The relationship between averaged sulfate exposures and concentrations: results from exposure assessment panel studies in four U.S. cities

Indoor (residential) and ambient particulate matter associations with urinary oxidative stress biomarkers in a COPD cohort

OBJECTIVES

Oxidative stress contributes to chronic obstructive pulmonary disease (COPD) pathophysiology. Associations between indoor (residential) exposure to particulate matter ≤2.5 μm in diameter (PM2.5) and one of its components, black carbon (BC), and oxidative stress are ill-defined.

METHODS

Between 2012 and 2017, 140 patients with COPD completed in-home air sampling over one week intervals, followed by collection of urine samples to measure oxidative stress biomarkers, malondialdehyde (MDA), a marker of lipid peroxidation, and 8-hydroxy-2' -deoxyguanosine (8-OHdG), a marker of oxidative DNA damage. Ambient (central site) BC and PM2.5 were measured, and the ratio of indoor/ambient sulfur in PM2.5, a surrogate for residential ventilation and particle infiltration, was used to estimate indoor BC and PM2.5 of outdoor origin. Mixed effects linear regression models with a participant-specific random intercept were used to assess associations with oxidative biomarkers, adjusting for personal characteristics.

RESULTS

There were positive associations (% increase per IQR; 95 % CI) of directly measured indoor BC with total MDA (6.96; 1.54, 12.69) and 8-OHdG (4.18; -0.67, 9.27), and similar associations with both indoor BC of outdoor origin and ambient BC. There were no associations with directly measured indoor PM2.5, but there were positive associations between indoor PM2.5 of outdoor origin and total MDA (5.40; -0.91, 12.11) and 8-OHdG (8.02; 2.14, 14.25).

CONCLUSIONS

In homes with few indoor combustion sources, directly measured indoor BC, estimates of indoor BC and PM2.5 of outdoor origin, and ambient BC, were positively associated with urinary biomarkers of oxidative stress. This suggests that the infiltration of particulate matter from outdoor sources, attributable to traffic and other sources of combustion, promotes oxidative stress in COPD patients.

Ambient air pollution and sickle cell disease-related emergency department visits in Atlanta, GA

BACKGROUND

Sickle cell disease (SCD) is an inherited, autosomal recessive blood disorder, among the most prevalent genetic diseases, globally. While the genetic and hemolytic dynamics of SCD have been well-characterized, the etiology of SCD-related pathophysiological processes is unclear. Although limited, observational evidence suggests that environmental factors, including urban air pollution, may play a role.

OBJECTIVES

We assessed whether daily ambient air pollution concentrations are associated with corresponding emergency department (ED) visit counts for acute SCD exacerbations in Atlanta, Georgia, during a 9-year (2005-2013) period. We also examined heterogeneity in response by age and sex.

METHODS

ED visit data were from 41 hospitals in the 20-county Atlanta, GA area. Associations between daily air pollution levels for 8 urban air pollutants and counts of SCD related ED visits were estimated using Poisson generalized linear models.

RESULTS

We observed positive associations between pollutants generally indicative of traffic emissions and corresponding SCD ED visits [e.g., rate ratio of 1.022 (95% CI: 1.002, 1.043) per interquartile range increase in carbon monoxide]. Age stratified analyses indicated stronger associations with traffic pollutants among children (0-18 years), as compared to older age strata. Associations involving other pollutants, including ozone and particulate matter and for models of individuals >18 years old, were consistent a null hypothesis of no association.

DISCUSSION

This analysis represents the first North American study to examine acute risk among individuals with SCD to urban air pollution and provide evidence of urban air pollution, especially from traffic sources, as a trigger for acute exacerbations. These findings are consistent with a hypothesis that biological pathways, including several centrally associated with oxidative stress, may contribute towards enhanced susceptibility in individuals with SCD.

Estimation of personal exposure to fine particles (PM2.5) of ambient origin for healthy adults in Hong Kong

Personal exposure and ambient fine particles (PM_2.5) measurements for 13 adult subjects (ages 19-57) were conducted in Hong Kong between April 2014 and June 2015. Six to 21 personal samples (mean = 19) per subject were obtained throughout the study period. Samples were analyzed for mass by gravimetric analysis, and 19 elements (from Na to Pb) were analyzed using X-Ray Fluorescence. Higher subject-specific correlations between personal and ambient sulfur (r_s = 0.92; p < 0.001) were found as compared to PM_2.5 mass (r_s = 0.79; p < 0.001) and other elements (0.06 < r_s < 0.86). Personal vs. ambient sulfur regression yielded an average exposure factor (F_pex) of 0.73 ± 0.02, supporting the use of sulfur as a surrogate to estimate personal exposure to PM_2.5 of ambient origin (E_a). E_a accounted for 41-82% and 57-73% of total personal PM_2.5 exposures (P) by season and by subject, respectively. The importance of both E_a and non-ambient exposures (E_na, 11.2 ± 5.6 μg/m³; 32.5 ± 10.9%) are noted. Mixed-effects models were applied to estimate the relationships between ambient PM_2.5 concentrations and their corresponding exposure variables (E_a, P). Higher correlations for E_a (0.90; p < 0.001) than for P (0.58; p < 0.01) were found. A calibration coefficient < 1 suggests an attenuation of 22% (ranging 16-28%) of the true effect estimates when using average ambient concentrations at central monitoring stations as surrogates for E_a. Stationary ambient data can be used to assess population exposure only if PM exposure is dominated by E_a.

Estimating ambient-origin PM2.5 exposure for epidemiology: observations, prediction, and validation using personal sampling in the Multi-Ethnic Study of Atherosclerosis

OBJECTIVES

We aim to characterize the qualities of estimation approaches for individual exposure to ambient-origin fine particulate matter (PM_2.5), for use in epidemiological studies.

METHODS

The analysis incorporates personal, home indoor, and home outdoor air monitoring data and spatio-temporal model predictions for 60 participants from the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air). We compared measurement-based personal PM_2.5 exposure with several measured or predicted estimates of outdoor, indoor, and personal exposures.

RESULTS

The mean personal 2-week exposure was 7.6 (standard deviation 3.7) µg/m³. Outdoor model predictions performed far better than outdoor concentrations estimated using a nearest-monitor approach (R = 0.63 versus R = 0.43). Incorporating infiltration indoors of ambient-derived PM_2.5 provided better estimates of the measurement-based personal exposures than outdoor concentration predictions (R = 0.81 versus R = 0.63) and better scaling of estimated exposure (mean difference 0.4 versus 5.4 µg/m³ higher than measurements), suggesting there is value to collecting data regarding home infiltration. Incorporating individual-level time-location information into exposure predictions did not increase correlations with measurement-based personal exposures (R = 0.80) in our sample consisting primarily of retired persons.

CONCLUSIONS

This analysis demonstrates the importance of incorporating infiltration when estimating individual exposure to ambient air pollution. Spatio-temporal models provide substantial improvement in exposure estimation over a nearest monitor approach.

Determinants of personal exposure to fine particulate matter (PM2.5) in adult subjects in Hong Kong

Personal monitoring for fine particulate matter (PM_2.5) was conducted for adults (48 subjects, 18-63years of age) in Hong Kong during the summer and winter of 2014-2015. All filters were analyzed for PM_2.5 mass and constituents (including carbonaceous aerosols, water-soluble ions, and elements). We found that season (p=0.02) and occupation (p<0.001) were significant factors affecting the strength of the personal-ambient PM_2.5 associations. We applied mixed-effects models to investigate the determinants of personal exposure to PM_2.5 mass and constituents, along with within- and between-individual variance components. Ambient PM_2.5 was the dominant predictor of (R²=0.12-0.59, p<0.01) and the largest contributor (>37.3%) to personal exposures for PM_2.5 mass and most components. For all subjects, a one-unit (2.72μg/m³) increase in ambient PM_2.5 was associated with a 0.75μg/m³ (95% CI: 0.59-0.94μg/m³) increase in personal PM_2.5 exposure. The adjusted mixed-effects models included information extracted from individual's activity diaries as covariates. The results showed that season, occupation, time indoors at home, in transit, and cleaning were significant determinants for PM_2.5 components in personal exposure (R²_β=0.06-0.63, p<0.05), contributing to 3.0-70.4% of the variability. For one-hour extra time spent at home, in transit, and cleaning an average increase of 1.7-3.6% (ammonium, sulfate, nitrate, sulfur), 2.7-12.3% (elemental carbon, ammonium, titanium, iron), and 8.7-19.4% (ammonium, magnesium ions, vanadium) in components of personal PM_2.5 were observed, respectively. In this research, the within-individual variance component dominated the total variability for all investigated exposure data except PM_2.5 and EC. Results from this study indicate that performing long-term personal monitoring is needed for examining the associations of mass and constituents of personal PM_2.5 with health outcomes in epidemiological studies by describing the impacts of individual-specific data on personal exposures.

Characterization of ambient-generated exposure to fine particles using sulfate as a tracer in the Chinese megacity of Guangzhou

Total personal exposures can differ from the concentrations measured at stationary ambient monitoring sites. To provide further insight into factors affecting exposure to particles, chemical tracers were used to separate total personal exposure into its ambient and non-ambient components. Simultaneous measurements of ambient and personal exposure to fine particles (PM_2.5) were conducted in eight districts of Guangzhou, a megacity in South China, during the winter of 2011. Considerable significant correlations (Spearman's Rho, r_s) between personal exposures and ambient concentrations of sulfate (SO₄^2-; r_s>0.68) were found in contrast to elemental carbon (EC; r_s>0.37). The average fraction of personal SO₄^2- to ambient SO₄^2- resulting in an adjusted ambient exposure factor of α=0.72 and a slope of 0.73 was determined from linear regression analysis when there were minimal indoor sources of SO₄^2-. From all data pooled across the districts, the estimated average ambient-generated and non-ambient-generated exposure to PM_2.5 were 55.3μg/m³ (SD=23.4μg/m³) and 18.1μg/m³ (SD=29.1μg/m³), respectively. A significant association was found between ambient-generated exposure and ambient PM_2.5 concentrations (Pearson's r=0.51, p<0.001). As expected, the non-ambient generated exposure was not related to the ambient concentrations. This study highlights the importance of both ambient and non-ambient components of total personal exposure in the megacity of Guangzhou. Our results support the use of SO₄^2- as a tracer of personal exposure to PM_2.5 of ambient origin in environmental and epidemiological studies.

Assessment on personal exposure to particulate compounds using an empirical exposure model in an elderly community in Tianjin, China

Using central site measurement data to predict personal exposure to particulate matter (PM) is challenging, because people spend most of their time indoors and ambient contribution to personal exposure is subject to infiltration conditions affected by many factors. Efforts in assessing and predicting exposure on the basis of associated indoor/outdoor and central site monitoring were limited in China. This study collected daily personal exposure, residential indoor/outdoor and community central site PM filter samples in an elderly community during the non-heating and heating periods in 2009 in Tianjin, China. Based on the chemical analysis results of particulate species, mass concentrations of the particulate compounds were estimated and used to reconstruct the PM mass for mass balance analysis. The infiltration factors (F_inf) of particulate compounds were estimated using both robust regression and mixed effect regression methods, and further estimated the exposure factor (F_pex) according to participants' time-activity patterns. Then an empirical exposure model was developed to predict personal exposure to PM and particulate compounds as the sum of ambient and non-ambient contributions. Results showed that PM mass observed during the heating period could be well represented through chemical mass reconstruction, because unidentified mass was minimal. Excluding the high observations (>300μg/m³), this empirical exposure model performed well for PM and elemental carbon (EC) that had few indoor sources. These results support the use of F_pex as an indicator for ambient contribution predictions, and the use of empirical non-ambient contribution to assess exposure to particulate compounds.

The effects of PM2.5 and its components from indoor and outdoor sources on cough and wheeze symptoms in asthmatic children

Particulate matter with aerodynamic diameter <2.5 μm (PM2.5) is associated with asthma exacerbation. In the Children's Air Pollution Asthma Study, we investigated the longitudinal association of PM2.5 and its components from indoor and outdoor sources with cough and wheeze symptoms in 36 asthmatic children. The sulfur tracer method was used to estimate infiltration factors. Mixed proportional odds models for an ordinal response were used to relate daily cough and wheeze scores to PM2.5 exposures. The odds ratio associated with being above a given symptom score for a SD increase in PM2.5 from indoor sources (PMIS) was 1.24 (95% confidence interval: 0.92-1.68) for cough and 1.63 (1.11-2.39) for wheeze. Ozone was associated with wheeze (1.82, 1.19-2.80), and cough was associated with indoor PM2.5 components from outdoor sources (denoted with subscript "OS") bromine (BrOS: 1.32, 1.05-1.67), chlorine (ClOS: 1.27, 1.02-1.59) and pyrolyzed organic carbon (OPOS: 1.49, 1.12-1.99). The highest effects were seen in the winter for cough with sulfur (SOS: 2.28, 1.01-5.16) and wheeze with organic carbon fraction 2 (OC2OS: 7.46, 1.19-46.60). Our results indicate that exposure to components originating from outdoor sources of photochemistry, diesel and fuel oil combustion is associated with symptom's exacerbation, especially in the winter. PM2.5 mass of indoor origin was more strongly associated with wheeze than with cough.

Reducing patients' exposures to asthma and allergy triggers in their homes: an evaluation of effectiveness of grades of forced air ventilation filters

Objective

Many interventions to reduce allergen levels in the home are recommended to asthma and allergy patients. One that is readily available and can be highly effective is the use of high performing filters in forced air ventilation systems.

Methods

We conducted a modeling analysis of the effectiveness of filter-based interventions in the home to reduce airborne asthma and allergy triggers. This work used “each pass removal efficiency” applied to health-relevant size fractions of particles to assess filter performance. We assessed effectiveness for key allergy and asthma triggers based on applicable particle sizes for cat allergen, indoor and outdoor sources of particles <2.5 µm in diameter (PM_2.5), and airborne influenza and rhinovirus.

Results

Our analysis finds that higher performing filters can have significant impacts on indoor particle pollutant levels. Filters with removal efficiencies of >70% for cat dander particles, fine particulate matter (PM_2.5) and respiratory virus can lower concentrations of those asthma triggers and allergens in indoor air of the home by >50%. Very high removal efficiency filters, such as those rated a 16 on the nationally recognized Minimum Efficiency Removal Value (MERV) rating system, tend to be only marginally more effective than MERV12 or 13 rated filters.

Conclusions

The results of this analysis indicate that use of a MERV12 or higher performing air filter in home ventilation systems can effectively reduce indoor levels of these common asthma and allergy triggers. These reductions in airborne allergens in turn may help reduce allergy and asthma symptoms, especially if employed in conjunction with other environmental management measures recommended for allergy and asthma patients.

Source attribution of personal exposure to airborne polycyclic aromatic hydrocarbon mixture using concurrent personal, indoor, and outdoor measurements

OBJECTIVES

Relative importance of multiple indoor and outdoor venues on personal exposure concentrations to pro-carcinogenic polycyclic aromatic hydrocarbons (c-PAHs) remains poorly understood. This is particularly challenging because many c-PAHs share sources and occur as a complex mixture. Accurate and precise apportionment of personal exposure according to exposure venues could aid in the understanding of human health effects due to a given source. Here, we partitioned indoor and personal exposure concentrations to seven c-PAHs and pyrene according to the indoor- and outdoor-origins.

METHODS

A simultaneous, integrated monitoring of personal, indoor and outdoor concentrations of nine PAHs was conducted in 75 homes for a consecutive 48-hour period across a two-year period in Kraków, Poland. Due to few known indoor sources for chrysene, we used this PAH species as a tracer for infiltration of outdoor PAHs. Personal and indoor concentrations of seven c-PAHs and pyrene were apportioned to home indoor, non-home indoor and outdoor origins.

RESULTS

Using Chrysenein/Chryseneout as proxy for an infiltration factor, Finf, infiltrated PAHs of outdoor origin are overall higher in concentration than those emitted from the indoor origin. Average contribution by the outdoor sources on B[a]A, B[b]F, and B[k]F were 92%, 79%, and 78% across all seasons, respectively. In contrast, in homes where a household member smoked, average contributions by the outdoor sources on B[ghi]P, B[a]P, D[ah]A, and IP were lower (i.e., 67%, 65%, 67%, and 66%, respectively). Season-averaged contributions by the outdoor sources on personal exposure to B[a]A, B[b]F, and B[k]F were 92%, 74%, and 77%, respectively. On the other hand, season-averaged home indoor source contributions on personal exposure to B[a]A, B[b]F, and B[k]F were estimated at 6%, 15%, and 19%, respectively. Similar contributions by season-averaged home indoor sources on personal exposure were estimated at 28% for B[ghi]P, 31% for B[a]P, 25% for D[ah]A, and 28% for IP.

CONCLUSION

Of the seven c-PAHs, B[a]A, B[b]F, and B[k]F are enriched in indoor and personal exposure concentrations from the outdoor coal-combustion. B[ghi]P, B[a]P, D[a,h]A, and IP, PAHs with some of the highest carcinogenic and mutagenic potencies, are considerably enriched by cigarette smoke in addition to the outdoor sources.

Application of alternative spatiotemporal metrics of ambient air pollution exposure in a time-series epidemiological study in Atlanta

Exposure error in studies of ambient air pollution and health that use city-wide measures of exposure may be substantial for pollutants that exhibit spatiotemporal variability. Alternative spatiotemporal metrics of exposure for traffic-related and regional pollutants were applied in a time-series study of ambient air pollution and cardiorespiratory emergency department visits in Atlanta, GA, USA. Exposure metrics included daily central site monitoring for particles and gases; daily spatially refined ambient concentrations obtained from regional background monitors, local-scale dispersion, and hybrid air quality models; and spatially refined ambient exposures from population exposure models. Health risk estimates from Poisson models using the different exposure metrics were compared. We observed stronger associations, particularly for traffic-related pollutants, when using spatially refined ambient concentrations compared with a conventional central site exposure assignment approach. For some relationships, estimates of spatially refined ambient population exposures showed slightly stronger associations than corresponding spatially refined ambient concentrations. Using spatially refined pollutant metrics, we identified socioeconomic disparities in concentration-response functions that were not observed when using central site data. In some cases, spatially refined pollutant metrics identified associations with health that were not observed using measurements from the central site. Complexity and challenges in incorporating modeled pollutant estimates in time-series studies are discussed.

Estimating the concentration of indoor particles of outdoor origin: a review

Recent toxicological results highlight the importance of separating exposure to indoor- and outdoor-generated particles, due to their different physicochemical and toxicological properties. In this framework, a number of studies have attempted to estimate the relative contribution of particles of indoor and outdoor origins to indoor concentrations, using either statistical analysis of indoor and outdoor concentration time-series or mass balance equations. The aim of this work is to review and compare the methodologies developed in order to determine the ambient particle infiltration factor (F(INF)) (i.e., the fraction of ambient particles that enter indoors and remains suspended). The different approaches are grouped into four categories according to their methodological principles: (1) steady-state assumption using the steady-state form of the mass balance equation; (2) dynamic solution of the mass balance equation using complex statistical techniques; (3) experimental studies using conditions that simplify model calculations (e.g., decreasing the number of unknowns); and (4) infiltration surrogates using a particulate matter (PM) constituent with no indoor sources to act as surrogate of indoor PM of outdoor origin. Examination of the various methodologies and results reveals that estimating infiltration parameters is still challenging. The main difficulty lies in the separate calculation of penetration efficiency (P) and deposition rate (k). The values for these two parameters that are reported in the literature vary significantly. Deposition rate presents the widest range of values, both between studies and size fractions. Penetration efficiency seems to be more accurately calculated through the application of dynamic models. Overall, estimates of the infiltration factor generated using dynamic models and infiltration surrogates show good agreement. This is a strong argument in favor of the latter methodology, which is simple and easy to apply when chemical speciation data are available.

Measurement error in environmental epidemiology and the shape of exposure-response curves

Both classical and Berkson exposure measurement errors as encountered in environmental epidemiology data can result in biases in fitted exposure-response relationships that are large enough to affect the interpretation and use of the apparent exposure-response shapes in risk assessment applications. A variety of sources of potential measurement error exist in the process of estimating individual exposures to environmental contaminants, and the authors review the evaluation in the literature of the magnitudes and patterns of exposure measurement errors that prevail in actual practice. It is well known among statisticians that random errors in the values of independent variables (such as exposure in exposure-response curves) may tend to bias regression results. For increasing curves, this effect tends to flatten and apparently linearize what is in truth a steeper and perhaps more curvilinear or even threshold-bearing relationship. The degree of bias is tied to the magnitude of the measurement error in the independent variables. It has been shown that the degree of bias known to apply to actual studies is sufficient to produce a false linear result, and that although nonparametric smoothing and other error-mitigating techniques may assist in identifying a threshold, they do not guarantee detection of a threshold. The consequences of this could be great, as it could lead to a misallocation of resources towards regulations that do not offer any benefit to public health.

Variability of environmental exposure to fine particles, black smoke, and trace elements among a Swedish population

Mixed-effects models were used to estimate within-person and between-person variance components, and some determinants of environmental exposure to particulate matter (PM(2.5)), black smoke (BS) and trace elements (Cl, K, Ca, Ti, Fe, Ni, Cu, Zn, and Pb) for personal measurements from 30 adult subjects in Gothenburg, Sweden. The within-person variance component dominated the total variability for all investigated compounds except for PM(2.5) and Zn (in which the variance components were about equal). Expressed as fold ranges containing 95% of the underlying distributions, the within-person variance component ranged between 5-fold and 39-fold (median: sixfold), whereas the between-person variance component was always <sixfold (median: threefold). The relatively large within-person variance components can lead to attenuation bias in exposure-response relationships and point to the importance of obtaining repeated samples of PM exposure from study subjects in epidemiological investigations of urban air pollution. On the basis of the variance components estimated for the various particulate species, between 3 and 39 repeated measurements per subject would be required to limit attenuation bias to 20%. Significant determinants for personal exposure levels were urban background air concentrations (PM(2.5), BS, Cl, Zn, and Pb), cigarette smoking (PM(2.5), BS, K, and Ti), season (PM(2.5), Fe, and Pb), and the time spent outdoors or in traffic (Fe).

Prolonged exposure to particulate pollution, genes associated with glutathione pathways, and DNA methylation in a cohort of older men

BACKGROUND

DNA methylation is a potential pathway linking environmental exposures to disease. Exposure to particulate air pollution has been associated with increased cardiovascular morbidity and mortality, and lower blood DNA methylation has been found in processes related to cardiovascular morbidity.

OBJECTIVE

We hypothesized that prolonged exposure to particulate pollution would be associated with hypomethylation of repetitive DNA elements and that this association would be modified by genes involved in glutathione metabolism and other host characteristics.

METHODS

DNA methylation of the long interspersed nucleotide element-1 (LINE-1) and the short interspersed nucleotide element Alu were measured by quantitative polymerase chain reaction pyrosequencing in 1,406 blood samples from 706 elderly participants in the Normative Aging Study. We estimated changes in repetitive element DNA methylation associated with ambient particles (particulate matter ≤ 2.5 µm in aerodynamic diameter), black carbon (BC), and sulfates (SO₄), with mixed models. We examined multiple exposure windows (1-6 months) before DNA methylation measurement. We investigated whether this association was modified by genotype and phenotype.

RESULTS

An interquartile range (IQR) increase in BC over a 90-day period was associated with a decrease of 0.31% 5-methylcytosine (5mC) (95% confidence interval, 0.12-0.50%) in Alu. An IQR increase in SO₄ over a 90-day period was associated with a decrease of 0.27% 5mC (0.02-0.52%) in LINE-1. The glutathione S-transferase mu-1-null genotype strengthened the association between BC and Alu hypomethylation.

CONCLUSION

Prolonged exposure to BC and SO₄ particles was associated with hypomethylation of two types of repetitive elements.