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"In conclusion, we found that higher levels of exposure to ambient PM [particulate matter (PM) air pollution] are associated with worse cognitive decline. Importantly, these associations were present at levels of PM exposure typical in many areas of the United States....PM2.5 exposure increases the risk of ischemic stroke at levels below those currently considered safe under US regulations. These associations can be observed within hours of exposure and are most strongly associated with pollution from local or transported traffic emissions. If pollution levels decline with regulation, data on timing of stroke onset, patient clinical characteristics, and stroke mechanisms will be essential for proper evaluation of the clinical benefits of pollution control on stroke risk."

By Michael Smith, North American Correspondent, MedPage Today
Published: February 13, 2012

Action Points

· Note that one study indicates that higher levels of long-term exposure to both coarse and fine particulate matter were associated with significantly faster cognitive decline in women ages 70 to 81.

· Note also that in another study, the risk for ischemic stroke was elevated acutely following short-term exposure to higher levels of ambient fine particulate matter.

Airborne pollution can have serious consequences for the brain and the heart even at typical levels of exposure, according to the results of two studies published in the Feb. 13 issue of Archives of Internal Medicine.

In one analysis, researchers led by Gregory Wellenius, ScD, of Brown University in Providence, R.I., found that short-term exposure to fine particulate matter - even at levels allowed by the EPA - can increase the risk of ischemic stroke.

In the other study, a team led by Jennifer Weuve, ScD, of Rush University Medical Center in Chicago, and colleagues found that long-term exposure to particulate matter speeded up cognitive decline in older women.

The first report "adds to the already strong evidence linking (particulate matter) to cardiovascular effects," wrote Rajiv Bhatia, MD, of the San Francisco Department of Public Health, in an accompanying commentary.

And, he added, the cognition study suggests that "we may not fully understand the breadth of (particulate matter) health burdens."

Bhatia concluded that controlling particulate matter is technically feasible, but needs "increased efforts to assess exposure at the community level, more stringent and creative regulatory initiatives, and political support."

Wellenius and colleagues studied links between daily variation in fine particulate matter - particles less than 2.5 micrometers in diameter - and stroke incidence in the Boston area.

They drew data from medical records of 1,705 patients admitted to a single institution with neurologist-confirmed ischemic stroke between April 1, 1999, and Oct. 31, 2008.

Fine matter concentrations were measured at a central monitoring station, using EPA guidelines that define moderate air quality as between 15 and 40 micrograms per cubic meter of air and good air quality as 15 micrograms or lower.

The study period included only days in which the air quality was good or moderate; the researchers excluded 11 days in which it exceeded 40 micrograms per cubic meter.

They found that the estimated odds ratio of ischemic stroke onset was 1.34 (95% CI 1.13 to 1.58) following a 24-hour period classified as moderate, compared with a period in which the air quality was good. The risk increase was significant at P<0.001.

They also found that the relationship between higher particulate levels and increased risk of stroke was linear, strongest within 12 hours of exposure, and was seen among patients with strokes caused by large-artery atherosclerosis or small-vessel occlusion but not cardioembolism.

The risk was more strongly associated with markers of traffic pollution - such as black carbon and NO2 - than with particles linked to nontraffic sources, they reported.

Although the findings add to the evidence linking stroke and air pollution, there are some "unique" aspects, according to Robert Brook, MD, of the University of Michigan Ann Arbor, and Sanjay Rajagopalan, MD, of the Ohio State University Medical Center in Columbus.

Specifically, they noted in an accompanying commentary, "the extremely rapid increase in stroke risk is an important novel insight" that suggests that current regulatory focus on daily and yearly average concentrations may be missing the boat.

For the cognition study, Weuve and colleagues turned to the long-running Nurses' Health Study, which began in 1976 with more than 121,000 participants.

Between 1995 and 2001, participants 70 or older with no history of stroke were asked to take part in a study of cognition and 19,049 agreed. Cognitive testing was done by telephone three times, with about two years between interviews.

The researchers tracked changes in cognition, looking for associations between both fine and coarse particulate matter, defined, respectively, as smaller than 2.5 micrometers in diameter and between 2.5 and 10 micrometers.

Particulate matter was measured using EPA monitoring data, adjusted to estimate local exposure for each participant.

Analysis showed that higher levels of long-term exposure to both grades of pollution were associated with "significantly faster cognitive decline," the researchers found. Specifically:

· The two-year decline on a global score was 0.020 units worse for every increase of 10 micrograms per cubic meter in long-term exposure to coarse particles.

· Similarly, the two-year decline was 0.018 units worse for every increase of 10 micrograms per cubic meter in long-term fine particle exposure.

The differences, Weuve and colleagues reported, were similar to those between women in the study who were approximately two years apart in age.

The associations, they reported, were found at pollution levels typical in many areas, suggesting that pollution control might be a way to reduce the "future population burden of age-related cognitive decline, and, eventually, dementia."

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Commentary

Policy and Regulatory Action Can Reduce Harms From Particulate Pollution

Comment on "Exposure to Particulate Air Pollution and Cognitive Decline in Older Women"


Rajiv Bhatia, MD, MPH

Arch Intern Med. 2012

Particulate matter (PM), a heterogeneous mixture that includes chemicals, metals, and soils, is an air pollutant that contributes to multiple poor health outcomes; small particles, which are able to reach deep into the lungs, cause the greatest harm. Sources of fine PM emissions into the air include motorized vehicles, diesel-powered equipment, industrial and residential fuel combustion, and other industrial processes. Reviews of the health effects of PM2.5, which is the fraction of airborne particles less than 2.5 μm in diameter, have established that short- and long-term exposure has causal effects on cardiovascular outcomes such as ischemic heart disease and premature mortality and likely has effects on respiratory morbidity.1 Toxicological evidence from animal and human studies supports this epidemiologic evidence, demonstrating the physiological effects of PM2.5 on the cardiovascular system. The association between ambient PM2.5 concentration and ischemic stroke reported in this issue adds to the already strong evidence linking PM2.5 to cardiovascular effects (Wellenius et al2), and the analysis on cognitive function shows that we may not fully understand the breadth of PM health burdens (Weuve et al3). The strong and growing evidence on the harms of PM2.5 demands scrutiny of societal efforts to reduce exposure.

Particulates have been a target for environmental regulation since notorious smog events, such as the one in London, England, in 1952 that resulted in thousands of untimely deaths. Today in the United States, under the Clean Air Act (42 USC 7401 et seq), the US Environmental Protection Agency (EPA) is required to establish air quality standards for PM adequate to protect public health. Since 1997, the primary federal standard for PM2.5 as an annual average has been 15 μg/m3. To achieve the standards, the EPA adopts regulations to restrict emissions from major sources. For example, federal fuel economy standards and rules for diesel engines and equipment will reduce particle emissions from engines. In addition, the EPA requires individual states to develop plans (State Implementation Plans) to achieve compliance with ambient air quality standards.

The EPA's implementation of the Clean Air Act has resulted in progress in reducing PM2.5 at an aggregate, nationwide level. On average, the concentration of PM2.5 has fallen since 1999, and reported levels at the majority of monitoring sites are below the federal standard. Although this is a significant achievement, evidence also suggests that exposure to PM2.5 still contributes to a substantial population health burden as well as to health disparities. Ambient concentrations of PM2.5 vary greatly among regions with levels exceeding the current national standard in several major population centers.

An issue deserving close public health attention is the adequacy of the current federal PM2.5 annual standard. Evidence demonstrates that negative health effects occur at current levels of exposure including at levels below ambient air quality standards4 (Wellenius et al2). The state of California adopted the more protective standard (12 μg/m3) in 2002, and at the last federal regulatory review, completed in 2006, the EPA Clean Air Scientific Advisory Committee concluded that that the existing federal standard was not protective of public health, yet the EPA administrator retained that standard. The EPA's own risk assessment conducted for the 2006 review concluded that lowering the proposed PM2.5 standard just by 1 μg/m3 (to 14 μg /m3) would have resulted in 1900 fewer annual deaths, 3700 fewer myocardial infarctions, and 3450 fewer hospitalizations and emergency department visits.5 The EPA is currently in the midst of another regulatory review, which has confirmed the health benefits of lowering PM2.5 concentration and recommended that the EPA administrator lower the annual standard to within the range of 11 to 12 μg/m3.6

Also deserving attention are the spatial and demographic disparities in PM2.5 exposure. Approximately 1.5 million people in the Los Angeles Air Basin, California, live in a near-highway environment (as detailed by Robert Yunke in his comments to the Clean Air Scientific Advisory Committee [CASAC] ambient air monitoring & methods subcommittee on EPA's draft near-road monitoring guidance; 2010 [hereinafter, Yunke]), and the population in these areas is exposed to concentrations of PM2.5 substantially higher than the regional average.7 Nationally, approximately 45% of the urban population lives near major roads.8 Ethnic minorities and lower-income populations are more likely to live near urban PM2.5 sources such as busy roadways, maritime ports, and freight distribution centers.9-11 Non-Hispanic blacks are consistently overrepresented in communities with the highest levels of PM2.5.12 Research has also estimated the degree to which these exposure disparities contribute to disparities in respiratory and cardiovascular diseases.13

Effective and equitable prevention of avoidable PM2.5 health effects demands reducing sources where they have the greatest contributions to human exposure and exposure disparities. Unfortunately, the current federal monitoring network is insufficient to fully capture intraregional variation in the distribution of exposure (Yunke). Concentrations of PM2.5 are known to be much higher near busy highways, rail yards, and ports than at regional monitors, but inadequate intraregional assessment means that these higher levels are often not considered by regulators. Routine collection of more spatially refined data, including monitoring near known hotspots, would help. Furthermore, technology to assess intraregional exposure variation now exists with computational modeling approaches such as dispersion modeling and land use regression.14

Several available approaches exist to reduce hotspots of exposure as well as exposure disparities. New regulations might prohibit the location or expansion of existing roadway facilities, ports, or distribution centers unless they effectively mitigate air pollution exposure disparities. Innovative technological strategies, such as calming speed and smoothing traffic flow on highways, could also substantially reduce near-roadway concentrations of PM.15 Where known unhealthy levels of exposure exist, it is also prudent to limit the growth of the population. This suggests that state and local land use regulation can play an important role in protection from PM2.5. California has begun to limit the location of new sensitive land uses (eg, residences, schools) near hotspots of PM2.5.16 Enhancing building performance, through improvements in ventilation and filtration, can both reduce indoor PM2.5 concentrations and provide other health benefits.17 In 2008, the city of San Francisco, California, adopted a novel public health law requiring enhanced ventilation systems for residential development near traffic-related PM2.5 hotspots, and the city is now working to improve ventilation in existing residences within hotspot zones.18

Improved control of human exposure to PM2.5 is technically feasible but will required increased efforts to assess exposure at the community level, more stringent and creative regulatory initiatives, and political support. Physicians, who are already responding to the human consequences of particulate pollution, can be effective advocates for these protections.

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Exposure to Particulate Air Pollution and Cognitive Decline in Older Women

Jennifer Weuve, MPH, ScD; Robin C. Puett, MPH, PhD; Joel Schwartz, PhD; Jeff D. Yanosky, MS, ScD; Francine Laden, MS, ScD; Francine Grodstein, ScD

Arch Intern Med. 2012

ABSTRACT

Background Chronic exposure to particulate air pollution may accelerate cognitive decline in older adults, although data on this association are limited. Our objective was to examine long-term exposure to particulate matter (PM) air pollution, both coarse ([PM 2.5-10 μm in diameter [PM2.5-10]) and fine (PM <2.5 μm in diameter [PM2.5]), in relation to cognitive decline.

Methods The study population comprised the Nurses' Health Study Cognitive Cohort, which included 19 409 US women aged 70 to 81 years. We used geographic information system-based spatiotemporal smoothing models to estimate recent (1 month) and long-term (7-14 years) exposures to PM2.5-10, and PM2.5 preceding baseline cognitive testing (1995-2001) of participants residing in the contiguous United States. We used generalized estimating equation regression to estimate differences in the rate of cognitive decline across levels of PM2.5-10 and PM2.5 exposures. The main outcome measure was cognition, via validated telephone assessments, administered 3 times at approximately 2-year intervals, includ-ing tests of general cognition, verbal memory, category fluency, working memory, and attention.

Results Higher levels of long-term exposure to both PM2.5-10 and PM2.5 were associated with significantly faster cognitive decline. Two-year decline on a global score was 0.020 (95% CI, -0.032 to -0.008) standard units worse per 10 μg/m3 increment in PM2.5-10 exposure and 0.018 (95% CI, -0.035 to -0.002) units worse per 10 μg/m3 increment in PM2.5 exposure. These differences in cognitive trajectory were similar to those between women in our cohort who were approximately 2 years apart in age, indicating that the effect of a 10-μg/m3 increment in long-term PM exposure is cognitively equivalent to aging by approximately 2 years.

Conclusion Long-term exposure to PM2.5-10 and PM2.5 at levels typically experienced by many individuals in the United States is associated with significantly worse cognitive decline in older women.

Introduction

Despite the tremendous public health importance of cognitive decline and dementia in older age1-8 and much effort to develop effective preventive and treatment regimes, few modifiable risk factors have been identified.9 One model has forecasted that a broadly applied intervention that delays the onset of Alzheimer disease (AD) by 2 years could reduce the number of prevalent cases in the United States by approximately 2 million over a 40-year interval.7

Exposures to environmental toxins are potential risk factors that can be modified. Among the most pervasive environmental toxins is particulate air pollution. Extensive toxicologic and epidemiologic research has documented the relation of exposure to ambient particles with mortality and adverse respiratory and cardiovascular outcomes.10-11 Regulatory actions have reduced ambient particulate matter (PM), resulting in decreased mortality.12-13 However, reductions have not occurred uniformly,14 and health effects remain associated with PM, even at current levels.15-16

Very little is known about the role of PM exposure in relation to cognitive decline. Evidence supporting such a relation could implicate exposure reduction as a potential means for reducing the public health burden of cognitive impairment. Yet existing studies in humans are rare,17-22 few have used measures that account for the exposures' complex spatial and temporal patterns, and none has evaluated the cognitive effects of exposure to fine particulate air pollution (<2.5 μm in diameter [PM2.5]). More notably, to our knowledge, no study has evaluated air pollution exposures in relation to longitudinal change in cognition. Therefore, using an established longitudinal study of older women living throughout the contiguous United States, we explored the hypothesis, specified a priori, that higher levels of exposure to PM would correspond to faster subsequent rates of decline in cognitive function.

Methods

The Nurses' Health Study (NHS) began in 1976 when 121 700 female registered nurses, aged 30 to 55 years and living in 11 US states, returned a mailed questionnaire about their medical history and health-related behaviors.23 Since then, women have completed questionnaires every 2 years. To date, we have maintained follow-up of more than 90% of the original participants. This study was approved by the institutional review board of Brigham and Women's Hospital, Boston, Massachusetts.

STUDY POPULATION

From 1995 to 2001, we invited participants 70 years and older with no history of stroke to participate in a study of cognition. Of the 22 715 women who were eligible, we were unable to contact 1031 (4.5%). Of those remaining, 7.7% declined participation. Our analyses of exposure to coarse PM (2.5-10 μm in diameter [PM2.5-10]) and PM2.5 in relation to cognitive decline were based on data from up to 19 409 women with relevant data. Second (1997-2004) and third (2002-2008) cognitive assessments were administered a mean (SD) of 1.9 (0.4) years (n = 17 089) and 4.3 (0.8) years (n = 14204) after initial testing, reflecting at least 83% participation at each follow-up cycle.

EXPOSURE TO COARSE AND FINE PM

We used geographic information system (GIS)-based spatiotemporal smoothing models to estimate exposures to PM10 (<10 μm in diameter) and PM2.5 for women residing in the contiguous United States. Coarse PM (PM2.5-10) was the difference between PM10 and PM2.5. The methods for estimating these exposures for a 13-state region have been described previously.24-26 These methods have been extended to estimate PM10 and PM2.5 for the contiguous United States. Briefly, PM10 and PM2.5 monitor data were obtained from the US Environmental Protection Agency's (USEPA) Air Quality System (AQS).26-28 Monitor data on PM10 were available nationwide from 1988 through 2007. Monitor data on PM2.5 were not widely available before 1999. Thus, separate PM2.5 models were developed for the pre-1999 and post-1999 periods, as in previous work.26 The pre-1999 PM2.5 model described seasonal spatial and monthly temporal patterns in the PM2.5 to PM10 ratio; we multiplied this ratio by PM10 to obtain PM2.5 predictions during this earlier period. Generalized additive mixed models were constructed to explain variation in measured PM10 and PM2.5 (post-1999) levels as the sum of effects of GIS-derived covariates (eg, distance to nearest road by road class, urban land use), meteorological data, and smooth spatial terms. These models were used with GIS-derived and meteorological data specific to each geocoded residential location for each nurse, to provide highly spatially resolved estimates of monthly PM10 and PM2.5 concentrations.

We averaged month-specific exposures to PM2.5-10, PM2.5, and PM10 over several intervals preceding the initial cognitive interview: preceding month, year, 2 years, 5 years, and from 1988 through the preceding month. (See the eFigure and eAppendix 1 for further detail on PM exposure models and exposure estimation, and the timing of exposure and cognitive assessments.)

COGNITIVE ASSESSMENT

Cognitive testing was administered using validated telephone interviews. In the initial interviewing, we administered only the Telephone Interview for Cognitive Status (TICS)29 and gradually added 5 more tests as high participation in the cognitive testing became apparent. Thus, the sample size differs somewhat across the cognitive tests, although participation rates remained identical for all tests. The TICS (n = 19 409) is modeled on the Mini-Mental State Examination (MMSE), and scores on the 2 tests are strongly correlated (Pearson correlation, 0.94).29 A test of delayed recall of the 10-word list from the TICS (N = 16 908) was one of the 5 tests added to our battery. We also added the East Boston Memory Test (EBMT)30-31 to assess immediate (n = 18 662) and delayed ( = 18 635) paragraph recall. We administered a test of category fluency in which participants were asked to name as many animals as they could in 1 minute32 (n = 18 652). Finally, participants were administered the Digit Span Backward test33 (n = 16 916), measuring working memory and attention. We used the full testing battery in the second and third assessment waves.

Our 2 prespecified primary outcomes were composite measures of cognition.5, 34 Specifically, to summarize the overall association of the air pollution exposure measures with cognitive performance, for women given all 6 tests (n = 16 887), we constructed a global score by averaging z scores from all tests. In addition, to assess overall verbal memory, a strong predictor of developing AD,35 we combined the immediate and delayed recalls of the EBMT and the TICS 10-word list, for women given all 4 tests (n = 16 906), by averaging z scores from these tests. We extensively tested the reliability and validity of our telephone procedure for assessing cognition in high functioning, educated women (eAppendix 2).

STATISTICAL ANALYSES

We performed separate analyses for each of the PM measures, evaluating exposures in quintiles and as continuous variables, in relation to each cognitive score, including the verbal and global scores. All individual test scores were expressed as z scores, computed from the means and standard deviations in our study population. We compared trajectories in cognitive function over the 3 repeated measures across levels of the exposure measures, using generalized estimating equations regression models,36 which allowed us to account for the correlations among repeated cognitive scores. In these models, we included terms for time, in years, since baseline cognitive assessment (as a continuous variable), air pollution exposure, and cross-products between the time and air pollution exposure terms. We adjusted these analyses for potential confounding variables, including age at cognitive assessment, education (registered nurse degree, bachelor's degree, or advanced graduate degree), husband's education (high school diploma or less, college degree, advanced graduate degree, or other), energy expended on recreational physical activity37 (mean of responses to 4-7 questionnaires from 1986 through initial cognitive assessment, in quartiles), and alcohol consumption (mean of responses to 5-8 questionnaires from 1986 through initial cognitive assessment; none, up to 1 drink/wk, 2-6 drinks/wk, or 1 drink/d). We also included terms for the cross-products between each covariate and time. Additional adjustment for body mass index, diabetes, smoking (status and pack-years), aspirin use (3 frequency categories), and ibuprofen use (ever/never), did not change our findings. We conducted tests for linear trend across the PM quintiles using an ordinal variable that took on values corresponding to each quintile (1, 2, 3, 4, or 5).

All associations are reported as mean differences in cognitive score change over a 2-year interval, across exposure levels, as 2 years is the approximate interval between the testing cycles. In addition, to help interpret these mean differences, we compared findings on the relation of PM exposure to cognitive decline with age-related differences in cognitive decline, generated from the women in our data set. While our primary focus was on PM2.5-10 and PM2.5, we also evaluated PM10.

In secondary analyses, we further adjusted our analyses for 3 measures of socioeconomic position in the census tract of residence: percentage of adults who have less than high school education, median home value, and median income. We also evaluated potential mediation of air pollution's association with cognitive decline by respiratory and cardiovascular conditions. In additional analyses, we further adjusted for self-reported emphysema and indicators of cardiovascular and cerebrovascular disease (high blood pressure, coronary heart disease, congestive heart failure, coronary artery bypass graft, transient ischemic attack, and carotid endarterectomy). Finally, we conducted sensitivity analyses restricted to women who did not move between 1988 and their first cognitive assessment (62% of the study population).

Results

Estimated exposures to PM2.5-10 and PM2.5 varied widely among the women (Table 1). Estimated exposures over the month preceding the initial cognitive assessment were significantly correlated with longer-term exposures, but these correlations weakened with increasing measurement interval length (Table 1). For any given interval, estimated exposure to PM2.5-10 was significantly correlated with estimated exposure to PM2.5 but at magnitudes lower than the correlations between measures of the same PM type.

EXPOSURE TO COARSE PM (PM2.5-10)

There were few meaningful differences in characteristics of women across quintiles of long-term PM2.5-10 exposure (Table 2). From our multivariable-adjusted analyses, we observed rates of change in global cognitive function score that were significantly worse with higher levels of long-term exposure to PM2.5-10 (P value for trend, .01; Table 3) and were significantly worse in the highest vs the lowest quintile of exposure (P = .003). Higher estimated PM2.5-10 exposures in the 1, 2, and 5 years before the initial cognitive assessment were also associated with significantly worse subsequent decline on the global cognitive score. By contrast, exposure to PM2.5-10 in the previous month was weakly and not significantly associated with cognitive decline. This pattern also was apparent in the findings for decline in the TICS and verbal memory scores, while short- and long-term PM2.5-10 exposures were associated with comparable increases of rates of decline in digit span backward and verbal fluency scores.

EXPOSURE TO FINE PM (PM2.5)

The distributions of key characteristics across quintiles of estimated long-term PM2.5 exposure were similar to those for PM2.5-10 (Table 4), with few notable or consistent differences across quintiles. Similar to PM2.5-10, women in the highest quintile of long-term exposure to PM2.5 experienced significantly worse rates of change in the global score than did women in the lowest quintile (P = .03; Table 5). The trend of across quintiles were borderline significant (P value for trend, .11), but, when modeled as continuous variables, higher levels of both long-term PM2.5 exposure (since 1988) and PM2.5 exposure in the 5 years before the initial cognitive assessment were associated with significantly worse decline in global cognition. Decline in the individual cognitive domains generally was more strongly predicted by long-term than recent exposure to PM2.5.

We observed similar differences in rates of global cognitive change per 10 μg/m3 increment in long-term exposure to PM2.5-10 and PM2.5 (-0.020 [95% CI, -0.032 to -0.008] and -0.018 [-0.035 to -0.002] standard units/2 years, respectively). These differences were similar to the difference in rates of change we observed between women in our data who were 1 to 2 years apart in age. Expressed per SD increment of each PM measure, these differences were -0.008 (95% CI, -0.013 to -0.003) and -0.006 (95% CI, -0.011 to -0.001) standard units/2 years.

Results from analyses of thoracic PM (PM10) indicated generally faster rates of cognitive decline with higher level of long-term exposure (P value for trend, .<.001; eTable).

SECONDARY ANALYSES

The associations of PM2.5-10 and PM2.5 with cognitive decline remained nearly identical when we adjusted our analyses for area socioeconomic position measures and for potential respiratory and cardiovascular intermediates. Analyses restricted to women who did not move yielded modestly stronger associations than those in our primary analyses. For example, 10-μg/m3 increments in long-term exposure to PM2.5-10 and PM2.5 corresponded to 2-year rates of decline in the global cognitive score that were worse by 0.025 (95% CI, -0.040 to -0.009) and 0.021 (95% CI, -0.043 to -0.000) standard units, respectively.

Comment

In this large, prospective study of older women, higher levels of long-term exposure to both PM2.5-10 and PM2.5 were associated with significantly faster cognitive decline. Placing these results in context, the differences in cognitive trajectory per 10-μg/m3 increment in long-term exposure to PM2.5-10 and PM2.5 were similar to the differences in trajectories between women in our study who were 1 to 2 years apart in age; that is, 10-μg/m3 higher exposure to PM was cognitively equivalent to aging by up to 2 years.

Several lines of indirect evidence indicate that PM may cause cognitive decline. Results from animal studies indicate that PM may access the brain either via circulation, or intranasally by direct translocation through the olfactory bulb.38-40 Once in the central nervous system, fine particles appear to exert adverse effects. Several animal studies have shown increased brain inflammation in response to air particulate exposures.41-44 In one experiment, mice were exposed either to filtered air, ambient ultrafine particles, or a mixture of fine and ultrafine particles sampled from Los Angeles, California, air. Two weeks after exposure, the brains of mice in both exposed groups contained higher levels of inflammatory markers, as compared with the mice in the control group.41 In dogs, signs of blood-brain barrier dysfunction, neural degeneration, cerebrovascular pathologic signs, and apoptosis in glial cells were present more often in those who had lived in Mexico City, Mexico, an area of high air pollution, than in dogs from less polluted cities.44 In a postmortem study of 19 humans aged 34 to 83 years, who had died of nonneurologic causes, brain levels of cyclooxygenase-2, an inflammatory mediator, in the frontal cortex and hippocampus were higher among those who had lived in highly polluted cities than among those who had lived in less polluted cities. Importantly, brain levels of amyloid-ß42, a pathologic hallmark of AD, were also higher among residents of the polluted cities.45

The relation of PM exposure to cognitive decline may also be mediated through cardiovascular mechanisms. Extensive experimental and epidemiologic data indicate an association between exposure to air pollution and cardiovascular diseases and risk factors.10-11,46-47 This link is important because vascular factors have also been found to predict cognitive decline and dementia.48-49 In our data, however, adjustment for vascular factors did not change our findings, indicating that this is not likely a key pathway by which PM influences cognition.

Several limitations of our study warrant consideration. First, our estimates of PM exposure were indirect, based on spatiotemporal modeling of measurements from air pollution monitors located near each woman's residence. Measurement via personal air monitoring devices is not practical for long-term exposures in large-scale epidemiologic studies. Yet, exposure measurement errors in our study were likely to be nondifferential with respect to degree of cognitive decline, resulting in attenuated estimates of association. In addition, our PM exposure estimation50-51 features GIS-based spatiotemporal statistical models with little bias and high precision-particularly relative to other modeling approaches24, 26-accounting for small-scale variations in exposure at each participant's residential address using GIS-based covariates. This enabled us to assign estimated PM exposure levels to each address for each participant throughout the study period. Therefore, exposure estimates should be more accurate over time than estimates from initial addresses only. If chronic PM exposure particularly affects cognitive aging or if the biologic response occurs over longer than 1 month, this improved accuracy over time may explain, in part, why many associations corresponding to recent PM exposure were weaker than associations corresponding to long-term PM exposures, although it is also plausible that recent PM exposure is less biologically relevant.

It is possible that our results from this observational study are due to confounding. However, we did not find meaningful differences in numerous potential confounding variables across levels of PM exposure, and adjustment for a variety of known confounding variables-some of them measured repeatedly over several study cycles-did not eliminate the observed associations.

Although ours is the first study, to our knowledge, to investigate PM2.5-10 and PM2.5 in relation to cognitive aging, previous epidemiologic studies of adults generally suggest an adverse association between exposure to other forms of ambient particulates and cognition.19-22 In a study of 399 older women residing in urban and rural areas of Germany, residential proximity to busy road, a source of exposure to ultrafine particles, was associated with performance on several tests of cognition and olfaction, but higher PM10 exposure in the previous 5 years was not.20 Another study of 671 older men measured exposure to black carbon, a marker of traffic-related particles, and observed that higher level of exposure over the previous 1 to 11 years was associated with worse cognitive function.22 In the largest study to date, among 15 973 older adults in China, residents of areas with poorer air quality over the previous 7 to 10 years, measured by an index of ambient particulate and gas concentrations, were more likely to have poor cognitive function.21 Finally, in a study of 1764 adults aged 20 to 59 years living throughout the contiguous United States, higher exposure to ozone over the previous year was associated with worse performance on several cognitive and motor tests, but exposure to PM10 was not. Neither of the 2 studies that examined PM10 observed an association with cognitive function, yet the range of PM10 exposure in the German study may have been too narrow (eg, 39.3-53.6 μg/m3 from 1980-1993) to observe a measureable effect,20 and the 1-year measurement interval for PM10 exposure used in the study of younger adults may have been too brief.19 These previous findings also suggest that traffic-related exposures may be important contributors to cognitive aging. Our findings complement and extend these previous findings not only by directly examining cognitive decline in a large population, but also by using detailed modeling of short- and long-term PM2.5-10 and PM2.5 exposures.

In conclusion, we found that higher levels of exposure to ambient PM are associated with worse cognitive decline. Importantly, these associations were present at levels of PM exposure typical in many areas of the United States. Therefore, if our findings are confirmed in other research, air pollution reduction is a potential means for reducing the future population burden of age-related cognitive decline, and eventually, dementia.

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Ambient Air Pollution and the Risk of Acute Ischemic Stroke

Gregory A. Wellenius, ScD; Mary R. Burger, MD; Brent A. Coull, PhD; Joel Schwartz, PhD; Helen H. Suh, ScD; Petros Koutrakis, PhD; Gottfried Schlaug, MD, MPH; Diane R. Gold, MD, MPH; Murray A. Mittleman, MD, DrPH

Arch Intern Med. 2012

Background The link between daily changes in level of ambient fine particulate matter (PM) air pollution (PM <2.5 μm in diameter [PM2.5]) and cardiovascular morbidity and mortality is well established. Whether PM2.5 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 PM2.5 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 PM2.5 levels in the hours and days preceding each event. We examined whether the association with PM2.5 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 (PM2.5 15-40 μg/m3) by the US Environmental Protection Agency's (EPA) Air Quality Index compared with a 24-hour period classified as good (15 μg/m3). Considering PM2.5 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 PM2.5 levels (6.4 μg/m3). The increase in risk was greatest within 12 to 14 hours of exposure to PM2.5 and was most strongly associated with markers of traffic-related pollution.

Conclusion These results suggest that exposure to PM2.5 levels considered generally safe by the US EPA increase the risk of ischemic stroke onset within hours of exposure.

Introduction

Daily changes in levels of ambient fine particulate matter (PM) air pollution (PM <2.5 μm in diameter [PM2.5]) have been associated with higher risk of acute cardiovascular events, excess hospitalizations, and deaths.1 These cardiovascular effects of PM2.5 appear to be mediated through a combination of autonomic, hemostatic, inflammatory, and vascular endothelial disturbances with consequent changes in cardiac and vascular function.2-7 Relying on the current evidence, the US Environmental Protection Agency (EPA) regulates mean daily and annual PM2.5 levels. Whether the current regulatory standards are sufficient to protect public health remains controversial.8

Although a number of studies have examined the association between other air pollutants and the risk of stroke,9-12 fewer studies have evaluated the effects of PM2.5 on stroke risk, and the results remain equivocal. Specifically, some,13-15 but not all,16-18 studies suggest that PM2.5 exposure may increase the incidence of the combined end point of acute cerebrovascular diseases, an etiologically diverse group with multiple underlying pathophysiologic mechanisms. Prior work has suggested that ambient air pollution is more strongly associated with ischemic stroke than intracranial hemorrhage.19 However, few studies have specifically evaluated the link between PM2.5 exposure and ischemic stroke risk,14, 20-22 and only 1 of these studies assessed whether the associations differ by presumed ischemic stroke cause.22

We therefore evaluated the association between daily and hourly changes in PM2.5 levels and the risk of ischemic stroke onset among patients residing in the greater Boston area and admitted between 1999 and 2008 to the Beth Israel Deaconess Medical Center (BIDMC). During the study period, PM2.5 levels in the Boston area did not exceed current EPA standards.

Methods

This study was approved by the committee on clinical investigations at BIDMC. We identified 1763 consecutive patients 21 years or older admitted to the BIDMC between April 1, 1999, and October 31, 2008, with neurologist-confirmed ischemic stroke, excluding patients with in-hospital strokes or transient ischemic attacks. The BIDMC is a 650-bed teaching hospital of Harvard Medical School and designated as a primary stroke service hospital by the state. The stroke service consists of 5 vascular neurologists who see about 550 patients with stroke annually. As in previous studies,23 we excluded patients residing farther than 40 km from the Harvard ambient monitoring station to reduce exposure misclassification. We identified patients potentially eligible for this study by reviewing daily emergency department admission logs, stroke service admission logs, stroke service consult logs, and hospital electronic discharge records. For patients meeting eligibility criteria, we abstracted data on demographics, presenting symptoms, medical history (including history of stroke), and imaging results from each patient's medical record. We classified presumed stroke pathophysiologic mechanisms as (1) large-artery atherosclerosis, (2) small-vessel occlusion, (3) cardioembolism, (4) other determined cause or (5) undetermined cause, using the approach developed for the Trial of ORG 10172 in Acute Stroke Treatment (TOAST).24 Time of stroke symptom onset or time last seen normal as documented by the attending stroke neurologist at the time of hospital presentation was classified as exact, estimated, or unknown.22 Given the documented morning peak in ischemic stroke incidence,25 we assumed that stroke onset occurred at 9:00 AM for 221 patients for whom the date of stroke symptom onset was documented but not the time (13%). We excluded 58 patients for whom neither the date nor the time of stroke onset was documented (3%), leaving 1705 patients available for analysis.

The concentrations of PM2.5 and black carbon were measured continuously, and levels of sulfate particles (SO42-) were measured daily (9:00 AM-9:00 AM) at the Harvard ambient monitoring station, as previously described.23 Hourly measures of nitrogen dioxide (NO2), carbon monoxide (CO), and ozone (O3) were obtained from local monitoring sites operated by the Massachusetts Department of Environmental Protection and averaged. We obtained hourly meteorologic data from the National Weather Service station at Boston's Logan Airport and calculated apparent temperature, an index of thermal comfort, as previously described.26 In a secondary analysis, we estimated exposure to black carbon at each subject's home as a marker of traffic pollution using a validated temporal-spatial model.27 Black carbon predictions are based on over 6000 black carbon measurements at 82 locations in the greater Boston area, meteorologic and other characteristics of a given day, and measures of land use (eg, traffic and population density) at a given location.

We used the time-stratified case-crossover study design28 to assess the association between the risk of ischemic stroke onset and PM2.5 concentrations in the hours and days preceding each event. In this design, each subject's exposure prior to a case-defining event (case period) is compared with his or her own exposure experience during 1 or more control periods when the subject did not become a case (control period). Control periods were chosen such that exposures during the case period were compared with exposures occurring on other days of the same month falling on the same day of the week and time of day as the case period. The use of control periods from both before and after the index event is appropriate in this setting because individual events do not affect the distribution of future exposure in the overall study population.29 This approach effectively controls for seasonality, time trends, and chronic and slowly varying potential confounders because the exposure information for cases and controls within the same stratum come from the same calendar month.30

We performed conditional logistic regression, stratifying on each hospitalization, to obtain estimates of odds ratios (ORs) associated with PM2.5 exposure and corresponding 95% CIs. In all analyses, we controlled for ambient temperature and dew point temperature using natural cubic splines (3 degrees of freedom each) and barometric pressure modeled as a linear continuous variable. We first considered 2 categories of PM2.5 levels defined a priori by the EPA's Air Quality Index31 as either good (15 μg/m3) or moderate (15-40 μg/m3), excluding 11 days where PM2.5 levels exceeded 40 μg/m3 (0.3%). Next we considered 5 a priori categories of PM2.5 levels (break points at 5, 10, 15, and 20 μg/m3). Finally, we considered PM2.5 exposure as a continuous variable.

In all analyses, PM2.5 exposure was assessed relative to the time of stroke symptom onset. We separately evaluated the association between the risk of ischemic stroke onset and PM2.5 levels averaged at 4 different periods prior to stroke symptom onset (0 to <24 hours, 24 to <48 hours, 48 to <72 hours, and 72 to <96 hours). Results were subsequently confirmed using unconstrained distributed lag models such that pollutant levels at each time point were considered jointly in a single model. To explore associations with shorter exposures in more detail, we additionally evaluated the association between risk of stroke onset and PM2.5 levels averaged in 2-hour increments prior to stroke symptom onset (0 to <2 hours through 36 to <38 hours).

We repeated these analyses for black carbon, NO2, CO, O3, and SO42-.

We evaluated whether the associations with PM2.5 concentrations differed by presumed ischemic stroke cause or according to the presence of major stroke risk factors including diabetes mellitus, atrial fibrillation, hypertension, and history of stroke or transient ischemic attack using fully stratified models. We used the 2 test for homogeneity32 to evaluate whether associations differed significantly across subgroups. A 2-sided P < .05 was considered statistically significant. Analyses were performed using SAS version 9.2 (SAS Institute Inc) and the R statistical package, version 2.8.1.

Results

The 1705 patients were predominantly white women, mean (SD) age 73.1 (14.5) years (Table 1). Small-vessel strokes were the most common determined cause of stroke (26%), followed by strokes due to cardioembolism (25%) and large-artery atherosclerosis (20%). The median delay time from stroke symptom onset to hospital presentation was 10 hours (25th percentile, 3 hours; 75th percentile, 26 hours). In-hospital mortality was 5.8%. Most patients resided less than 20 km from the Harvard ambient monitoring site in Boston (97%) (eTable 1).

For 2888 days during the study period (83% of study days), the air quality was classified as good, according to the EPA's Air Quality Index for PM2.5 ("air quality is satisfactory and poses little or no risk"33(p3)); for 572 days (16% of study days), it was classified as moderate ("air quality is acceptable; however, there may be a moderate health concern for a very small number of people"33(p3)).

The OR of ischemic stroke onset was 1.34 (95% CI, 1.13-1.58) (P < .001) following a 24-hour period during which the air quality was moderate compared with a period during which it was good. The association between PM2.5 level and risk of ischemic stroke onset was approximately linear (Figure 1). Considering PM2.5 concentration as a continuous variable, the OR of stroke onset was 1.11 (95% CI, 1.03-1.20) (P = .006) comparing the 75th to the 25th percentile of PM2.5 levels (6.4 μg/m3) over the previous 24 hours. The PM2.5 levels preceding stroke onset by more than 24 hours were not associated with higher risk.

The results were not materially different when we excluded from analysis patients living more than 20 km from the monitoring site, those presenting more than 48 hours after symptom onset, or those patients for whom time of symptom onset was not documented. Results also did not differ materially when we adjusted for apparent temperature or ozone levels (eTable 2). The results from an unconstrained distributed lag model were also similar.

Figure 2 shows that the OR of stroke onset was elevated immediately, peaked in association with mean PM2.5 levels 12 to 14 hours earlier (OR comparing the 75th to 25th percentile of PM2.5, 1.10 [95% CI, 1.04-1.17] [P = .001]), and decreased thereafter.

We considered the association between the risk of stroke onset and other pollutants (Table 2). Results for black carbon concentrations (either measured at the Harvard ambient monitoring site or estimated at each patient's home address) and NO2 levels were similar to those for PM2.5 levels, while results for CO, O3, and SO42- concentrations were not statistically significant.

We examined whether the association between PM2.5 levels and stroke onset varied across subgroups of patients with specific clinical characteristics (Table 3). Fine particulate matter air pollution levels were associated with stroke onset among patients with ischemic stroke classified as due to large-artery atherosclerosis and small-vessel disease but not cardioembolism. There was no evidence suggesting that the association varied according to the presence of comorbid diabetes mellitus, atrial fibrillation or hypertension, history of stroke or transient ischemic attack, or age.

Comment

In this Boston area study conducted while the air quality in the region was in attainment of EPA regulatory standards, we found that ischemic stroke risk was 34% higher (95% CI, 13%-58%) (P < .001) on days with moderate PM2.5 levels compared with days with good levels, according to the EPA's Air Quality Index.31 The relationship between higher PM2.5 levels and increased risk of stroke onset was linear, strongest within 12 hours of PM2.5 exposure, and observed among patients presenting with strokes classified as due to large-artery atherosclerosis or small-vessel occlusion but not cardioembolism. Stroke risk was more strongly associated with concentrations of black carbon and NO2, markers of traffic pollution, than with components linked to nontraffic sources.

From a public health perspective, we observed an association between PM2.5 levels and ischemic stroke onset in an area in attainment of the US National Ambient Air Quality Standards.33 Although the observed relative risk is modest, the number of strokes attributable to PM2.5 may be high given the high incidence of ischemic stroke and the fact that nearly everyone is exposed to ambient fine particulate matter. If the association observed in this study is causal, and if a linear dose-response function is assumed, a 2 μg/m3 reduction in mean PM2.5 levels (approximately 20%) during this time period might have averted approximately 6100 of the 184 000 stroke hospitalizations observed in the US Northeast region in 2007 alone.34

An analysis of Medicare beneficiaries in 204 US counties found a 0.4% (95% CI, 0.0%-0.9%) higher risk of admission for the combined end point of cerebrovascular disease per 10-μg/m3 increase in same-day PM2.5 levels.13 Smaller studies in Taiwan14 and Southern California15 have reported excess relative risks of approximately 2% per 10-μg/m3 increase in PM2.5 levels, while others have found no evidence of an association.16-18 Of 4 prior studies that have specifically evaluated the association between PM2.5 concentrations and the risk of ischemic stroke, 2 Canadian studies found no association,20, 22 while studies from Taiwan14 and Nueces County, Texas,21 found a 3% (95% CI, -1% to 7%) and 6% (95% CI, -1% to 13%) excess risk per 10-μg/m3 increase in PM2.5 levels, respectively.

The estimate from the current study scaled to a 10-μg/m3 increase in PM2.5 levels would be 18% (95% CI, 5%-34%), substantially larger than that of previous reports. We believe that this difference is attributable, at least in part, to the use in the current study of data on the timing of ischemic stroke onset. Most prior studies have assessed exposure to PM2.5 based on the calendar day of hospital admission, an exposure assessment strategy that can bias health effects estimates toward the null by as much as 60%.35 Our group's estimates in a previous study in a quality of care registry in Ontario, Canada,22 may have been biased toward the null partly by misclassification of stroke onset time for patients presenting later than the limited time when they might have benefited from thrombolytic therapy. Differences in outcome assessment methods, population and pollutant characteristics, and other aspects of the exposure assessment strategy very likely also contribute to heterogeneity across studies. For example, health effects of PM2.5 concentrations in North America are known to vary geographically depending on the local pollutant sources and components36 as well as community characteristics.37

In the current study we were able to estimate the time course of the association between PM2.5 levels and stroke onset in greater detail than has been previously possible. We observed an immediate increase in the OR for stroke onset that peaked 12 hours after PM2.5 exposure and decreased thereafter (Figure 2). Experimental studies in humans and animals have shown that exposure to concentrated ambient PM2.5 can induce increases in blood pressure and heart rate and reductions in heart rate variability within this time frame,7, 38 suggesting that altered hemodynamics could play an important role. Other potential mechanisms include alterations in hemostatic factors, systemic inflammation, endothelial cell injury, and vascular dysfunction.4-6 Although these physiologic intermediate factors have typically been investigated in association with PM2.5 exposures lasting a day or longer, there is some evidence suggesting that these effects may also follow exposures shorter than 24 hours.7, 39-41

The observation that PM2.5 exposure was more strongly associated with stroke onset in patients with strokes due to large-artery atherosclerosis is consistent with a mechanism involving altered hemodynamics and/or vascular dysfunction that results in disruption of a vulnerable atherosclerotic plaque with subsequent thrombosis and/or downstream embolism, as well as with results from a prior study.22 This result is also consistent with a Boston area study showing a higher risk of acute myocardial infarction within 2 hours of exposure to elevated levels of PM2.5.42 The mechanisms underlying the observed association between PM2.5 exposure and small-vessel stroke are less clear because the pathologic characteristics of these strokes remains poorly understood. However, evidence suggests that endothelial dysfunction and injury, potentially triggered by exposure to PM2.5 or its components, may contribute to the distinct nonatherosclerotic arteriopathy that likely underlies many small-vessel strokes.43 We did not find evidence to suggest that the presence of comorbid diabetes, hypertension, atrial fibrillation, or a history of stroke increased patients' vulnerability to PM2.5-related stroke.

Identifying the components or sources of PM2.5 responsible for the observed associations is of public health and regulatory interest. We found that the risk of stroke onset was most strongly associated with PM2.5 exposure, but also significantly associated with exposure to black carbon and NO2, markers of traffic pollution. This finding is in agreement with past studies suggesting that traffic pollution may trigger ischemic strokes.20, 44-45 We did not find any association between risk of stroke onset and ozone levels, a secondary pollutant formed from the reaction of oxides of nitrogen and volatile organic compounds in the presence of sunlight. This is in agreement with most,14, 16-17,20 but not all,46 prior studies. We also did not find any association between risk of stroke onset and levels of SO42-, consistent with prior studies using administrative data.16, 47 In the Northeast, SO42- generally represents regional pollution from coal-fired power plants.48

Our study has some limitations. First, the use of air quality measures from a single monitoring site is expected to lead to exposure misclassification, increasing the width of our CIs but not otherwise biasing our results.49 However, PM2.5 levels measured at this monitoring site have been shown to be strong proxies for personal exposure to particles of ambient origin in communities surrounding Boston.50 In support of this, our results were not materially different when we restricted the analyses to patients living less than 20 km from the monitoring site, and the results were similar when we evaluated the association between black carbon estimated at patients' homes and ischemic stroke onset. Second, we did not study the association between PM2.5 exposure and stroke resulting in death prior to coming to medical attention. Third, in 13% of patients, we were able to estimate the day but not the time of stroke symptom onset, likely resulting in some exposure misclassification and biasing our results toward the null hypothesis of no association. Consistent with this notion, the association between PM2.5 exposure and ischemic stroke was more pronounced after exclusion of these patients from analysis. Fourth, this study involved patients from a single tertiary care center in Boston. Since the effects of PM2.5 exposure likely vary depending on population characteristics, pollution sources, and particle constituents, our results are not necessarily generalizable to other populations or geographic locations.

As in previous studies, important strengths of this study include detailed data on the time of stroke symptom onset22 and patient clinical characteristics.22, 45 In particular, our use of data on the time of stroke symptom onset provides novel insights into the mechanisms by which PM2.5 exposure may increase the risk of ischemic stroke onset.

In conclusion, these results suggest that PM2.5 exposure increases the risk of ischemic stroke at levels below those currently considered safe under US regulations. These associations can be observed within hours of exposure and are most strongly associated with pollution from local or transported traffic emissions. If pollution levels decline with regulation, data on timing of stroke onset, patient clinical characteristics, and stroke mechanisms will be essential for proper evaluation of the clinical benefits of pollution control on stroke risk.

 
 
 
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