Air pollution exposure is associated with rhinitis in older US adults via specific immune mechanisms

BACKGROUND

Pathophysiology of rhinitis in older adults is largely unknown. We tested whether air pollution is associated with this condition and how immune mechanisms may play a role in this relationship.

METHODS

We analyzed cross-sectional data from the National Social Life, Health, and Aging Project, a nationally representative study of older adults born between 1920 and 1947. Particulate matter ≤2.5 μm (PM2.5 ) air pollution exposure estimates were generated using validated spatiotemporal models. Presence of rhinitis was defined based on medication use (≥1: intranasal medications: steroids, antihistamines, lubricants, and/or decongestants, and/or oral medications: antihistamines and/or decongestants). K-means cluster analysis (Jaccard method) was used to group 13 peripheral blood cytokines into 3 clusters to facilitate functional determination. We fitted multivariate logistic regressions to correlate PM2.5 exposure with presence of rhinitis, controlling for confounders, and then determined the role of cytokines in this relationship.

RESULTS

Long- (but not short-) term exposure to PM2.5 was associated with presence of rhinitis: 3-year exposure window, odds ratio (OR) = 1.32, 95% confidence interval (CI): 0.98, 1.80, per 1 standard deviation (SD) PM2.5 increase. Inclusion of cytokine cluster in the model led to a modestly stronger effect of PM2.5 exposure on rhinitis (OR = 1.37; 95% CI: 1.00, 1.87; 3-year exposure window). The particular immune profile responsible for this result was composed of elevated IL-3, IL-12, and IFN-γ (OR = 4.86, 95% CI: 1.10, 21.58, immune profile-PM2.5 exposure interaction term).

CONCLUSION

We show for the first time that IL-3, IL-12, and IFN-γ explain in part the relationship between PM2.5 exposure and rhinitis in older US adults. If confirmed, these immune pathways may be used as therapeutic targets.

Long-term PM2.5 exposure and sepsis mortality in a US medicare cohort

Background

Risk factors contributing to sepsis-related mortality include clinical conditions such as cardiovascular disease, chronic lung disease, and diabetes, all of which have also been shown to be associated with air pollution exposure. However, the impact of chronic exposure to air pollution on sepsis-related mortality has been little studied. 

Methods

In a cohort of 53 million Medicare beneficiaries (228,439 sepsis-related deaths) living across the conterminous United States between 2000 and 2008, we examined the association of long-term PM_2.5 exposure and sepsis-related mortality. For each Medicare beneficiary (ages 65–120), we estimated the 12-month moving average PM_2.5 concentration for the 12 month before death, for their ZIP code of residence using well validated GIS-based spatio-temporal models. Deaths were categorized as sepsis-related if they have ICD-10 codes for bacterial or other sepsis. We used Cox proportional hazard models to assess the association of long-term PM_2.5 exposure on sepsis-related mortality. Models included strata for age, sex, race, and ZIP code and controlled for neighborhood socio-economic status (SES). We also evaluated confounding through adjustment of neighborhood behavioral covariates.

Results

A 10 μg/m³ increase in 12-month moving average PM_2.5 was associated with a 9.1% increased risk of sepsis mortality (95% CI: 3.6–14.9) in models adjusted for age, sex, race, ZIP code, and SES. HRs for PM_2.5 were higher and statistically significant for older (> 75), Black, and urban beneficiaries. In stratified analyses, null associations were found for younger beneficiaries (65–75), beneficiaries who lived in non-urban ZIP codes, and those residing in low-SES urban ZIP codes.

Conclusions

Long-term PM_2.5 exposure is associated with elevated risks of sepsis-related mortality.

The impact of Long-Term PM2.5 constituents and their sources on specific causes of death in a US Medicare cohort

BACKGROUND

Our understanding of the impact of long-term exposures to PM_2.5 constituents and sources on mortality is limited.

OBJECTIVES

To examine associations between long-term exposures to PM_2.5 constituents and sources and cause-specific mortality in US older adults.

METHODS

We obtained demographic and mortality data for 15.4 million Medicare beneficiaries living within the conterminous United States (US) between 2000 and 2008. We assessed PM_2.5 constituents exposures for each beneficiary and used factor analysis and residual-based methods to characterize PM_2.5 sources and mixtures, respectively. In age-, sex-, race- and site- stratified Cox proportional hazard models adjusted for neighborhood socio-economic status (SES), we assessed associations of individual PM_2.5 constituents, sources, and mixtures and cause-specific mortality and examined modification of these associations by participant demographics and location of residence. We assessed the robustness of our findings to additional adjustment for behavioral risk factors and to alternate exposure definitions and exposure windows.

RESULTS

Hazard ratios (HR) were highest for all causes of death, except COPD, for PM_2.5 constituents and the coal combustion-related PM_2.5 components, with no evidence of confounding by behavioral covariates. We further found Pb and metal-related PM_2.5 components to be significantly associated with increased HR of all causes of death, except COPD and lung cancer mortality, and nitrate (NO₃^-) and silicon (Si) and associated source-related PM_2.5 components (traffic and soil, respectively) to be significantly associated with increased all-cause, CVD, respiratory and all cancer-related mortality HR. Associations for other examined constituents and mortality were inconsistent or largely null. Our analyses of mixtures were generally consistent with these findings. Mortality HRs were greatest for minority, especially Black, low-income urban, younger, and male beneficiaries.

DISCUSSION

PM_2.5 components related to coal combustion, traffic, and to a lesser extent, soil were strongly associated with mortality from CVD, respiratory disease, and cancer.

Non-pharmaceutical interventions and COVID-19 cases in US summer camps: results from an American Camp Association survey

BACKGROUND

Most camps remained closed during Summer 2020, due to concerns regarding child transmission of SARS-CoV-2 and limited information about the effectiveness of non-pharmaceutical interventions (NPIs) within child congregate settings.

METHODS

We surveyed US camps about on-site operations, camper and staff demographics, COVID-19 cases among campers and staff, and NPI usage as related to pre-camp quarantine, facial coverings, physical distancing, cleaning and facility modifications. For all NPIs, save quarantine, responses were provided on a 5-point Likert scale format.

RESULTS

Within 486 on-site camps, a range of NPIs were instituted, most often related to reduced camper interactions, staff face coverings, cleaning and hand hygiene. Camper facial coverings were less common, with campers always wearing masks at ~34% of the camps. Approximately 15% of camps reported 1+ confirmed COVID-19 case in either campers or staff, with three camps reporting a COVID-19 outbreak. In both single and multi-NPI analyses, the risk of COVID-19 cases was lowest when campers always wore facial coverings. Constant use of staff facial coverings and targeted physical distancing measures, but not pre-camp quarantine, also reduced COVID-19 risks.

CONCLUSIONS

We found constant facial coverings, especially for campers, and targeted physical distancing measures to reduce risks of SARS-CoV-2 transmission within summer camps. Our findings provide valuable insights for future operations of summer camps and other child congregate settings regarding the use of NPIs to reduce the risk of SARS-CoV-2 infection.

Non-nutritive suck and airborne metal exposures among Puerto Rican infants

Air pollution has been shown to impact multiple measures of neurodevelopment in young children. Its effects on particularly vulnerable populations, such as ethnic minorities, however, is less studied. To address this gap in the literature, we assess the associations between infant non-nutritive suck (NNS), an early indicator of central nervous system integrity, and air pollution exposures in Puerto Rico. Among infants aged 0-3 months enrolled in the Center for Research on Early Childhood Exposure and Development (CRECE) cohort from 2017 to 2019, we examined associations between exposure to fine particulate matter (PM_2.5) and its components on infant NNS in Puerto Rico. NNS was assessed using a pacifier attached to a pressure transducer, allowing for real-time visualization of NNS amplitude, frequency, duration, cycles/burst, cycles/min and bursts/min. These data were linked to 9-month average prenatal concentrations of PM_2.5 and components, measured at three community monitoring sites. We used linear regression to examine the PM_2.5-NNS association in single pollutant models, controlling for infant sex, maternal age, gestational age, and season of birth in base and additionally for household smoke exposure, age at testing, and NNS duration in full models. Among 198 infants, the average NNS amplitude and burst duration was 17.1 cmH₂O and 6.1 s, respectively. Decreased NNS amplitude was consistently and significantly associated with 9-month average exposure to sulfur (-1.026 ± 0.507), zinc (-1.091 ± 0.503), copper (-1.096 ± 0.535) vanadium (-1.157 ± 0.537), and nickel (-1.530 ± 0.501). Decrements in NNS frequency were associated with sulfur exposure (0.036 ± 0.018), but not other examined PM components. Our findings provide new evidence that prenatal maternal exposure to specific PM components are associated with impaired neurodevelopment in Puerto Rican infants soon after birth.

Preterm birth and PM2.5 in Puerto Rico: evidence from the PROTECT birth cohort

BACKGROUND

Preterm birth (PTB, birth before 37 weeks of gestation) has been associated with adverse health outcomes across the lifespan. Evidence on the association between PTB and prenatal exposure to air pollutants is inconsistent, and is especially lacking for ethnic/racial minority populations.

METHODS

We obtained data on maternal characteristics and behaviors and PTB and other birth outcomes for women participating in the Puerto Rico Testsite for Exploring Contamination Threats (PROTECT) cohort, who lived in municipalities located along the North Coast of Puerto Rico. We assessed pre-natal PM_2.5 exposures for each infant based on the nearest US Environmental Protection Agency monitor. We estimated prenatal phthalate exposures as the geometric mean of urinary measurements obtained during pregnancy. We then examined the association between PM_2.5 and PTB using modified Poisson regression and assessed modification of the association by phthalate exposure levels and sociodemographic factors such as maternal age and infant gender.

RESULTS

Among 1092 singleton births, 9.1% of infants were born preterm and 92.9% of mothers had at least a high school education. Mothers had a mean (standard deviation) age of 26.9 (5.5) years and a median (range) of 2.0 (1.0-8.0) pregnancies. Nearly all women were Hispanic white, black, or mixed race. Median (range) prenatal PM_2.5 concentrations were 6.0 (3.1-19.8) μ g/m³. Median (interquartile range) prenatal phthalate levels were 14.9 (8.9-26.0) and 14.5 (8.4-26.0), respectively, for di-n-butyl phthalate (DBP) and di-isobutyl phthalate (DiBP). An interquartile range increase in PM_2.5 was associated with a 1.2% (95% CI 0.4, 2.1%) higher risk of PTB. There was little difference in PTB risk in strata of infant sex, mother's age, family income, history of adverse birth outcome, parity, and pre-pregnancy body mass index. Pregnancy urinary phthalate metabolite levels did not modify the PM_2.5-PTB association.

CONCLUSION

Among ethnic minority women in Puerto Rico, prenatal PM_2.5 exposure is associated with a small but significant increase in risk of PTB.

Cohort profile: Center for Research on Early Childhood Exposure and Development in Puerto Rico

PURPOSE

Puerto Rican children experience high rates of asthma and obesity. Further, infants born in Puerto Rico are more at risk for being born prematurely compared with infants on the mainland USA. Environmental exposures from multiple sources during critical periods of child development, potentially modified by psychosocial factors, may contribute to these adverse health outcomes. To date, most studies investigating the health effects of environmental factors on infant and child health have focused on single or individual exposures.

PARTICIPANTS

Infants currently in gestation whose mother is enrolled in Puerto Rico Testsite for Exploring Contamination Threats (PROTECT) cohort, and infants and children already born to mothers who participated in the PROTECT study.

FINDINGS TO DATE

Data collection and processing remains ongoing. Demographic data have been collected on 437 mother-child pairs. Birth outcomes are available for 420 infants, neurodevelopmental outcomes have been collected on 319 children. Concentrations of parabens and phenols in maternal spot urine samples have been measured from 386 mothers. Center for Research on Early Childhood Exposure and Development mothers have significantly higher urinary concentrations of dichlorophenols, triclosan and triclocarban, but lower levels of several parabens compared with reference values from a similar population drawn from the National Health and Nutrition Examination Survey.

FUTURE PLANS

Data will continue to be collected through recruitment of new births with a target of 600 children. Seven scheduled follow-up visits with existing and new participants are planned. Further, our research team continues to work with healthcare providers, paediatricians and early intervention providers to support parent's ability to access early intervention services for participants.

Long-term ozone exposures and cause-specific mortality in a US Medicare cohort

We examined the association of long-term, daily 1-h maximum O₃ (ozone) exposures on cause-specific mortality for 22.2 million US Medicare beneficiaries between 2000-2008. We modeled the association between O₃ and mortality using age-gender-race stratified log-linear regression models, adjusted for state of residence. We examined confounding by (1) adjusting for PM_2.5 (particles with aerodynamic diameters <2.5 μm) and NO₂ (nitrogen dioxide) exposures, temperature, and neighborhood-level characteristics and behaviors, and (2) decomposing O₃ into its temporal and spatio-temporal components and comparing estimated risk ratios. We also examined sensitivity of our results to alternate exposure measures based on warm-season 8-h daily maximum and 24-h average exposures. We found increased risks from long-term O₃ exposures to be strongest and most consistent for mortality from respiratory disease (1.030, 95% CI: 1.027, 1.034) (including COPD (chronic obstructive pulmonary disease)), CHF (congestive heart failure), and lung cancer (1.015, 95% CI: 1.010, 1.020), with no evidence of confounding by PM_2.5, NO₂, and temperature and with results similar across O₃ exposure measures. While significant, associations between long-term O₃ exposures and CVD (cardiovascular)-related mortality (1.005, 95% CI: 1.003, 1.007) were confounded by PM_2.5 and varied with the exposure measure, with associations no longer significantly positive when warm-season 8-h maximum or 24-h average O₃ was used to assess exposures. In this large study, we provide strong evidence that O₃ exposure is associated with mortality from respiratory-related causes and for the first-time, lung cancer, but raise questions regarding O₃-related impacts on CVD mortality. Our findings demonstrate the need to further identify potential confounders.

Low birth weight and PM2.5 in Puerto Rico

BACKGROUND

Low birth weight (LBW) has been associated with adverse health outcomes across the lifespan. Among ethnic/racial minority populations, few studies have examined the association between LBW (<2,500 or ≥2,500 g) and prenatal exposure to air pollution, a key modifiable environmental risk factor.

METHODS

We examined the association between LBW and prenatal exposure to PM2.5 in a Hispanic and black population in Puerto Rico between 1999 and 2013, adjusting for individual and municipality-level confounders. We used modified Poisson regression to estimate the association and performed sensitivity analyses treating birth weight as continuous or polychotomous. In secondary analyses, we applied a 2-stage mixed effects model suitable for longitudinally measured exposures and binary outcomes.

RESULTS

Among 332,129 total and 275,814 term births, 12.2% and 6.3% of infants had LBW, respectively. Eighty-eight percent of mothers were Hispanic. Mean (SD) PM2.5 concentrations declined from 9.9 (1.7) μg/m3 in 1999 to 6.1 (1.1) μg/m3 in 2013. Mean birth weights dropped to 3,044 g in 2010 and rose steadily afterward. Among term births, a SD increase in PM2.5 was associated with a 3.2% (95% CI = -1.0%, 6.3%) higher risk of LBW. First (risk ratio, 1.02; 95% CI = 1.00, 1.04) and second (1.02; 95% CI = 1.01, 1.05) trimester exposures were associated with increased LBW risk. In a 2-stage approach that longitudinally modeled monthly prenatal exposure levels, a standard deviation increase in average PM2.5 was associated with higher risk of LBW (odds ratio, 1.04; 95% CI = 1.01, 1.08).

CONCLUSIONS

In Puerto Rico, LBW is associated with prenatal PM2.5 exposure.

Close proximity to roadway and urbanicity associated with mental ill-health in older adults

Evidence for the association between built environment and mental ill health, especially in older population where mental ill health is common, remains inconclusive. We examined the association of roadway distance and urbanicity, measured as percentage of urban land use within 1 km from participants' residence, with mental ill-health in a longitudinal study of community-dwelling older adults in the United States between 2005 and 2006 and 2011-2012. We evaluated perceived stress, depression and anxiety symptoms using the Cohen's Perceived Stress Scale, the Center for Epidemiological Studies - Depression, and the Hospital Anxiety and Depression Scale - anxiety subscale, respectively. Increment in roadway distance was significantly associated with -0.03 point (95% CI: -0.05, -0.01) change in depressive score, with loneliness and PM_2.5 partially mediating the observed associations. Age, gender, race/ethnicity, and physical activity significantly modified the distance-depression association. Anxiety was inversely associated with roadway distance (-0.02; 95% CI: -0.03, 0.00), though the associations became insignificant upon adjusting for road traffic or noise. Urbanicity was significantly associated with 0.29 (95% CI: 0.10, 0.57) point increase in depressive symptoms in multivariable model; the association was partly mediated by loneliness, physical activity, social support and air pollution. No association was found between roadway distance and perceived stress, and between urbanicity, and anxiety and perceived stress. Built environment was associated with mental ill health, partially through pathways related to air pollution and certain individual characteristics (e.g. loneliness). Our study warrants further examination of the mediation and interaction of the built environment-mental health association.

Association of neighborhood greenness with self-perceived stress, depression and anxiety symptoms in older U.S adults

BACKGROUND

Neighborhood environment, such as green vegetation, has been shown to play a role in coping with stress and mental ill health. Yet, epidemiological evidence of the association between greenness and mental health is inconsistent.

METHODS

We examined whether living in green space is associated with self-perceived stress, depressive and anxiety symptoms in a nationally representative, longitudinal sample of community-dwelling older adults (N = 4118; aged 57-85 years) in the United States. We evaluated perceived stress, depression and anxiety symptoms using the Cohen's Perceived Stress Scale, the Center for Epidemiological Studies - Depression, and the Hospital Anxiety and Depression Scale - anxiety subscale, respectively. Greenness was assessed for each participant using the Normalized Difference Vegetation Index at 250-m resolution, as well as a buffer of 1000-m. We conducted longitudinal analyses to assess the associations between greenness and mental health upon adjusting for confounders (e.g., education), and to examine potential mediation and effect modification.

RESULTS

An interquartile range (0.25 point) increase in contemporaneous greenness was significantly associated with 0.238 unit (95% CI: - 0.346, - 0.130) and 0.162 unit (95% CI: - 0.271, - 0.054) decrease in the perceived stress in base and multivariable models, respectively. The magnitude of the association was similar or even stronger when examining summer (- 0.161; 95% CI: - 0.295, - 0.027) and annual average of greenness (- 0.188; 95% CI: - 0.337, - 0.038), as well as greenness buffer of 1000-m. The greenness-stress association was partially mediated by physical activity (15.1% mediated), where increased greenness led to increased physical activity and less stress, and by history of respiratory diseases (- 3.8% mediated), where increased greenness led to increased respiratory disease and more stress. The association was also significantly modified by race, social support, physical function, socioeconomic status, and region. While greenness was not significantly associated with anxiety and depressive scores across all participants, significant inverse associations were found for Whites participants, and for individuals with higher socioeconomic status, who were physically active, as compared to their counterparts.

CONCLUSION

We found a direct association of greenness with perceived stress among older adults, and an indirect association mediated through physical activity and respiratory disease history. Our study findings warrant further examination of the mediation and modification of the greenness-mental health association.

Long-Term PM2.5 Exposure and Respiratory, Cancer, and Cardiovascular Mortality in Older US Adults

The impact of chronic exposure to fine particulate matter (particulate matter with an aerodynamic diameter less than or equal to 2.5 μm (PM2.5)) on respiratory disease and lung cancer mortality is poorly understood. In a cohort of 18.9 million Medicare beneficiaries (4.2 million deaths) living across the conterminous United States between 2000 and 2008, we examined the association between chronic PM2.5 exposure and cause-specific mortality. We evaluated confounding through adjustment for neighborhood behavioral covariates and decomposition of PM2.5 into 2 spatiotemporal scales. We found significantly positive associations of 12-month moving average PM2.5 exposures (per 10-μg/m3 increase) with respiratory, chronic obstructive pulmonary disease, and pneumonia mortality, with risk ratios ranging from 1.10 to 1.24. We also found significant PM2.5-associated elevated risks for cardiovascular and lung cancer mortality. Risk ratios generally increased with longer moving averages; for example, an elevation in 60-month moving average PM2.5 exposures was linked to 1.33 times the lung cancer mortality risk (95% confidence interval: 1.24, 1.40), as compared with 1.13 (95% confidence interval: 1.11, 1.15) for 12-month moving average exposures. Observed associations were robust in multivariable models, although evidence of unmeasured confounding remained. In this large cohort of US elderly, we provide important new evidence that long-term PM2.5 exposure is significantly related to increased mortality from respiratory disease, lung cancer, and cardiovascular disease.

Smoking and olfactory dysfunction: A systematic literature review and meta-analysis

OBJECTIVES/HYPOTHESIS

A systematic review and meta-analysis of the literature was undertaken, examining the association between tobacco smoking and olfactory function in humans, utilizing PubMed and Web of Science (1970-2015) as data sources.

STUDY DESIGN

Systematic literature review and meta-analysis.

METHODS

This database review of studies of smoking and olfaction, with a focus on identifying high-quality studies (based on modified versions of the Newcastle-Ottawa Scale), used validated olfactory tests among the generally healthy population.

RESULTS

We identified 11 studies meeting inclusion criteria. Of 10 cross-sectional studies, two were excluded from meta-analysis because the cohorts they studied were included in another article in the review. In meta-analysis, current smokers had substantially higher odds of olfactory dysfunction compared to never smokers (odds ratio [OR] = 1.59, 95% confidence interval [CI] = 1.37-1.85). In contrast, former smokers were found to have no difference in risk of impaired olfaction compared to never smokers (OR = 1.05, 95% CI = 0.91-1.21). The single longitudinal study reviewed found a trend toward increased risk of olfactory decline over time in ever smokers; this trend was stronger in current as compared to former smokers.

CONCLUSIONS

Current smoking, but not former smoking, is associated with significantly increased risk of olfactory dysfunction, suggesting that the effects of smoking on olfaction may be reversible. Future studies that prospectively evaluate the impact of smoking cessation on improvement in olfactory function are warranted.

LEVEL OF EVIDENCE

N/A. Laryngoscope, 127:1753-1761, 2017.

Fine particulate matter exposure and olfactory dysfunction among urban-dwelling older US adults

OBJECTIVES

The olfactory nerve is anatomically susceptible to injury from pollution in inspired air, but there are no large-scale epidemiologic studies investigating this relationship.

METHODS

Cross-sectional study using data from the National Social Life, Health, and Aging Project, a representative sample of home-dwelling US adults age 57-85 years. Olfactory function was tested using a validated 5-item odor identification test (Sniffin' Sticks). Exposure to fine particulate matter (PM_2.5) at each respondent's home was estimated as 1-12 month moving averages prior to olfactory assessment using validated spatio-temporal models.

RESULTS

Olfactory dysfunction was significantly associated with PM_2.5 exposures averaged over 3-12 months in urban-dwelling respondents. The strongest effect was for 6 month average exposure (per 1-IQR increase in PM_2.5: OR 1.28, 95% CI 1.05, 1.55) adjusting for age, gender, race/ethnicity, education, cognition, comorbidity, smoking, and the season. Interestingly, the most deleterious effects were observed among the youngest respondents, 57-64 years old, and those living in the northeast and south.

CONCLUSIONS

We show for the first time that air pollution exposure is associated with poor olfaction among urban-living, older US adults.

Effects of Ambient Air Pollution Exposure on Olfaction: A Review

BACKGROUND

Olfactory dysfunction affects millions of people worldwide. This sensory impairment is associated with neurodegenerative disease and significantly decreased quality of life. Exposure to airborne pollutants has been implicated in olfactory decline, likely due to the anatomic susceptibility of the olfactory nerve to the environment. Historically, studies have focused on occupational exposures, but more recent studies have considered effects from exposure to ambient air pollutants.

OBJECTIVES

To examine all relevant human data evaluating a link between ambient pollution exposure and olfaction and to review supporting animal data in order to examine potential mechanisms for pollution-associated olfactory loss.

METHODS

We identified and reviewed relevant articles from 1950 to 2015 using PubMed and Web of Science and focusing on human epidemiologic and pathophysiologic studies. Animal studies were included only to support pertinent data on humans. We reviewed findings from these studies evaluating a relationship between environmental pollutant exposure and olfactory function.

RESULTS

We identified and reviewed 17 articles, with 1 additional article added from a bibliography search, for a total of 18 human studies. There is evidence in human epidemiologic and pathologic studies that increased exposure to ambient air pollutants is associated with olfactory dysfunction. However, most studies have used proxies for pollution exposure in small samples of convenience. Human pathologic studies, with supporting animal work, have also shown that air pollution can contact the olfactory epithelium, translocate to the olfactory bulb, and migrate to the olfactory cortex. Pollutants can deposit at each location, causing direct damage and disruption of tissue morphology or inducing local inflammation and cellular stress responses.

CONCLUSIONS

Ambient air pollution may impact human olfactory function. Additional studies are needed to examine air pollution-related olfactory impacts on the general population using measured pollution exposures and to link pollution exposure with olfactory dysfunction and related pathology. Citation: Ajmani GS, Suh HH, Pinto JM. 2016. Effects of ambient air pollution exposure on olfaction: a review. Environ Health Perspect 124:1683-1693; http://dx.doi.org/10.1289/EHP136.

Nitrogen dioxide pollution exposure is associated with olfactory dysfunction in older U.S. adults

BACKGROUND

Olfactory dysfunction has profound effects on quality of life, physical and social function, and mortality itself. Nitrogen dioxide (NO₂ ) is a pervasive air pollutant that is associated with respiratory diseases. Given the olfactory nerve's anatomic exposure to airborne pollutants, we investigated the relationship between NO₂ exposure and olfactory dysfunction.

METHODS

The ability to identify odors was evaluated using a validated test in respondents from the National Social Life, Health, and Aging Project (NSHAP), a representative probability sample of home-dwelling, older U.S. adults age 57 to 85 years. Exposure to NO₂ pollution was assessed using measurements obtained from the U.S. Environmental Protection Agency (EPA) Aerometric Information Retrieval System (AIRS) ambient monitoring site closest to each respondent's home. We tested the association between NO₂ exposure and olfactory dysfunction using multivariate logistic regression.

RESULTS

Among older adults in the United States, 22.6% had impaired olfactory function, defined as ≤3 correct (out of 5) on the odor identification test. Median NO₂ exposure during the 365 days prior to the interview date was 14.7 ppb (interquartile range [IQR], 10.8 to 19.7 ppb). An IQR increase in NO₂ exposure was associated with increased odds of olfactory dysfunction (OR, 1.35; 95% CI, 1.07 to 1.72), adjusting for age, gender, race/ethnicity, education, cognition, comorbidity, smoking, and season of the home interview (n = 1823).

CONCLUSION

We show for the first time that NO₂ exposure is associated with olfactory dysfunction in older U.S. adults. These results suggest an important role for NO₂ exposure on olfactory dysfunction, and, potentially, nasal disease more broadly.

Spatio-temporal modeling of particulate air pollution in the conterminous United States using geographic and meteorological predictors

BACKGROUND

Exposure to atmospheric particulate matter (PM) remains an important public health concern, although it remains difficult to quantify accurately across large geographic areas with sufficiently high spatial resolution. Recent epidemiologic analyses have demonstrated the importance of spatially- and temporally-resolved exposure estimates, which show larger PM-mediated health effects as compared to nearest monitor or county-specific ambient concentrations.

METHODS

We developed generalized additive mixed models that describe regional and small-scale spatial and temporal gradients (and corresponding uncertainties) in monthly mass concentrations of fine (PM2.5), inhalable (PM10), and coarse mode particle mass (PM(2.5-10)) for the conterminous United States (U.S.). These models expand our previously developed models for the Northeastern and Midwestern U.S. by virtue of their larger spatial domain, their inclusion of an additional 5 years of PM data to develop predictions through 2007, and their use of refined geographic covariates for population density and point-source PM emissions. Covariate selection and model validation were performed using 10-fold cross-validation (CV).

RESULTS

The PM2.5 models had high predictive accuracy (CV R2=0.77 for both 1988-1998 and 1999-2007). While model performance remained strong, the predictive ability of models for PM10 (CV R2=0.58 for both 1988-1998 and 1999-2007) and PM(2.5-10) (CV R2=0.46 and 0.52 for 1988-1998 and 1999-2007, respectively) was somewhat lower. Regional variation was found in the effects of geographic and meteorological covariates. Models generally performed well in both urban and rural areas and across seasons, though predictive performance varied somewhat by region (CV R2=0.81, 0.81, 0.83, 0.72, 0.69, 0.50, and 0.60 for the Northeast, Midwest, Southeast, Southcentral, Southwest, Northwest, and Central Plains regions, respectively, for PM2.5 from 1999-2007).

CONCLUSIONS

Our models provide estimates of monthly-average outdoor concentrations of PM2.5, PM10, and PM(2.5-10) with high spatial resolution and low bias. Thus, these models are suitable for estimating chronic exposures of populations living in the conterminous U.S. from 1988 to 2007.

Spatio-temporal modeling of particulate air pollution in the conterminous United States using geographic and meteorological predictors

BACKGROUND

Exposure to atmospheric particulate matter (PM) remains an important public health concern, although it remains difficult to quantify accurately across large geographic areas with sufficiently high spatial resolution. Recent epidemiologic analyses have demonstrated the importance of spatially- and temporally-resolved exposure estimates, which show larger PM-mediated health effects as compared to nearest monitor or county-specific ambient concentrations.

METHODS

We developed generalized additive mixed models that describe regional and small-scale spatial and temporal gradients (and corresponding uncertainties) in monthly mass concentrations of fine (PM2.5), inhalable (PM10), and coarse mode particle mass (PM(2.5-10)) for the conterminous United States (U.S.). These models expand our previously developed models for the Northeastern and Midwestern U.S. by virtue of their larger spatial domain, their inclusion of an additional 5 years of PM data to develop predictions through 2007, and their use of refined geographic covariates for population density and point-source PM emissions. Covariate selection and model validation were performed using 10-fold cross-validation (CV).

RESULTS

The PM2.5 models had high predictive accuracy (CV R2=0.77 for both 1988-1998 and 1999-2007). While model performance remained strong, the predictive ability of models for PM10 (CV R2=0.58 for both 1988-1998 and 1999-2007) and PM(2.5-10) (CV R2=0.46 and 0.52 for 1988-1998 and 1999-2007, respectively) was somewhat lower. Regional variation was found in the effects of geographic and meteorological covariates. Models generally performed well in both urban and rural areas and across seasons, though predictive performance varied somewhat by region (CV R2=0.81, 0.81, 0.83, 0.72, 0.69, 0.50, and 0.60 for the Northeast, Midwest, Southeast, Southcentral, Southwest, Northwest, and Central Plains regions, respectively, for PM2.5 from 1999-2007).

CONCLUSIONS

Our models provide estimates of monthly-average outdoor concentrations of PM2.5, PM10, and PM(2.5-10) with high spatial resolution and low bias. Thus, these models are suitable for estimating chronic exposures of populations living in the conterminous U.S. from 1988 to 2007.

Spatio-temporal modeling of particulate air pollution in the conterminous United States using geographic and meteorological predictors

BACKGROUND

Exposure to atmospheric particulate matter (PM) remains an important public health concern, although it remains difficult to quantify accurately across large geographic areas with sufficiently high spatial resolution. Recent epidemiologic analyses have demonstrated the importance of spatially- and temporally-resolved exposure estimates, which show larger PM-mediated health effects as compared to nearest monitor or county-specific ambient concentrations.

METHODS

We developed generalized additive mixed models that describe regional and small-scale spatial and temporal gradients (and corresponding uncertainties) in monthly mass concentrations of fine (PM2.5), inhalable (PM10), and coarse mode particle mass (PM(2.5-10)) for the conterminous United States (U.S.). These models expand our previously developed models for the Northeastern and Midwestern U.S. by virtue of their larger spatial domain, their inclusion of an additional 5 years of PM data to develop predictions through 2007, and their use of refined geographic covariates for population density and point-source PM emissions. Covariate selection and model validation were performed using 10-fold cross-validation (CV).

RESULTS

The PM2.5 models had high predictive accuracy (CV R2=0.77 for both 1988-1998 and 1999-2007). While model performance remained strong, the predictive ability of models for PM10 (CV R2=0.58 for both 1988-1998 and 1999-2007) and PM(2.5-10) (CV R2=0.46 and 0.52 for 1988-1998 and 1999-2007, respectively) was somewhat lower. Regional variation was found in the effects of geographic and meteorological covariates. Models generally performed well in both urban and rural areas and across seasons, though predictive performance varied somewhat by region (CV R2=0.81, 0.81, 0.83, 0.72, 0.69, 0.50, and 0.60 for the Northeast, Midwest, Southeast, Southcentral, Southwest, Northwest, and Central Plains regions, respectively, for PM2.5 from 1999-2007).

CONCLUSIONS

Our models provide estimates of monthly-average outdoor concentrations of PM2.5, PM10, and PM(2.5-10) with high spatial resolution and low bias. Thus, these models are suitable for estimating chronic exposures of populations living in the conterminous U.S. from 1988 to 2007.

Proximity of US schools to major roadways: a nationwide assessment

Long-term exposure to traffic pollution has been associated with adverse health outcomes in children and adolescents. A significant number of schools may be located near major roadways, potentially exposing millions of children to high levels of traffic pollution, but this hypothesis has not been evaluated nationally. We obtained data on the location and characteristics of 114,644 US public and private schools, grades prekindergarten through 12, and calculated their distance to the nearest major roadway. In 2005-2006, 3.2 million students (6.2%) attended 8,424 schools (7.3%) located within 100 m of a major roadway, and an additional 3.2 million (6.3%) students attended 8,555 (7.5%) schools located 100-250 m from a major roadway. Schools serving predominantly Black students were 18% (95% CI, 13-23%) more likely to be located within 250 m of a major roadway. Public schools eligible for Title I programs and those with a majority of students eligible for free/reduced price meals were also more likely to be near major roadways. In conclusion, 6.4 million US children attended schools within 250 m of a major roadway and were likely exposed to high levels of traffic pollution. Minority and underprivileged children were disproportionately affected, although some results varied regionally.

Structural equation modeling of parasympathetic and sympathetic response to traffic air pollution in a repeated measures study

BACKGROUND

Traffic-related air pollution has been associated to a range of adverse health impacts, including decreased heart rate variability (HRV). The association between traffic-related pollution and HRV, however, has varied by traffic-related or HRV marker as well as by study, suggesting the need for a more comprehensive and integrative approach to examining air pollution-mediated biological impacts on these outcomes. In a Bayesian framework, we examined the effect of traffic pollution on HRV using structural equation models (SEMs) and looked at effect modification by participant characteristics.

METHODS

We studied measurements of 5 HRV markers [high frequency (HF), low frequency (LF), 5-min standard deviation of normal-to-normal intervals (SDNN), square root of the mean squared differences of successive normal-to-normal intervals (rMSSD), and LF/HF ratio (LF/HF)] for 700 elderly men from the Normative Aging Study. Using SEMs, we fit a latent variable for traffic pollution that is reflected by levels of carbon monoxide, nitrogen monoxide, nitrogen dioxide, and black carbon (BC) to estimate its effect on latent variable for parasympathetic tone that included HF, SDNN and rMSSD, and the sympathetic tone marker, LF/HF. Exposure periods were assessed using 4-, 24-, 48-, 72-hour moving average pre-visit. We compared our main effect findings using SEMs with those obtained using linear mixed models.

RESULTS

Traffic pollution was not associated with mean parasympathetic tone and LF/HF for all examined moving averages. In Bayesian linear mixed models, however, BC was related to increased LF/HF, an inter quartile range (IQR) increase in BC was associated with a 6.5% (95% posterior interval (PI): -0.7%, 14.2%) increase in mean LF/HF 24-hours later. The strongest association observed was for the 4-hour moving average (10.1%; 95% PI: 3.0%, 17.6%). The effect of traffic on parasympathetic tone was stronger among diabetic as compared to non-diabetic participants. Specifically, an IQR increase in traffic pollution in the 48-hr prior to the clinic visit was associated with a 44.3% (95% PI: -67.7%, -4.2%) lower mean parasympathetic tone among diabetics, and a 7.7% (95% PI: -18.0%, 41.4%) higher mean parasympathetic tone among non-diabetics.

CONCLUSIONS

BC was associated with adverse changes LF/HF in the elderly. Traffic pollution may decrease parasympathetic tone among diabetic elderly.

The effect of primary organic particles on emergency hospital admissions among the elderly in 3 US cities

BACKGROUND

Fine particle (PM2.5) pollution related to combustion sources has been linked to a variety of adverse health outcomes. Although poorly understood, it is possible that organic carbon (OC) species, particularly those from combustion-related sources, may be partially responsible for the observed toxicity of PM2.5. The toxicity of the OC species may be related to their chemical structures; however, few studies have examined the association of OC species with health impacts.

METHODS

We categorized 58 primary organic compounds by their chemical properties into 5 groups: n-alkanes, hopanes, cyclohexanes, PAHs and isoalkanes. We examined their impacts on the rate of daily emergency hospital admissions among Medicare recipients in Atlanta, GA and Birmingham, AL (2006-2009), and Dallas, TX (2006-2007). We analyzed data in two stages; we applied a case-crossover analysis to simultaneously estimate effects of individual OC species on cause-specific hospital admissions. In the second stage we estimated the OC chemical group-specific effects, using a multivariate weighted regression.

RESULTS

Exposures to cyclohexanes of six days and longer were significantly and consistently associated with increased rate of hospital admissions for CVD (3.40%, 95%CI = (0.64, 6.24%) for 7-d exposure). Similar increases were found for hospitalizations for ischemic heart disease and myocardial infarction. For respiratory related hospital admissions, associations with OC groups were less consistent, although exposure to iso-/anteiso-alkanes was associated with increased respiratory-related hospitalizations.

CONCLUSIONS

Results suggest that week-long exposures to traffic-related, primary organic species are associated with increased rate of total and cause-specific CVD emergency hospital admissions. Associations were significant for cyclohexanes, but not hopanes, suggesting that chemical properties likely play an important role in primary OC toxicity.

Structural equation modeling of the inflammatory response to traffic air pollution

Several epidemiological studies have reported conflicting results on the effect of traffic-related pollutants on markers of inflammation. In a Bayesian framework, we examined the effect of traffic pollution on inflammation using structural equation models (SEMs). We studied measurements of C-reactive protein (CRP), soluble vascular cell adhesion molecule-1 (sVCAM-1), and soluble intracellular adhesion molecule-1 (sICAM-1) for 749 elderly men from the Normative Aging Study. Using repeated measures SEMs, we fit a latent variable for traffic pollution that is reflected by levels of black carbon, carbon monoxide, nitrogen monoxide and nitrogen dioxide to estimate its effect on a latent variable for inflammation that included sICAM-1, sVCAM-1 and CRP. Exposure periods were assessed using 1-, 2-, 3-, 7-, 14- and 30-day moving averages previsit. We compared our findings using SEMs with those obtained using linear mixed models. Traffic pollution was related to increased inflammation for 3-, 7-, 14- and 30-day exposure periods. An inter-quartile range increase in traffic pollution was associated with a 2.3% (95% posterior interval (PI): 0.0-4.7%) increase in inflammation for the 3-day moving average, with the most significant association observed for the 30-day moving average (23.9%; 95% PI: 13.9-36.7%). Traffic pollution adversely impacts inflammation in the elderly. SEMs in a Bayesian framework can comprehensively incorporate multiple pollutants and health outcomes simultaneously in air pollution-cardiovascular epidemiological studies.

Modeling the association between particle constituents of air pollution and health outcomes

There is increasing interest in evaluating the association between specific fine-particle (particles with aerodynamic diameters less than 2.5 µm; PM2.5) constituents and adverse health outcomes rather than focusing solely on the impact of total PM2.5. Because PM2.5 may be related to both constituent concentration and health outcomes, constituents that are more strongly correlated with PM2.5 may appear more closely related to adverse health outcomes than other constituents even if they are not inherently more toxic. Therefore, it is important to properly account for potential confounding by PM2.5 in these analyses. Usually, confounding is due to a factor that is distinct from the exposure and outcome. However, because constituents are a component of PM2.5, standard covariate adjustment is not appropriate. Similar considerations apply to source-apportioned concentrations and studies assessing either short-term or long-term impacts of constituents. Using data on 18 constituents and data from 1,060 patients admitted to a Boston medical center with ischemic stroke in 2003-2008, the authors illustrate several options for modeling the association between constituents and health outcomes that account for the impact of PM2.5. Although the different methods yield results with different interpretations, the relative rankings of the association between constituents and ischemic stroke were fairly consistent across models.

Ambient air pollution and the risk of acute ischemic stroke

BACKGROUND

The link between daily changes in level of ambient fine particulate matter (PM) air pollution (PM <2.5 μm in diameter [PM(2.5)]) and cardiovascular morbidity and mortality is well established. Whether PM(2.5) levels below current US National Ambient Air Quality Standards also increase the risk of ischemic stroke remains uncertain.

METHODS

We reviewed the medical records of 1705 Boston area patients hospitalized with neurologist-confirmed ischemic stroke and abstracted data on the time of symptom onset and clinical characteristics. The PM(2.5) concentrations were measured at a central monitoring station. We used the time-stratified case-crossover study design to assess the association between the risk of ischemic stroke onset and PM(2.5) levels in the hours and days preceding each event. We examined whether the association with PM(2.5) levels differed by presumed ischemic stroke pathophysiologic mechanism and patient characteristics.

RESULTS

The estimated odds ratio (OR) of ischemic stroke onset was 1.34 (95% CI, 1.13-1.58) (P < .001) following a 24-hour period classified as moderate (PM(2.5) 15-40 μg/m(3)) by the US Environmental Protection Agency's (EPA) Air Quality Index compared with a 24-hour period classified as good (≤15 μg/m(3)). Considering PM(2.5) levels as a continuous variable, we found the estimated odds ratio of ischemic stroke onset to be 1.11 (95% CI, 1.03-1.20) (P = .006) per interquartile range increase in PM(2.5) levels (6.4 μg/m(3)). The increase in risk was greatest within 12 to 14 hours of exposure to PM(2.5) and was most strongly associated with markers of traffic-related pollution.

CONCLUSION

These results suggest that exposure to PM(2.5) levels considered generally safe by the US EPA increase the risk of ischemic stroke onset within hours of exposure.

Opposing effects of particle pollution, ozone, and ambient temperature on arterial blood pressure

BACKGROUND

Diabetes increases the risk of hypertension and orthostatic hypotension and raises the risk of cardiovascular death during heat waves and high pollution episodes.

OBJECTIVE

We examined whether short-term exposures to air pollution (fine particles, ozone) and heat resulted in perturbation of arterial blood pressure (BP) in persons with type 2 diabetes mellitus (T2DM).

METHODS

We conducted a panel study in 70 subjects with T2DM, measuring BP by automated oscillometric sphygmomanometer and pulse wave analysis every 2 weeks on up to five occasions (355 repeated measures). Hourly central site measurements of fine particles, ozone, and meteorology were conducted. We applied linear mixed models with random participant intercepts to investigate the association of fine particles, ozone, and ambient temperature with systolic, diastolic, and mean arterial BP in a multipollutant model, controlling for season, meteorological variables, and subject characteristics.

RESULTS

An interquartile increase in ambient fine particle mass [particulate matter (PM) with an aerodynamic diameter of ≤ 2.5 μm (PM2.5)] and in the traffic component black carbon in the previous 5 days (3.54 and 0.25 μg/m3, respectively) predicted increases of 1.4 mmHg [95% confidence interval (CI): 0.0, 2.9 mmHg] and 2.2 mmHg (95% CI: 0.4, 4.0 mmHg) in systolic BP (SBP) at the population geometric mean, respectively. In contrast, an interquartile increase in the 5-day mean of ozone (13.3 ppb) was associated with a 5.2 mmHg (95% CI: -8.6, -1.8 mmHg) decrease in SBP. Higher temperatures were associated with a marginal decrease in BP.

CONCLUSIONS

In subjects with T2DM, PM was associated with increased BP, and ozone was associated with decreased BP. These effects may be clinically important in patients with already compromised autoregulatory function.

Ambient particulate matter and the response to orthostatic challenge in the elderly: the Maintenance of Balance, Independent Living, Intellect, and Zest in the Elderly (MOBILIZE) of Boston study

Short-term elevations in ambient fine particulate matter (PM(2.5)) may increase resting systolic (SBP) and diastolic (DBP) blood pressures, but whether PM(2.5) alters hemodynamic responses to orthostatic challenge has not been studied in detail. We repeatedly measured SBP and DBP during supine rest and 1 and 3 minutes after standing among 747 elderly (aged 78.3±5.3 years, mean±SD) participants from a prospective cohort study. We used linear mixed models to assess the association between change in SBP (ΔSBP=standing SBP-supine SBP) and DBP (ΔDBP) on standing and mean PM(2.5) levels over the preceding 1 to 28 days, adjusting for meteorologic covariates, temporal trends, and medical history. We observed a 1.4-mm Hg (95% CI: 0.0-2.8 mm Hg; P=0.046) higher ΔSBP and a 0.7-mm Hg (95% CI: 0.0-1.4 mm Hg; P=0.053) higher ΔDBP at 1 minute of standing per interquartile range increase (3.8 μg/m(3)) in mean PM(2.5) levels in the past 7 days. ΔSBP and ΔDBP measured 3 minutes after standing were not associated with PM(2.5). Resting DBP (but not SBP or pulse pressure) was positively associated with PM(2.5) at longer averaging periods. Responses were more strongly associated with black carbon than sulfate levels. These associations did not differ significantly according to hypertension status, obesity, diabetes mellitus, or sex. These results suggest that ambient particles can increase resting DBP and exaggerate blood pressure responses to postural changes in elderly people. Increased vasoreactivity during posture change may be responsible, in part, for the adverse effect of ambient particles on cardiovascular health.

Chemical properties of air pollutants and cause-specific hospital admissions among the elderly in Atlanta, Georgia

BACKGROUND

Health risks differ by fine particle (aerodynamic diameter ≤ 2.5 μm) component, although with substantial variability. Traditional methods to assess component-specific risks are limited, suggesting the need for alternative methods.

OBJECTIVES

We examined whether the odds of daily hospital admissions differ by pollutant chemical properties.

METHODS

We categorized pollutants by chemical properties and examined their impacts on the odds of daily hospital admissions among Medicare recipients > 64 years of age in counties in Atlanta, Georgia, for 1998-2006. We analyzed data in two stages. In the first stage we applied a case-crossover analysis to simultaneously estimate effects of 65 pollutants measured in the Aerosol Research and Inhalation Epidemiology Study on cause-specific hospital admissions, controlling for temperature and ozone. In the second stage, we regressed pollutant-specific slopes from the first stage on pollutant properties. We calculated uncertainty estimates using a bootstrap procedure. We repeated the two-stage analyses using coefficients from first-stage models that included single pollutants plus ozone and meteorological variables only. We based our primary analyses on exposures on day of admission.

RESULTS

We found that 24-hr transition metals and alkanes were associated with increased odds [0.26%; 95% confidence interval (CI), 0.02-0.48; and 0.37%; 95% CI, 0.04-0.72, respectively] of hospital admissions for cardiovascular disease (CVD). Transition metals were significantly associated with increased hospital admissions for ischemic heart disease, congestive heart failure, and atrial fibrillation. Increased respiratory-related hospital admissions were significantly associated with alkanes. Aromatics and microcrystalline oxides were significantly associated with decreased CVD- and respiratory-related hospital admissions.

CONCLUSIONS

The two-stage approach showed transition metals to be consistently associated with increased odds of CVD-related hospital admissions.

Particulate air pollution and socioeconomic position in rural and urban areas of the Northeastern United States

OBJECTIVES

Although differential exposure by socioeconomic position (SEP) to hazardous waste and lead is well demonstrated, there is less evidence for particulate air pollution (PM), which is associated with risk of death and illness. This study determined the relationship of ambient PM and SEP across several spatial scales.

METHODS

Geographic information system-based, spatio-temporal models were used to predict PM in the Northeastern United States. Predicted concentrations were related to census tract SEP and racial composition using generalized additive models.

RESULTS

Lower SEP was associated with small, significant increases in PM. Annual PM(10) decreased between 0.09 and 0.93 micrograms per cubic meter and PM(2.5) between 0.02 and 0.94 micrograms per cubic meter for interquartile range increases in income. Decrements in PM with SEP increased with spatial scale, indicating that between-city spatial gradients were greater than within-city differences. The PM-SEP relation in urban tracts was not substantially modified by racial composition.

CONCLUSIONS

Lower compared with higher SEP populations were exposed to higher ambient PM in the Northeastern United States. Given the small percentage change in annual PM(2.5) and PM(10), SEP was not likely a major source of confounding in epidemiological studies of PM, especially those conducted within a single urban/metropolitan area.

Hourly measurements of fine particulate sulfate and carbon aerosols at the Harvard-U.S. Environmental Protection Agency Supersite in Boston

Hourly concentrations of ambient fine particle sulfate and carbonaceous aerosols (elemental carbon [EC], organic carbon [OC], and black carbon [BC]) were measured at the Harvard-U.S. Environmental Protection Agency Supersite in Boston, MA, between January 2007 and October 2008. These hourly concentrations were compared with those made using integrated filter-based measurements over 6-day or 24-hr periods. For sulfate, the two measurement methods showed good agreement. Semicontinuous measurements of EC and OC also agreed (but not as well as for sulfate) with those obtained using 24-hr integrated filter-based and optical BC reference methods. During the study period, 24-hr PM2.5 (particulate matter [PM] < or = 2.5 microm in aerodynamic diameter) concentrations ranged from 1.4 to 37.6 microg/m3, with an average of 9.3 microg/m3. Sulfate as the equivalent of ammonium sulfate accounted for 39.1% of the PM2.5 mass, whereas EC and OC accounted for 4.2 and 35.2%, respectively. Hourly sulfate concentrations showed no distinct diurnal pattern, whereas hourly EC and BC concentrations peaked during the morning rush hour between 7:00 and 9:00 a.m. OC concentrations also exhibited nonpronounced, small peaks during the day, most likely related to traffic, secondary organic aerosol, and local sources, respectively.

Systemic inflammation, heart rate variability and air pollution in a cohort of senior adults

OBJECTIVES

Short-term elevation of ambient particulate air pollution has been associated with autonomic dysfunction and increased systemic inflammation, but the interconnections between these pathways are not well understood. We examined the association between inflammation and autonomic dysfunction and effect modification of inflammation on the association between air pollution and heart rate variability (HRV) in elderly subjects.

METHODS

25 elderly subjects in Steubenville, Ohio, were followed up to 24 times with repeated 30-min ECG Holter monitoring (545 observations). C-reactive protein (CRP), fibrinogen, interleukin-6 (IL-6), soluble inter-cellular adhesion molecule 1 (sICAM-1), and white blood cell and platelet counts were measured in peripheral blood samples collected in the first month of the study. Increased systemic inflammation was defined for subjects within the upper 20% of the distribution for each marker. A central ambient monitoring station provided daily fine particle (PM(2.5)) and sulphate (SO(4)(2-)) data. Linear mixed models were used to identify associations between inflammatory markers and HRV and to assess effect modification of the association between air pollution and HRV due to inflammatory status.

RESULTS

A 5.8 mg/l elevation in CRP was associated with decreases of between -8% and -33% for time and frequency domain HRV outcomes. A 5.1 microg/m(3) increase in SO(4)(2-) on the day before the health assessment was associated with a decrease of -6.7% in the SD of normal RR intervals (SDNN) (95% CI -11.8% to -1.3%) in subjects with elevated CRP, but not in subjects with lower CRP (p value interaction=0.04), with similar findings for PM(2.5).

CONCLUSIONS

Increased systemic inflammation is associated with autonomic dysfunction in the elderly. Air pollution effects on reduced SDNN are stronger in subjects with elevated systemic inflammation.

Traffic-related air pollution and QT interval: modification by diabetes, obesity, and oxidative stress gene polymorphisms in the normative aging study

BACKGROUND

Acute exposure to ambient air pollution has been associated with acute changes in cardiac outcomes, often within hours of exposure.

OBJECTIVES

We examined the effects of air pollutants on heart-rate-corrected QT interval (QTc), an electrocardiographic marker of ventricular repolarization, and whether these associations were modified by participant characteristics and genetic polymorphisms related to oxidative stress.

METHODS

We studied repeated measurements of QTc on 580 men from the Veterans Affairs Normative Aging Study (NAS) using mixed-effects models with random intercepts. We fitted a quadratic constrained distributed lag model to estimate the cumulative effect on QTc of ambient air pollutants including fine particulate matter <or= 2.5 microm in aerodynamic diameter (PM2.5), ozone (O3), black carbon (BC), nitrogen dioxide (NO2), carbon monoxide (CO), and sulfur dioxide (SO2) concentrations during the 10 hr before the visit. We genotyped polymorphisms related to oxidative stress and analyzed pollution-susceptibility score interactions using the genetic susceptibility score (GSS) method.

RESULTS

Ambient traffic pollutant concentrations were related to longer QTc. An interquartile range (IQR) change in BC cumulative during the 10 hr before the visit was associated with increased QTc [1.89 msec change; 95% confidence interval (CI), -0.16 to 3.93]. We found a similar association with QTc for an IQR change in 1-hr BC that occurred 4 hr before the visit (2.54 msec change; 95% CI, 0.28-4.80). We found increased QTc for IQR changes in NO2 and CO, but the change was statistically insignificant. In contrast, we found no association between QTc and PM2.5, SO2, and O3. The association between QTc and BC was stronger among participants who were obese, who had diabetes, who were nonsmokers, or who had higher GSSs.

CONCLUSIONS

Traffic-related pollutants may increase QTc among persons with diabetes, persons who are obese, and nonsmoking elderly individuals; the number of genetic variants related to oxidative stress increases this effect.

Reduction in heart rate variability with traffic and air pollution in patients with coronary artery disease

INTRODUCTION

Ambient particulate pollution and traffic have been linked to myocardial infarction and cardiac death risk. Possible mechanisms include autonomic cardiac dysfunction.

METHODS

In a repeated-measures study of 46 patients 43-75 years of age, we investigated associations of central-site ambient particulate pollution, including black carbon (BC) (a marker for regional and local traffic), and report of traffic exposure with changes in half-hourly averaged heart rate variability (HRV), a marker of autonomic function measured by 24-hr Holter electrocardiogram monitoring. Each patient was observed up to four times within 1 year after a percutaneous intervention for myocardial infarction, acute coronary syndrome without infarction, or stable coronary artery disease (4,955 half-hour observations). For each half-hour period, diary data defined whether the patient was home or not home, or in traffic.

RESULTS

A decrease in high frequency (HF; an HRV marker of vagal tone) of 16.4% [95% confidence interval (CI), 20.7 to 11.8%] was associated with an interquartile range of 0.3-microg/m3 increase in prior 5-day averaged ambient BC. Decreases in HF were independently associated both with the previous 2-hr averaged BC (10.4%; 95% CI, 15.4 to 5.2%) and with being in traffic in the previous 2 hr (38.5%; 95% CI, 57.4 to 11.1%). We also observed independent responses for particulate air matter with aerodynamic diameter < or = 2.5 microm and for gases (ozone or nitrogen dioxide).

CONCLUSION

After hospitalization for coronary artery disease, both particulate pollution and being in traffic, a marker of stress and pollution, were associated with decreased HRV.

Effects of exposure measurement error in the analysis of health effects from traffic-related air pollution

In large epidemiological studies, many researchers use surrogates of air pollution exposure such as geographic information system (GIS)-based characterizations of traffic or simple housing characteristics. It is important to evaluate quantitatively these surrogates against measured pollutant concentrations to determine how their use affects the interpretation of epidemiological study results. In this study, we quantified the implications of using exposure models derived from validation studies, and other alternative surrogate models with varying amounts of measurement error on epidemiological study findings. We compared previously developed multiple regression models characterizing residential indoor nitrogen dioxide (NO(2)), fine particulate matter (PM(2.5)), and elemental carbon (EC) concentrations to models with less explanatory power that may be applied in the absence of validation studies. We constructed a hypothetical epidemiological study, under a range of odds ratios, and determined the bias and uncertainty caused by the use of various exposure models predicting residential indoor exposure levels. Our simulations illustrated that exposure models with fairly modest R(2) (0.3 to 0.4 for the previously developed multiple regression models for PM(2.5) and NO(2)) yielded substantial improvements in epidemiological study performance, relative to the application of regression models created in the absence of validation studies or poorer-performing validation study models (e.g., EC). In many studies, models based on validation data may not be possible, so it may be necessary to use a surrogate model with more measurement error. This analysis provides a technique to quantify the implications of applying various exposure models with different degrees of measurement error in epidemiological research.

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

This analysis examines differences between measured ambient indoor, and personal sulfate concentrations across cities, seasons, and individuals to elucidate how these differences may impact PM2.5 exposure measurement error. Data were analyzed from four panel studies conducted in Atlanta, Baltimore, Boston, and Steubenville (OH). Among the study locations, 1912 person-days of personal sulfate data were collected over 396 days involving 245 individual sampling sessions. Long-term differences in ambient and personal levels averaged over time are examined. Differences between averaged ambient and personal sulfate among and within cities were observed, driven by between subject and city differences in sulfate infiltration, F(inf), from outdoors to indoors. Neglecting this source of variability in associations may introduce bias in studies examining long-term exposures and chronic health. Indoor sulfate was highly correlated with and similar in magnitude to personal sulfate, suggesting indoor PM monitoring may be another means of characterizing true exposure variability.

Factors influencing relationships between personal and ambient concentrations of gaseous and particulate pollutants

Previous exposure studies have shown considerable inter-subject variability in personal-ambient associations. This paper investigates exposure factors that may be responsible for inter-subject variability in these personal-ambient associations. The personal and ambient data used in this paper were collected as part of a personal exposure study conducted in Boston, MA, during 1999-2000. This study was one of a group of personal exposure panel studies funded by the U.S. Environmental Protection Agency's National Exposure Research Laboratory to address areas of exposure assessment warranting further study, particularly associations between personal exposures and ambient concentrations of particulate matter and gaseous co-pollutants. Twenty-four-hour integrated personal, home indoor, home outdoor and ambient sulfate, elemental carbon (EC), PM(2.5), ozone (O(3)), nitrogen dioxide (NO(2)) and sulfur dioxide were measured simultaneously each day. Fifteen homes in the Boston area were measured for 7 days during winter and summer. A previous paper explored the associations between personal-indoor, personal-outdoor, personal-ambient, indoor-outdoor, indoor-ambient and outdoor-ambient PM(2.5), sulfate and EC concentrations. For the current paper, factors that may affect personal exposures were investigated, while controlling for ambient concentrations. The data were analyzed using mixed effects regression models. Overall personal-ambient associations were strong for sulfate during winter (p<0.0001) and summer (p<0.0001) and PM(2.5) during summer (p<0.0001). The personal-ambient mixed model slope for PM(2.5) during winter but was not significant at p=0.10. Personal exposures to most pollutants, with the exception of NO(2), increased with ventilation and time spent outdoors. An opposite pattern was found for NO(2) likely due to gas stoves. Personal exposures to PM(2.5) and to traffic-related pollutants, EC and NO(2), were higher for those individuals living close to a major road. Both personal and indoor sulfate and PM(2.5) concentrations were higher for homes using humidifiers. The impact of outdoor sources on personal and indoor concentrations increased with ventilation, whereas an opposite effect was observed for the impact of indoor sources.

Rapid DNA methylation changes after exposure to traffic particles

RATIONALE

Exposure to particulate air pollution has been related to increased hospitalization and death, particularly from cardiovascular disease. Lower blood DNA methylation content is found in processes related to cardiovascular outcomes, such as oxidative stress, aging, and atherosclerosis.

OBJECTIVES

We evaluated whether particulate pollution modifies DNA methylation in heavily methylated sequences with high representation throughout the human genome.

METHODS

We measured DNA methylation of long interspersed nucleotide element (LINE)-1 and Alu repetitive elements by quantitative polymerase chain reaction-pyrosequencing of 1,097 blood samples from 718 elderly participants in the Boston area Normative Aging Study. We used covariate-adjusted mixed models to account for within-subject correlation in repeated measures. We estimated the effects on DNA methylation of ambient particulate pollutants (black carbon, particulate matter with aerodynamic diameter < or = 2.5 microm [PM2.5], or sulfate) in multiple time windows (4 h to 7 d) before the examination. We estimated standardized regression coefficients (beta) expressing the fraction of a standard deviation change in DNA methylation associated with a standard deviation increase in exposure.

MEASUREMENTS AND MAIN RESULTS

Repetitive element DNA methylation varied in association with time-related variables, such as day of the week and season. LINE-1 methylation decreased after recent exposure to higher black carbon (beta = -0.11; 95% confidence interval [CI], -0.18 to -0.04; P = 0.002) and PM2.5 (beta = -0.13; 95% CI, -0.19 to -0.06; P < 0.001 for the 7-d moving average). In two-pollutant models, only black carbon, a tracer of traffic particles, was significantly associated with LINE-1 methylation (beta = -0.09; 95% CI, -0.17 to -0.01; P = 0.03). No association was found with Alu methylation (P > 0.12).

CONCLUSIONS

We found decreased repeated-element methylation after exposure to traffic particles. Whether decreased methylation mediates exposure-related health effects remains to be determined.

Predicting chronic fine and coarse particulate exposures using spatiotemporal models for the Northeastern and Midwestern United States

BACKGROUND

Chronic epidemiologic studies of particulate matter (PM) are limited by the lack of monitoring data, relying instead on citywide ambient concentrations to estimate exposures. This method ignores within-city spatial gradients and restricts studies to areas with nearby monitoring data. This lack of data is particularly restrictive for fine particles (PM with aerodynamic diameter < 2.5 microm; PM(2.5)) and coarse particles (PM with aerodynamic diameter 2.5-10 microm; PM(10-2.5)), for which monitoring is limited before 1999. To address these limitations, we developed spatiotemporal models to predict monthly outdoor PM(2.5) and PM(10-2.5) concentrations for the northeastern and midwestern United States.

METHODS

For PM(2.5), we developed models for two periods: 1988-1998 and 1999-2002. Both models included smooth spatial and regression terms of geographic information system-based and meteorologic predictors. To compensate for sparse monitoring data, the pre-1999 model also included predicted PM(10) (PM with aerodynamic diameter < 10 microm) and extinction coefficients (km(-1)). PM(10-2.5) levels were estimated as the difference in monthly predicted PM(10) and PM(2.5), with predicted PM(10) from our previously developed PM(10) model.

RESULTS

Predictive performance for PM(2.5) was strong (cross-validation R2 = 0.77 and 0.69 for post-1999 and pre-1999 PM(2.5) models, respectively) with high precision (2.2 and 2.7 microg/m3, respectively). Models performed well irrespective of population density and season. Predictive performance for PM(10-2.5) was weaker (cross-validation R2 = 0.39) with lower precision (5.5 microg/m3). PM(10-2.5) levels exhibited greater local spatial variability than PM(10) or PM(2.5), suggesting that PM(2.5) measurements at ambient monitoring sites are more representative for surrounding populations than for PM(10) and especially PM(10-2.5).

CONCLUSIONS

We provide semiempirical models to predict spatially and temporally resolved long-term average outdoor concentrations of PM(2.5) and PM(10-2.5) for estimating exposures of populations living in the northeastern and midwestern United States.

Weather and air pollution as triggers of severe headaches

BACKGROUND

The roles of weather conditions and air pollution as triggers of headache have been inconsistent in previous, generally small studies.

METHODS

We performed a case-crossover study of 7,054 patients seen in a single emergency department between May 2000 and December 2007 with a primary discharge diagnosis of headache. We compared levels of temperature, barometric pressure, humidity, fine particulate matter, black carbon, and nitrogen and sulfur dioxides during the three 24-hour periods preceding presentation with corresponding levels on the remaining occurrences of that day of the week in a given month, using local meteorologic and pollutant monitors.

RESULTS

Higher mean ambient temperature in the 24 hours preceding hospital presentation positively and linearly increased the acute risk of headache (odds ratio [OR] for a 5 degrees C increment 1.075; 95% confidence interval [CI], 1.021-1.133; p = 0.006) [corrected]. Higher risk was observed for cases with and without a discharge diagnosis of migraine and for cases between October and March or between April and September. Lower barometric pressure also increased the risk of nonmigraine cases in the 48 to 72 hours before hospitalization (OR 0.939 per 5 mm Hg; 95% CI, 0.902-0.978; p = 0.002). Current levels of pollutants did not influence the risk of headache.

CONCLUSIONS

Higher ambient temperature and, to a lesser degree, lower barometric pressure led to a transient increase in risk of headache requiring emergency department evaluation. We did not find clear association of air pollutants with risk, but cannot exclude effects of air pollution of the magnitude previously observed for stroke and other cardiovascular events.

Rapid DNA methylation changes after exposure to traffic particles

RATIONALE

Exposure to particulate air pollution has been related to increased hospitalization and death, particularly from cardiovascular disease. Lower blood DNA methylation content is found in processes related to cardiovascular outcomes, such as oxidative stress, aging, and atherosclerosis.

OBJECTIVES

We evaluated whether particulate pollution modifies DNA methylation in heavily methylated sequences with high representation throughout the human genome.

METHODS

We measured DNA methylation of long interspersed nucleotide element (LINE)-1 and Alu repetitive elements by quantitative polymerase chain reaction-pyrosequencing of 1,097 blood samples from 718 elderly participants in the Boston area Normative Aging Study. We used covariate-adjusted mixed models to account for within-subject correlation in repeated measures. We estimated the effects on DNA methylation of ambient particulate pollutants (black carbon, particulate matter with aerodynamic diameter < or = 2.5 microm [PM2.5], or sulfate) in multiple time windows (4 h to 7 d) before the examination. We estimated standardized regression coefficients (beta) expressing the fraction of a standard deviation change in DNA methylation associated with a standard deviation increase in exposure.

MEASUREMENTS AND MAIN RESULTS

Repetitive element DNA methylation varied in association with time-related variables, such as day of the week and season. LINE-1 methylation decreased after recent exposure to higher black carbon (beta = -0.11; 95% confidence interval [CI], -0.18 to -0.04; P = 0.002) and PM2.5 (beta = -0.13; 95% CI, -0.19 to -0.06; P < 0.001 for the 7-d moving average). In two-pollutant models, only black carbon, a tracer of traffic particles, was significantly associated with LINE-1 methylation (beta = -0.09; 95% CI, -0.17 to -0.01; P = 0.03). No association was found with Alu methylation (P > 0.12).

CONCLUSIONS

We found decreased repeated-element methylation after exposure to traffic particles. Whether decreased methylation mediates exposure-related health effects remains to be determined.

Whole house particle removal and clean air delivery rates for in-duct and portable ventilation systems

A novel method for determining whole house particle removal and clean air delivery rates attributable to central and portable ventilation/air cleaning systems is described. The method is used to characterize total and air-cleaner-specific particle removal rates during operation of four in-duct air cleaners and two portable air-cleaning devices in a fully instrumented test home. Operation of in-duct and portable air cleaners typically increased particle removal rates over the baseline rates determined in the absence of operating a central fan or an indoor air cleaner. Removal rates of 0.3- to 0.5-microm particles ranged from 1.5 hr(-1) during operation of an in-duct, 5-in. pleated media filter to 7.2 hr(-1) for an in-duct electrostatic air cleaner in comparison to a baseline rate of 0 hr(-1) when the air handler was operating without a filter. Removal rates for total particulate matter less than 2.5 microm in aerodynamic diameter (PM2.5) mass concentrations were 0.5 hr(-1) under baseline conditions, 0.5 hr(-1) during operation of three portable ionic air cleaners, 1 hr(-1) for an in-duct 1-in. media filter, 2.4 hr(-1) for a single high-efficiency particle arrestance (HEPA) portable air cleaner, 4.6 hr(-1) for an in-duct 5-in. media filter, 4.7 hr(-1) during operation of five portable HEPA filters, 6.1 hr(-1) for a conventional in-duct electronic air cleaner, and 7.5 hr(-1) for a high efficiency in-duct electrostatic air cleaner. Corresponding whole house clean air delivery rates for PM2.5 attributable to the air cleaner independent of losses within the central ventilation system ranged from 2 m3/min for the conventional media filter to 32 m3/min for the high efficiency in-duct electrostatic device. Except for the portable ionic air cleaner, the devices considered here increased particle removal indoors over baseline deposition rates.

Ambient site, home outdoor and home indoor particulate concentrations as proxies of personal exposures

Despite strong longitudinal associations between particle personal exposures and ambient concentrations, previous studies have found considerable inter-personal variability in these associations. Factors contributing to this inter-personal variability are important to identify in order to improve our ability to assess particulate exposures for individuals. This paper examines whether ambient, home outdoor and home indoor particle concentrations can be used as proxies of corresponding personal exposures. We explore the strength of the associations between personal, home indoor, home outdoor and central outdoor monitoring site ("ambient site") concentrations of sulfate, fine particle mass (PM(2.5)) and elemental carbon (EC) by season and subject for 25 individuals living in the Boston, MA, USA area. Ambient sulfate concentrations accounted for approximately 70 to 80% of the variability in personal and indoor sulfate levels. Correlations between ambient and personal sulfate, however, varied by subject (0.1-1.0), with associations between personal and outdoor sulfate concentrations generally mirroring personal-ambient associations (median subject-specific correlations of 0.8 to 0.9). Ambient sulfate concentrations are good indicators of personal exposures for individuals living in the Boston area, even though their levels may differ from actual personal exposures. The strong associations for sulfate indicate that ambient concentrations and housing characteristics are the driving factors determining personal sulfate exposures. Ambient PM(2.5) and EC concentrations were more weakly associated with corresponding personal and indoor levels, as compared to sulfate. For EC and PM(2.5), local traffic, indoor sources and/or personal activities can significantly weaken associations with ambient concentrations. Infiltration was shown to impact the ability of ambient concentrations to reflect exposures with higher exposures to particles from ambient sources during summer. In contrast in the winter, lower infiltration can result in a greater contribution of indoor sources to PM(2.5) and EC exposures. Placing EC monitors closer to participants' homes may reduce exposure error in epidemiological studies of traffic-related particles, but this reduction in exposure error may be greater in winter than summer. It should be noted that approximately 20% of the EC data were below the field limit of detection, making it difficult to determine if the weaker associations with the central site for EC were merely a result of methodological limitations.

Spatio-temporal modeling of chronic PM10 exposure for the Nurses' Health Study

Chronic epidemiological studies of airborne particulate matter (PM) have typically characterized the chronic PM exposures of their study populations using city- or countywide ambient concentrations, which limit the studies to areas where nearby monitoring data are available and which ignore within-city spatial gradients in ambient PM concentrations. To provide more spatially refined and precise chronic exposure measures, we used a Geographic Information System (GIS)-based spatial smoothing model to predict monthly outdoor PM(10) concentrations in the northeastern and midwestern United States. This model included monthly smooth spatial terms and smooth regression terms of GIS-derived and meteorological predictors. Using cross-validation and other pre-specified selection criteria, terms for distance to road by road class, urban land use, block group and county population density, point- and area-source PM(10) emissions, elevation, wind speed, and precipitation were found to be important determinants of PM(10) concentrations and were included in the final model. Final model performance was strong (cross-validation R(2)=0.62), with little bias (-0.4 mug m(-3)) and high precision (6.4 mug m(-3)). The final model (with monthly spatial terms) performed better than a model with seasonal spatial terms (cross-validation R(2)=0.54). The addition of GIS-derived and meteorological predictors improved predictive performance over spatial smoothing (cross-validation R(2)=0.51) or inverse distance weighted interpolation (cross-validation R(2)=0.29) methods alone and increased the spatial resolution of predictions. The model performed well in both rural and urban areas, across seasons, and across the entire time period. The strong model performance demonstrates its suitability as a means to estimate individual-specific chronic PM(10) exposures for large populations.

Associations between measures of socioeconomic position and chronic nitrogen dioxide exposure in Worcester, Massachusetts

Census block-group-specific predicted outdoor nitrogen dioxide (NO(2); a marker of traffic pollution) levels and four census block group socioeconomic position (SEP) measures were used to evaluate whether chronic exposures to traffic-related air pollutants are higher in areas with lower SEP, after controlling for spatial autocorrelation in mixed models. NO(2) levels were predicted using a geographic information system (GIS)-based spatiotemporal model that was validated with measured NO(2) concentrations. The GIS-based model predicted weekly NO(2) concentrations with high accuracy (slope of 0.98 from regression of held-out observations on predictions) and precision (cross-validation mean absolute error of 2.2 ppb). The model performed well in both rural and urban areas and warm and cold seasons. Estimated mean block group NO(2) concentrations were significantly negatively associated with median household income, and positively associated with poverty, crowding, and low educational attainment rates after controlling for spatial autocorrelation. Results indicated that a standard deviation (3.5 ppb) increase in block group NO(2) concentrations was associated with a $9090 decrease in median household income. Results suggest that on average those with lower SEP experience higher chronic exposure to outdoor NO(2).

Effects of ambient air pollution on functional status in patients with chronic congestive heart failure: a repeated-measures study

BACKGROUND

Studies using administrative data report a positive association between ambient air pollution and the risk of hospitalization for congestive heart failure (HF). Circulating levels of B-type natriuretic peptide (BNP) are directly associated with cardiac hemodynamics and symptom severity in patients with HF and, therefore, serves as a marker of functional status. We tested the hypothesis that BNP levels would be positively associated with short-term changes in ambient pollution levels among 28 patients with chronic stable HF and impaired systolic function.

METHODS

BNP was measured in whole blood at 0, 6, and 12 weeks. We used linear mixed models to evaluate the association between fine particulate matter (PM2.5), carbon monoxide, sulfur dioxide, nitrogen dioxide, ozone, and black carbon and log(BNP). Lags of 0 to 3 days were considered in separate models. We calculated the intraclass correlation coefficient and within-subject coefficient of variation as measures of reproducibility.

RESULTS

We found no association between any pollutant and measures of BNP at any lag. For example, a 10 microg/m3 increase in PM2.5 was associated with a 0.8% (95% CI: -16.4, 21.5; p = 0.94) increase in BNP on the same day. The within-subject coefficient of variation was 45% on the natural scale and 9% on the log scale.

CONCLUSION

These results suggest that serial BNP measurements are unlikely to be useful in a longitudinal study of air pollution-related acute health effects. The magnitude of expected ambient air pollution health effects appears small in relation to the considerable within-person variability in BNP levels in this population.

Short-Term Effects of Air Pollution on Heart Rate Variability in Senior Adults in Steubenville, Ohio

OBJECTIVE

We examined the association between ambient air pollution levels and heart rate variability (HRV) in a panel study of 32 subjects.

METHODS

We used linear mixed models to analyze the effects of fine particles (PM2.5), sulfate (SO4), elemental carbon (EC), and gases on log-transformed standard deviation of normal RR intervals (SDNN), mean square of differences between adjacent RR intervals (r-MSSD), and high- and low-frequency power (HF, LF).

RESULTS

An interquartile range (IQR) increase of 5.1 mug/m in SO4 on the previous day was associated with a decrease of -3.3% SDNN (95% confidence = -6.0% to -0.5%), -5.6% r-MSSD (-10.7% to -0.2%), and -10.3% HF (-19.5% to -0.1%). Associations with total PM2.5 were similar. HRV was not associated with EC, NO2, SO2, or O3.

CONCLUSION

In addition to traffic-related particles, elevated levels of sulfate particles may also adversely affect autonomic function.