸系统疾病总住院量分别增加0.95% (95%CI:0.21% ~ 1.70%)和3.48% (95%CI:1.65% ~ 5.33%)。PM2.5对14岁及以下儿童的影响较其他年龄人群明显,对女性的影响也大于男性。结论 合肥市大气PM2.5浓度升高可能会增加居民呼吸系统疾病住院量,14岁及以下儿童及女性更敏感。     

Personal exposure to PM2.5, black smoke and NO2 in Copenhagen: relationship to bedroom and outdoor concentrations covering seasonal variation

Epidemiological studies have found negative associations between human health and particulate matter in urban air. In most studies outdoor monitoring of urban background has been used to assess exposure. In a field study, personal exposure as well as bedroom, front door and background concentrations of PM(2.5), black smoke (BS), and nitrogen dioxide (NO(2)) were measured during 2-day periods in 30 subjects (20-33 years old) living and studying in central parts of Copenhagen. The measurements were repeated in the four seasons. Information on indoor exposure sources such as environmental tobacco smoke (ETS) and burning of candles was collected by questionnaires. The personal exposure, the bedroom concentration and the front door concentration was set as outcome variable in separate models and analysed by mixed effect model regression methodology, regarding subject levels as a random factor. Seasons were defined as a dichotomised grouping of outdoor temperature (above and below 8 degrees C). For NO(2) there was a significant association between personal exposure and both the bedroom, the front door and the background concentrations, whereas for PM(2.5) and BS only the bedroom and the front door concentrations, and not the background concentration, were significantly associated to the personal exposure. The bedroom concentration was the strongest predictor of all three pollution measurements. The association between the bedroom and front door concentrations was significant for all three measurements, and the association between the front door and the background concentrations was significant for PM(2.5) and NO(2), but not for BS, indicating greater spatial variation for BS than for PM(2.5) and NO(2). For NO(2), the relationship between the personal exposure and the front door concentration was dependent upon the "season", with a stronger association in the warm season compared with the cold season, and for PM(2.5) and BS the same tendency was seen. Time exposed to burning of candles was a significant predictor of personal PM(2.5), BS and NO(2) exposure, and time exposed to ETS only associated with personal PM(2.5) exposure. These findings imply that the personal exposure to PM(2.5), BS and NO(2) depends on many factors besides the outdoor levels, and that information on, for example, time of season or outdoor temperature and residence exposure, could improve the accuracy of the personal exposure estimation.     

Ozone and PM2.5 exposure and acute pulmonary health effects: a study of hikers in the Great Smoky Mountains National Park

To address the lack of research on the pulmonary health effects of ozone and fine particulate matter (相似文献   

Determinants of personal and indoor PM2.5 and absorbance among elderly subjects with coronary heart disease

Epidemiological studies have established an association between outdoor levels of fine particles (PM2.5) and cardiovascular health. However, there is little information on the determinants of PM2.5 exposures among persons with cardiovascular disease, a potentially susceptible population group. Daily outdoor, indoor and personal PM2.5 and absorbance (proxy for elemental carbon) concentrations were measured among elderly subjects with cardiovascular disease in Amsterdam, the Netherlands, and Helsinki, Finland, during the winter and spring of 1998-1999 within the framework of the ULTRA study. There were 37 non-smoking subjects in Amsterdam and 47 in Helsinki. In Amsterdam, where there were enough exposure events for analyses, exposure to environmental tobacco smoke (ETS) indoors was a major source of between-subject variation in PM2.5 exposures, and a strong determinant of PM2.5 and absorbance exposures. When the days with ETS were excluded, within-subject variation accounted for 89% of the total variation in personal PM2.5 and 97% in absorbance in Amsterdam. The respective figures were 66% and 61% in Helsinki. In both cities, outdoor levels of PM2.5 and absorbance were major determinants of personal and indoor levels. Traffic was also an important determinant of absorbance: living near a major street increased exposure by 22%, and every hour spent in a motor vehicle by 13% in Amsterdam. The respective increases were 37% and 9% in Helsinki. Cooking was associated with increased levels of both absorbance and PM2.5. Our results demonstrate that by using questionnaires in connection with outdoor measurements, exposure estimation of PM2.5 and its combustion originating fraction can be improved among elderly persons with compromised health.     

Comparison of PM2.5 and PM10 monitors

An extensive PM monitoring study was conducted during the 1998 Baltimore PM Epidemiology-Exposure Study of the Elderly. One goal was to investigate the mass concentration comparability between various monitoring instrumentation located across residential indoor, residential outdoor, and ambient sites. Filter-based (24-h integrated) samplers included Federal Reference Method Monitors (PM2.5-FRMs), Personal Environmental Monitors (PEMs), Versatile Air Pollution Samplers (VAPS), and cyclone-based instruments. Tapered element oscillating microbalances (TEOMs) collected real-time data. Measurements were collected on a near-daily basis over a 28-day period during July-August, 1998. The selected monitors had individual sampling completeness percentages ranging from 64% to 100%. Quantitation limits varied from 0.2 to 5.0 microg/m3. Results from matched days indicated that mean individual PM10 and PM2.5 mass concentrations differed by less than 3 microg/m3 across the instrumentation and within each respective size fraction. PM10 and PM2.5 mass concentration regression coefficients of determination between the monitors often exceeded 0.90 with coarse (PM10-2.5) comparisons revealing coefficients typically well below 0.40. Only one of the outdoor collocated PM2.5 monitors (PEM) provided mass concentration data that were statistically different from that produced by a protoype PM2.5 FRM sampler. The PEM had a positive mass concentration bias ranging up to 18% relative to the FRM prototype.     

Ambient gas concentrations and personal particulate matter exposures: implications for studying the health effects of particles

BACKGROUND: Data from a previous study conducted in Baltimore, MD, showed that ambient fine particulate matter less than 2.5 mum in diameter (PM2.5) concentrations were strongly correlated with corresponding personal PM2.5 exposures, whereas ambient O3, NO2, and SO2 concentrations were weakly correlated with their personal exposures to these gases. In contrast, many of the ambient gas concentrations were reasonable surrogates of personal PM2.5 exposures. METHODS: Personal multipollutant exposures and corresponding ambient air pollution concentrations were measured for 43 subjects living in Boston, MA. The cohort consisted of 20 healthy senior citizens and 23 schoolchildren. Simultaneous 24-hour integrated PM2.5, O3, NO2, and SO2 personal exposures and ambient concentrations were measured. All PM2.5 samples were also analyzed for SO4 (sulfate). We analyzed personal exposure and ambient concentration data using correlation and mixed model regression analyses to examine relationships among (1) ambient PM2.5 concentrations and corresponding ambient gas concentrations; (2) ambient PM2.5 and gas concentrations and their respective personal exposures; (3) ambient gas concentrations and corresponding personal PM2.5 exposures; and (4) personal PM2.5 exposures and corresponding personal gas exposures. RESULTS: We found substantial correlations between ambient PM2.5 concentrations and corresponding personal exposures over the course of time. Additionally, our results support the earlier finding that summertime gaseous pollutant concentrations may be better surrogates of personal PM2.5 exposures (especially personal exposures to PM2.5 of ambient origin) than they are surrogates of personal exposures to the gases themselves. CONCLUSIONS: Particle health effects studies that include both ambient PM2.5 and gaseous concentrations as independent variables must be analyzed carefully and interpreted cautiously, since both parameters may be serving as surrogates for PM2.5 exposures.     

Sociodemographic descriptors of personal exposure to fine particles (PM2.5) in EXPOLIS Helsinki

Demographic and socioeconomic differences between population sub-groups were analyzed, as a component of the EXPOLIS (Air Pollution Exposure Distributions Within Adult Urban Populations in Europe) Helsinki study, to explain variation in personal exposures to fine particles (PM2.5). Two-hundred one individuals were randomly selected among 25--55-year-old inhabitants of Helsinki Metropolitan area. Personal exposure samples and residential indoor, residential outdoor and workplace indoor microenvironment measurements of PM2.5 were collected between October 1996 and December 1997. Variation in PM2.5 personal exposures, between sociodemographic sub-groups, was best described by differences in occupational status, education and age. Lower occupational status, less educated and young participants had greater exposures than upper occupational status, more educated and older participants. Different workplace concentrations explained most of the socioeconomic differences, and personal day and night exposures and concentrations in home (but not workplace or outdoor concentrations) caused the PM2.5 exposure differences between age groups. Men had higher exposures and much larger exposure differences between the sociodemographic groups than women. No gender, socioeconomic or age differences were observed in home outdoor concentrations between groups. Exposure to tobacco smoke did not seem to create new differences between the sociodemographic groups; instead, it amplified the existing differences.