Exposure to elevated levels of PM 2.5 was associated with smaller total cerebral brain volume, a marker of age-associated brain atrophy, and with higher odds of covert brain infarcts. These findings suggest that air pollution is associated with insidious effects on structural brain aging even in dementia- and stroke-free persons.

A 2-μg/m 3 increase in PM 2.5 was associated with −0.32% (95% confidence interval, −0.59 to −0.05) smaller total cerebral brain volume and 1.46 (95% confidence interval, 1.10 to 1.94) higher odds of covert brain infarcts. Living further away from a major roadway was associated with 0.10 (95% confidence interval, 0.01 to 0.19) greater log-transformed white matter hyperintensity volume for an interquartile range difference in distance, but no clear pattern of association was observed for extensive white matter.

Framingham Offspring Study participants who attended the seventh examination were at least 60 years old and free of dementia and stroke were included. We evaluated associations between exposures (fine particulate matter [PM 2.5 ] and residential proximity to major roadways) and measures of total cerebral brain volume, hippocampal volume, white matter hyperintensity volume (log-transformed and extensive white matter hyperintensity volume for age), and covert brain infarcts. Models were adjusted for age, clinical covariates, indicators of socioeconomic position, and temporal trends.

Long-term exposure to ambient air pollution is associated with cerebrovascular disease and cognitive impairment, but whether it is related to structural changes in the brain is not clear. We examined the associations between residential long-term exposure to ambient air pollution and markers of brain aging using magnetic resonance imaging.

Introduction

Long-term exposure to particulate air pollution has been associated with higher incidence of stroke1 and impaired cognitive function in older adults.2,3 Long-term exposures have also been associated with changes in cerebral hemodynamics,4 impaired microvascular reactivity,5 and greater carotid atherosclerotic burden.6 Air pollution has been hypothesized to affect the central nervous system through activation of systemic inflammatory pathways and vascular dysfunction.7 Particulate air pollution is a pervasive component of urban and suburban ambient air pollution. Animal models have shown that particles can translocate from the nose via the olfactory nerve into the brain, and evidence of these particles has been found in the striatum, frontal cortex, and cerebellum.8 However, it is not known whether long-term exposures to air pollution at urban background levels are related to measures of structural integrity and atrophy in the brains of older adults.

Magnetic resonance imaging (MRI) of the brain can detect early vascular impairment9 that is associated with subsequent risk of dementia and stroke.10 Therefore, we investigated the associations between exposure to fine particulate matter (PM 2.5 ) and residential proximity to major roadways with measures of total cerebral brain volume (TCBV), hippocampal volume (HV), white matter hyperintensity volume (WMHV), and covert brain infarcts (CBI) in the Framingham Offspring Study. We hypothesized that higher long-term exposure to ambient air pollution would be associated with subclinical damage as indicated by smaller TCBV and HV, larger WMHV, and higher odds of CBI.

Materials and Methods

Study Participants

The design of the Framingham Offspring Study has been detailed previously.10,11 Community-dwelling participants living in the New England Region with no history of dementia, stroke, or transient ischemic attack who attended the seventh examination (1998–2001) were aged ≥60 years at the time of MRI and were eligible for inclusion in this study (n=943). All participants provided written informed consent, and the Institutional Review Boards at Beth Israel Deaconess Medical Center and Boston Medical Center approved the protocol.

Exposure Assessment

PM 2.5 Satellite Data

Participant primary addresses at the seventh examination were geocoded using ArcGIS 10 (ESRI, Redlands, CA), and census tract median household income was assigned (US Census 2000). Beginning in the year 2000, Moderate Resolution Imaging Spectroradiometer satellite-derived Aerosol Optical Density measurements were used to predict daily PM 2.5 concentration across New England as previously described.12,13

Near Roadway Exposure

Residential proximity to the nearest A1, A2, or A3 roadway was determined by US Census Features Class in ArcGIS. We categorized proximity based on the following cut points: <50, 50 to <100, 100 to <200, 200 to <400, and 400 to <1000 m. We also evaluated the continuous association between the natural logarithm of proximity to a major roadway and neuroimaging outcomes because we have previously reported that this exposure and mortality were linearly associated.12 Participants living further than 1000 m from a major road in rural areas were excluded in primary analyses because the exposures of individuals living in exurb areas beyond 1000 m away from a major roadway are likely to be different from those of people living in urban and suburban areas.

Volumetric Brain MRI

TCBV, HV, and WMHV assessments and inter-rater reliability have been described previously.14–17 Total cranial volume was determined by manual delineation of the intracranial vault, and total brain parenchymal volume was determined by mathematical modeling. TCBV was then computed as a ratio of brain parenchymal volume:total cranial volume. The T2-weighted double spin-echo coronal sequences were acquired in 4-mm contiguous slices. Extensive WMHV (EXT-WMHV) was determined as a binary outcome by whether the log(WMHV/total cranial volume) was >1 SD above the age-adjusted mean in this cohort.10,18 The presence of CBI was determined manually on the basis of size (>3 mm), location, and characteristics of the lesions.19

Additional Covariates

History of cardiovascular disease was determined as previously described.20 Prevalent diabetes mellitus was defined as a fasting glucose ≥126 mg/dL or oral hypoglycemic or insulin use at an examination or any previous history of diabetes mellitus (excluding gestational diabetes). Smoking status (never, current, and former), pack-years smoked (<10 years, ≥10 years, and missing), education (no high school, high school, some college, bachelors or higher), and alcohol intake (0, 1–7 drinks/wk, and 7–14, ≥15) were self-reported. Fasting homocysteine was measured in plasma. Systolic and diastolic seated blood pressures were calculated as the mean of 2 measurements taken during the clinical examination.

Statistical Methods

Linear and logistic regression models were used to evaluate continuous outcomes (TCBV, HV, and WMHV) and dichotomous outcomes (EXT-WMHV and CBI), respectively. We first adjusted for age at MRI, [age at MRI]2, sex, time from examination 7 to MRI, median household income, date of MRI, smoking status, pack-years smoked, education, alcohol intake, and sine and cosine of MRI date to account for seasonal trends (model 1). We then added covariates thought to be potential confounders that could also be mediators of the associations between particulate air pollution and brain structure, including natural logarithm of homocysteine, systolic blood pressure, diabetes mellitus, cardiovascular disease, history of atrial fibrillation, hypertension medications, and obesity (body mass index ≥30 kg/m2) (model 2).

We tested whether observed associations differed by factors related to biological susceptibility and socioeconomic position as an evaluation of effect modification using cross-product terms for sex, diabetes mellitus, obesity, current and former smoking (versus never smoking), and median household income <25th percentile (≤$44 901).

In sensitivity analyses, we accounted for clustering by census tract to further control confounding by socioeconomic position using generalized estimating equations with exchangeable working correlation matrix. Nonlinearity was evaluated using restricted cubic splines with knots at the 5th, 27.5th, 50th, 72.5th, and 95th percentiles. We evaluated associations with PM 2.5 restricting to participants living within 1000 m of a major road. We also considered whether adjusting for CBI altered findings for associations between exposures of interest and TCBV.16

Models of PM 2.5 were scaled to 2 μg/m3, which approximates the interquartile range (1.7 μg/m3). We present the results of log-linear residential proximity to major roadway within 1000 m analyses for an interquartile range. All analyses were performed in SAS version 9.3 or STATA version 12. Plots were created using the POSTRCSPLINE package in Stata.21

Results

Table 1 shows population characteristics. The median (interquartile range) of PM 2.5 exposure was 11.1 (1.7) μg/m3. Participants lived a median distance (25th to 75th percentile) from a major road of 173 (48–415) m (Table 2). The Spearman rank correlation between the natural logarithm of residential distance from a major road and PM 2.5 was −0.15.

Table 1. Population Characteristics (n=943) Characteristic Median [IQR] or n (%) Age at MRI, y 68 [9] Systolic blood pressure, mm Hg 129 [25] Diastolic blood pressure, mm Hg 72 [13] Men 456 (48%) Prevalent cardiovascular disease 130 (14%) Smoking status Current 73 (8%) Former 532 (56%) Never 337 (36%) Missing 1 (<1%) Prevalent heart failure 46 (5%) Diabetes mellitus 134 (14%) Hypertension medication use 366 (39%) Homocysteine 8.3 [3.1] Education Less than high school 51 (5%) High school 311 (33%) Some college/associate degree 275 (29%) Bachelors or higher 298 (32%) Missing education 8 (<1%) Median household income 63,479 [29,270] Total cerebral brain volume 78.41 [4.39] Hippocampal volume 0.33 [0.07] Log white matter hyperintensity volume -2.69 [1.30] Extensive white matter hyperintensity 135 (14%) Covert brain infarcts 133 (14%)

Table 2. Exposure Characteristics Exposure Median [IQR] or n (%) Range PM 2.5 , μg/m3* 11.1 [1.7] 7.7—17.6 Distance to major road, m† 173 [367] 0–993 Distance by category, m <50 226 (24%) … 50 to <100 87 (9%) … 100 to<200 149 (16%) … 200 to<400 186 (20%) … 400 to<1000 226 (24%) … ≥1000 69 (7%) …

Higher PM 2.5 was associated with smaller TCBV and 1.46 times (95% confidence interval [CI], 1.10 to 1.94) higher odds of CBI (Tables 3 and 4). A 2-μg/m3 increase in PM 2.5 was associated with a 0.32 U difference in TCBV (95% CI, −0.59 to −0.05). There was no clear pattern of association between PM 2.5 and HV, WMHV, or EXT-WMHV.

Table 3. Associations Between Exposures and Continuous Volumetric Outcomes Outcome Exposure Model 1* Model 2† β 95% CI n β 95% CI n Hippocampal volume <50 0.004 (−0.005 to 0.014) 865 0.005 (−0.004 to 0.015) 853 50 to <100 0.003 (−0.011 to 0.016) … 0.003 (−0.010 to 0.017) … 100 to <200 0.005 (−0.006 to 0.016) … 0.005 (−0.006 to 0.016) … 200 to <400 0.003 (−0.007 to 0.013) … 0.003 (−0.007 to 0.013) … 400 to <1000 Ref … … Ref … … Log(distance)‡ −0.002 (−0.007 to 0.003) 865 −0.003 (−0.008 to 0.002) 853 PM 2.5 § 0.0001 (−0.005 to 0.005) 921 0.0004 (−0.005 to 0.005) 909 Log (white matter hyperintensities) <50 −0.17 (−0.35 to 0.01) 873 −0.16 (−0.34 to 0.02) 861 50 to <100 −0.13 (−0.37 to 0.11) … −0.12 (−0.36 to 0.11) … 100 to <200 −0.07 (−0.27 to 0.13) … −0.06 (−0.26 to 0.13) … 200 to <400 0.02 (−0.16 to 0.21) … 0.03 (−0.15 to 0.22) … 400 to <1000 Ref … … … Ref … Log(distance)‡ 0.10 (0.01 to 0.19) 873 0.09 (−0.0004 to 0.18) 861 PM 2.5 § −0.06 (−0.16 to 0.03) 929 −0.08 (−0.17 to 0.01) 917 Total cerebral brain volume <50 0.23 (−0.29 to 0.75) 873 0.09 (−0.42 to 0.60) 861 50 to <100 0.45 (−0.24 to 1.14) … 0.47 (−0.21 to 1.16) … 100 to <200 −0.02 (−0.60 to 0.56) … −0.14 (−0.71 to 0.43) … 200 to <400 −0.19 (−0.73 to 0.35) … −0.30 (−0.84 to 0.23) … 400 to <1000 Ref … … … Ref … Log(distance)‡ −0.15 (−0.41 to 0.11) 873 −0.10 (−0.36 to 0.16) 861 PM 2.5 § −0.32 (−0.59 to −0.05) 929 −0.26 (−0.53 to 0.004) 917

Table 4. Associations Between Exposures and Binary Outcome Outcome Exposure Model 1* Model 2† OR 95% CI n OR 95% CI n Extensive white matter hyperintensity volume for age <50 0.88 (0.51–1.52) 873 0.94 (0.53–1.67) 861 50 to <100 0.56 (0.25–1.29) … 0.59 (0.25–1.38) … 100 to <200 0.86 (0.46–1.60) … 0.96 (0.51–1.83) … 200 to <400 1.05 (0.60–1.84) … 1.16 (0.65–2.06) … 400 to <1000 Ref … … Ref … … Log(distance)‡ 1.11 (0.84–1.48) 873 1.09 (0.81–1.47) 861 PM 2.5 § 1.00 (0.76–1.32) 929 0.94 (0.70–1.26) 917 Covert brain infarcts <50 1.21 (0.67–2.17) 870 1.29 (0.70–2.36) 861 50 to <100 1.25 (0.58–2.67) … 1.16 (0.53–2.56) … 100 to <200 1.17 (0.61–2.23) … 1.10 (0.56–2.15) … 200 to <400 1.69 (0.95–3.00) … 1.72 (0.95–3.11) … 400 to <1000 Ref … … Ref … … Log(distance)‡ 1.05 (0.79–1.40) 870 1.02 (0.75–1.37) 861 PM 2.5 § 1.46 (1.10–1.94) 926 1.37 (1.02–1.85) 917

An interquartile range difference in residential proximity to a major road was associated with 0.10 (95% CI, 0.01 to 0.19) higher WMHV. A similar pattern was observed with categories of distance. However, there was no evidence of an association between proximity to a major road and EXT-WMHV, or was it associated with TCBV, HV, or CBI.

There was no evidence of effect modification for the observed associations by sex, diabetes mellitus diagnosis, obesity, smoking, or median income below the 25th percentile.

Only the association between PM 2.5 and TCBV met criteria for significant deviation from linearity, suggesting a stronger association at lower exposure levels and wide CIs at high levels (Figure I in the online-only Data Supplement). We found no material differences when we considered restricting PM 2.5 analyses to regions within 1000 m of a major road or clustering by socioeconomic position. Adjustment for covert brain injury did not alter the association between PM 2.5 and TCBV.

Discussion

In this study, we observed that an increase in PM 2.5 within the range of exposures observed at urban and suburban background levels in New England was associated with smaller −0.32 (95% CI, −0.59 to −0.05) TCBV and with 1.46 times (95% CI, 1.10 to 1.94) higher odds of CBI. These findings support the hypothesis that higher long-term exposures to ambient air pollution are associated with structural changes in the brain that could precede cognitive impairment and overt cerebrovascular damage.22–24

To our knowledge, there are no published studies of associations between air pollution and brain volume or CBI in older adults. Although CBI may appear asymptomatic, these small infarcts typically located in deep regions of the brain have been associated with neurological abnormalities, poorer cognitive function,25 onset of dementia,24 and are thought to reflect small-vessel disease.26 Smaller TCBV has been associated subsequent stroke among Framingham Offspring participants27 and also with poorer performance on tests of attention, executive, and visuospatial function.16 The magnitude of association that we observed for a 2-μg/m3 increase in PM 2.5 was similar to ≈1 year of brain aging computed as the ratio of the coefficients for PM 2.5 and age in the model. Adjustment for CBI did not alter this association, suggesting that atrophy was independent of the presence of asymptomatic injury and not merely a direct result of the presence of cerebral infarction.

The mechanisms through which air pollution may affect brain aging remain unclear, but systemic inflammation resulting from deposition of fine particles in alveoli is likely important. Upregulation of a proinflammatory state has been associated both with elevated risk of stroke7,28 and cognitive decline.29 Circulating levels of biomarkers indicative of systemic inflammation have been associated with lower brain volume.30

Our findings are largely consistent with previous studies showing that long-term exposure to ambient air pollution is associated with vascular impairment.4,5,12 Several previous studies have reported associations between long-term pollution exposure and living close to major roads with incident stroke1,31,32 and poorer cognitive function in older adults.2,3,33 Living in a high air pollution region in Mexico City was associated with greater accumulation of 42-amino acid form of β-amyloid in the frontal cortex and hippocampus than living in a nonpolluted area.34

Although evidence on the associations between long-term air pollution exposures and white matter damage is limited, an ecological study in Mexico reported associations between higher levels of air pollution and white matter damage in children and dogs.35 Our findings of a positive association between WMHV and living further from a major road but no association with EXT-WMHV were unexpected. However, among Framingham Offspring Study participants, EXT-WMHV was associated with poorer cognitive function18 and elevated risk of stroke10 but WMHV was not, suggesting a threshold for these associations. Different findings may have distinct underlying pathophysiologic mechanisms. To evaluate this, it will require additional studies in experimental models designed to address these questions.

There were some differences in associations we observed for PM 2.5 and residential proximity to a major roadway. Although both capture features of long-term exposure to ambient air pollution, proximity is an integrated measure of exposure to traffic, which includes vehicle emissions, noise, ultrafine particles, road dust, and gaseous pollutants such as nitrogen dioxide, carbon monoxide, and volatile organic compounds but does not specifically account for the intensity of traffic or meteorologic conditions at a given location. In contrast, modeled PM 2.5 incorporates both locally and regionally generated air pollution. Hence, they represent different aspects of ambient pollutant exposures.

Our study is not without limitations. Although we accounted for individual-level and area-level characteristics of socioeconomic position, there may be residual confounding. However, the results from our analysis taking spatial clustering into account were similar to our primary results, and previous literature using modeled PM 2.5 has also shown that correlations between socioeconomic position and PM 2.5 are low within urban areas.36 The Framingham Offspring population comprised mostly white participants. Therefore, these results may not be generalizable to other populations. Recent addresses were stable, with 91% of participants reporting the same address at the sixth and seventh examination cycles. Our PM 2.5 data are based on an average for the year 2001 similar to other large epidemiological studies.12,31 This approach limits the influence of secular trends in exposure, while capturing the spatial distribution of average PM 2.5. This study also has several strengths, including a relatively large, community-based sample, inclusion of both men and women, quantitative brain MRI, and individual-level estimates of exposures.

Conclusions

We observed evidence suggesting that long-term exposure to PM 2.5 is associated with lower TCBV and more CBI among a community-based sample of participants free of dementia and stroke. These findings suggest that relatively low urban background levels of particulate air pollution may contribute to the acceleration of atrophic changes and small-vessel disease in older adults. Additional studies will be necessary to confirm or refute these findings, extend the work to include longitudinal assessments, and to determine factors that mediate this association.

Sources of Funding This work was supported by grants from the National Institutes of Health (NIH: ES022243, ES000002, AG008122, AG033193, AG016495, NS017950, and N01 HC025195 ) and the United States Environmental Protection Agency (USEPA; RD834798 ). The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH or the USEPA. No funding organization had any role in the design and conduct of the study; collection; management, analysis and interpretation of the data; and preparation of the article. Its contents are solely the responsibility of the grantee and do not necessarily represent the official views of the funders. Furthermore, USEPA does not endorse the purchase of any commercial products or services mentioned in the publication.

Disclosures None.

Footnotes