Alexeeff et al. and a positive association for those not taking statins, but further investigation is needed to clarify this potential effect. TRAP and inflammatory response. Several studies have examined the effects of short- term (i.e., < 24 hr to 3 weeks) TRAP and various markers of inflammation. For exam- ple, in a large epidemiological study, daily increases in ambient PM levels were posi- tively associated with plasma fibrinogen levels, with the strongest association observed in par- ticipants with chronic obstructive lung dis- ease (Schwartz 2001). In a study of a small (n = 29) elderly population, Delfino et al. (2008) examined inflammatory markers and PM components measured at each subject’s home for 1–9 days on average. The authors reported that several traffic-related compo- nents were significantly associated with CRP and interleukin-6, and observed positive but nonsignificant associations with sICAM-1 and sVCAM-1. In other studies of NAS participants, traf- fic-related PM (BC and organic carbon) expo- sure has also been positively associated with plasma total homocysteine concentrations (Park et al. 2008), and this association is mod- ified by polymorphisms in genes related to oxidative stress (Ren et al. 2010). PM2.5 and BC averages of 1–3 days measured at the cen- tral site have been associated with increased vascular cell adhesion in NAS participants (Madrigano et al. 2010). Traffic-related PM (particle number and BC) has also been posi- tively associated with inflammatory markers (CRP, white blood cell count, sediment rate, and fibrinogen) in NAS participants, with sICAM-1 Not diabetic Diabetic r r r r stronger associations with particle numbers than with BC and stronger associations with BC averaged over 4 weeks than averaged over 48 hr or 1 week (Zeka et al. 2006). Few controlled studies of PM on human inflammatory response have been conducted, but one reported that plasma fibrinogen increased after exposure to urban PM (Ghio et al. 2000), and another reported that periph- eral neutrophils, sVCAM-1, and sICAM-1 increased after a 1-hr exposure to diesel PM (Salvi et al. 1999). Mechanisms and interactions. Diabetics have impaired endothelial function com- pared with nondiabetics (Calles-Escandon and Cipolla 2001), and there is increasing evidence that diabetics are more susceptible to the effects of air pollution. Inverse associations between 60-day average BC exposure and bra- chial artery flow-mediated dilation (FMD) were stronger in diabetics than in non- diabetics (O’Neill et al. 2005). Associations between 24-hr exposure to PM2.5 and FMD were stronger among diabetics with markers of severe insulin resistance compared with other diabetics (Schneider et al. 2008). In contrast with our findings, obese NAS participants have been reported to have stronger associations between short-term BC exposure and plasma CRP, erythrocyte sedi- ment rate (Zeka et al. 2006), and sVCAM-1 (Madrigano et al. 2010) than nonobese participants. Our finding that statin users are less sus- ceptible than those not taking statins is gener- ally consistent with other studies. In diabetics, stronger associations of PM2.5 and BC with sVCAM-1 10.0 8.0 6.0 t e4.0 n c eP2.0 0 –2.0 –4.0 10.0 8.0 t 6.0 n ec4.0 eP2.0 0 –2.0 –4.0 sVCAM-1 were reported among those not using statins than in statin users (O’Neill et al. 2007). Associations between CRP and traffic PM exposures of 5 and 9 days were reported to be stronger among those using statins than those not using statins (Delfino et al. 2008). Statins promote endothelial nitric oxide release, which reduces cell adhesion, thus suggesting a mechanism for this association. However, we cannot rule out the possibility that statin use is an indicator of health status or some other unmeasured factor that may explain why BC did not appear to influence sICAM-1 and sVCAM-1 in statin users. The question of which CAM is most closely associated with PM remains unre- solved. Differences in the associations reported in epidemiological studies of the two CAMs could reflect differences in cell types that express the molecules or differences in the process of cleavage and shedding from endothelial cells. In the present study, the effects on both sICAM-1 and sVCAM-1 were consistent: The effect sizes were similar and the direction of the effects and the inter- actions were the same, even though we found differences in statistical significance. Thus, our study does not support the idea of a differ- ent underlying mechanism for the effects of TRAP on these two CAMs. The expression of both ICAM-1 and VCAM-1 on the surface of vascular endothe- lial cells is associated with the formation of early atherosclerotic lesions. Although the relationship between the degree of cellular ICAM-1 and VCAM-1 expression and plasma concentrations of soluble forms is not entirely clear, multiple studies have shown that sICAM-1 and sVCAM-1 predict risk of car- diovascular disease (Albert and Ridker 1999; Pradhan et al. 2002; Rana et al. 2011; Ridker et al. 2003). In a recent study investigating the variability of sICAM-1 and sVCAM-1 measures over a 4-week period, Eschen et al. (2008) reported an estimated intrasubject variability of 7.6% for sICAM-1 and 9.5% for sVCAM-1, which suggests that these markers are relatively stable over a 4-week period. Exposure estimation. A major advantage of the present study is the use of a validated land-use regression model to character- ize the individual-level differences in expo- sures instead of classifying exposure based on measurements at the nearest monitor, land- use regression models without BC measure- ments, or a weighted form of distance to roadway. Although the study is still limited by the lack of individual-level monitoring data at the home, our validation study suggests that our estimates are highly correlated with actual exposure measurements at locations in Boston other than those used to fit the model and are much more closely correlated with these measurements than are exposure estimates ovlume 119 | number 4 | April 2011 • Environmental Health Perspectives 4-week 8-week 12-week 4-week 8-week 12-week Figure 2. Estimated percent increase in sICAM-1 (A) and sVCAM-1 (B) levels by diabetic status, per 0.3-μg/m3 increase in BC, for 4-, 8-, and 12-week averages. sICAM-1 No statin Statin sVCAM-1 10.0 8.0 t 6.0 ecn4.0 eP2.0 0 –2.0 –4.0 10.0 8.0 t 6.0 n ec4.0 eP2.0 0 –2.0 –4.0 484 4-week 8-week 12-week 4-week 8-week 12-week Figure 3. Estimated percent increase in sICAM-1 (A) and sVCAM-1 (B) levels by statin use, per 0.3-μg/m3 increase in BC, for 4-, 8-, and 12-week averages.