Fuks et al. age, ethnicity, and lifestyle of the study popu- lations, differences in exposure assessment, and so on. Auchincloss et al. (2008) estimated a 1.0-mmHg increase in systolic BP with a 10-gμ/m 3 increase in mean monthly PM2.5 in a North American population. This estimated effect is smaller than ours; however, consid- ering that yearly mean is less variable than monthly mean, which is reflected in a smaller IQR and exposure contrast in our study, the observed effects are quite similar. Although we estimated a small absolute change in BP in our study, it is of potential public health importance. High BP is the most important determinant of cardiovascu- lar mortality, and even small changes on the population level can lead to a high burden of attributable disease (Chobanian et al. 2003; Ezzati et al. 2002). An exposure contrast of only a few micrograms per cubic meter of PM2.5 in the urban background concentration may therefore lead to a shift in the popula- tion distribution of BP similar in effect size to the dietary salt reductions (Hooper et al. 2004). From this perspective, levels of urban background air pollution can be seen as a tar- get for population-based preventive strategies (Rose 1985). Furthermore, we did not find evidence of a departure from a linear relation- ship between PM and BP, which supports the importance of reducing PM exposures at all levels. High BP also plays a major role in the development and progression of atheroscle- rosis. Our findings point to PM-related BP increases as one possible, although not exclu- sive, mechanism by which PM air pollution may lead to atherosclerosis, as suggested in recent studies (Bauer et al. 2010; Hoffmann et al. 2007; Künzli et al. 2010). No single highly susceptible group could be identified in our analysis of subject charac- teristics. Rather, the estimated effect seemed consistent across the population. We found no clear effect modification of the PM effect by season, but the estimate was somewhat higher in spring and summer. This observa- tion is similar to results of Choi et al. (2007), who reported PM effects on BP only dur- ing the warm season. Possible explanations include a) a different chemical composition of the PM mixture during the warm season, when, in the absence of household heating, traffic emissions cause a greater fraction of the overall particle mass or b) varying ven- tilation patterns in warm and cold seasons, resulting in different personal exposure. We estimated higher within-city effects for Essen and Bochum compared with Mülheim, simi- lar to our previous analysis of fine PM and carotid intima-media thickness (Bauer et al. 2010). One possible explanation is the nature of the PM mixture. Exposure in Mülheim is characterized by the more even distribu- tion of regionally transported PM, whereas in 1710 Bochum and Essen, local heavy industry con- tributes to within-city variations of primary industrial emissions (Bauer et al. 2010). The spatial distribution of traffic-related PM is on a small scale for up to 400 m from a road (Zhou and Levy 2007). The EURAD model estimates an average background expo- sure in 1-km2 grid cells. In order to capture the small-scale traffic-related exposures, we therefore included traffic indicators as sur- rogates for the combined exposure to freshly produced traffic-related PM and traffic noise. Alternatively, we included modeled residential traffic noise exposure, making use of the man- datory European Union noise maps. Although adjustment for proximity to high traffic or traffic noise did not influence main effect esti- mates for urban background PM on BP, our results suggest a possible association of residen- tial proximity to high traffic and high traffic noise with BP and prevalence of hypertension. We consider these findings to be indicative of traffic-related effects on a small spatial scale, independent of and in addition to the effects of urban background air pollution. In future analyses, we plan to investigate association between the local exposure to traffic-related air pollution and arterial BP more precisely, using different techniques for exposure assessment. Our results on road traffic noise exposure are in line with the recent evidence (Bluhm et al. 2007; Bodin et al. 2009). Because of relatively small numbers of highly exposed participants, effects of noise exposure on BP were not estimated precisely enough in our study to reach definitive conclusions. An assessment of personal characteristics (e.g., impaired hearing) and of individual measures to reduce traffic noise exposure (type of win- dows, location of bedroom, ventilation habits) will help to clarify the role of chronic noise exposure on BP in future analyses. The posi- tive associations of traffic indicators with BP and prevalence of hypertension, independent of the effect of background PM, may also indicate an effect of traffic-related PM. The lack of a clear association of back- ground PM exposure with prevalent hyper- tension might be due to loss of information when using a dichotomized outcome instead of a continuous outcome like BP. Another possible explanation includes the misclassifica- tion of the outcome hypertension, which was defined as a combination of measured BP and intake of drugs used for antihypertensive treat- ment. Some of these drugs have overlapping indications (e.g., diuretics or angiotensin- converting enzyme inhibitors might have been prescribed for heart failure instead of hyper- tension), leading to a false-positive assignment of hypertension in some cases. Additionally, local traffic-related PM, which is not captured in our PM model, may have stronger health effects than the mixture of background air pollution. This is supported by several studies that have shown an association of markers of subclinical atherosclerosis or cardiac function with traffic proximity but not with PM (Adar et al. 2010; Hoffmann et al. 2007; Künzli et al. 2010; Van Hee et al. 2009). One limitation of our study is its cross- sectional design, which precludes a causal interpretation of the complex relationship between different risk factors for hypertension, BP, and antihypertensive medication. If PM actually caused an increase in BP, one would expect a higher use of antihypertensive medi- cation in highly exposed subjects, assuming the same level of medical care. The intake of anti- hypertensive medication, however, decreases BP. If only this mechanism were in place, one would expect a negative or association of PM and BP in the medicated participants. However, because the hypothesized effect of long-term PM exposure on BP is expected to be small relative to the effect of individ- ual characteristics (e.g., age, BMI, physical activity), we assumed that its impact on the presence or absence of antihypertensive medi- cation is likewise small compared with other risk factors. In sensitivity analyses, we explored the association of long-term PM exposure and BP with different model specifications, such as including and excluding antihypertensive medication from the adjustment set. Also, we limited the analysis to participants who did not use antihypertensive medication, thereby selecting possibly less susceptible individu- als. None of these measures had an effect on the main estimate, but further analyses using follow-up data with repeated measurements of BP and incident hypertension will shed more light on this problem. We did not explore the association of spe- cific components of PM (e.g., black smoke) with BP, thus we are not able to identify the pathogenic constituents of urban background PM. Because effects of traffic exposure were observed mostly in relation to heavy-duty traffic consisting of diesel-powered engines, exploration of the compounds of air pollution and investigation of the effects of smaller par- ticles should be the direction of future research. Other modeling techniques, such as land use regression models, which can model traffic-re- lated air pollution on very small spatial scales of 10–20 m, are complementary to the chemistry transport model used here, which models the average exposure in a 1-km2 grid cell. Conclusions We found an association of long-term expo- sure to PM with increased arterial BP in a population-based sample. This finding sup- ports our hypothesis that long-term PM exposure may promote atherosclerosis with air-pollution–induced increases in BP being one possible biological pathway. ovlume 119 | number 12 | December 2011 • Environmental Health Perspectives