Fuks et al. 132.7 and 81.2 mmHg, respectively (Table 1). Hypertension (57.0%) and use of anti- hypertensive medication (36.1%) were highly prevalent in this elderly population. Mean 1-year PM2.5 and PM10 exposure for the study population were 16.7 and 20.7 gμ/m 3 , respectively. About 16% of study participants resided within 200 m of a highly trafficked road. One-year mean values of PM2.5 and PM10 were highly correlated with each other (Spearman correlation coefficient = 0.84; see Supplemental Material, Table 2). Correlations of long-term PM exposure with individual daily PM values were low (0.15–0.26), as were Table 1. Baseline characteristics (2000–2003) of the analyzed (n = 4,291) participants of the Heinz Nixdorf Recall Study. Variable Long-term exposure Mean PM2.5 (μg/m3) Mean PM10 (μg/m3) Traffic proximity, general (m) ≤ 50 > 50–100 > 100–200 > 200 24-hr mean noise [Lden, dB(A)] ≤ 55 > 55–60 > 60–65 > 65 Short-term environmental variables PM2.5 (3-day lag, μg/m3) PM10 (3-day lag, μg/m3) Temperature (3-day mean, °C) O3 (4-day mean, μg/m3) Outcome Systolic BP (mmHg) Diastolic BP (mmHg) Hypertension Antihypertensive medication Covariates Male sex Age (years) Coronary heart disease Diabetes mellitus BMI (kg/m2) Weekly physical activity (103 metabolic equivalents) Weekly alcohol intake (drinks) 0 1–3 > 3 Smoking Never Ex-smoker Current smoker Education ≤ 10 years 11–13 years 14–17 years ≥ 18 years Economic activity Employed Inactive/homemaker Retired Unemployed 1708 Mean ± SD (IQR) or n (%) 16.7 ± 1.6 (2.4) 20.7 ± 2.6 (3.9) 131 (3.1) 178 (4.1) 365 (8.5) 3,617 (84.3) 2,757 (64.3) 542 (12.6) 490 (11.4) 502 (11.7) 16.5 ± 9.5 20.5 ± 11.3 10.6 ± 7.4 37.4 ± 20.0 132.7 ± 20.6 81.2 ± 10.8 2,444 (57.0) 1,550 (36.1) 2,147 (50.0) 59.7 ±7.8 290 (6.8) 594 (13.8) 27.9 ± 4.6 1.3 ± 2.1 2,131 (49.7) 749 (17.5) 1,411 (32.9) 1,789 (41.7) 1,513 (35.3) 989 (23.0) 461 (10.7) 2,390 (55.7) 970 (22.6) 470 (11.0) 1,716 (40.0) 590 (13.8) 1,719 (40.1) 266 (6.2) correlations of PM with proximity to high traffic and road traffic noise (0.07–0.24). We found an association of long-term PM exposure with arterial BP, which was consistent across a wide range of different model specifi- cations (Table 2) [for the full results of the main model for systolic BP, see Supplemental Material, Table 3 (http://dx.doi.org/10.1289/ ehp.1103564)]. In the crude model, systolic BP increased by 1.0 mmHg [95% confidence interval (CI): 0.1, 2.0 mmHg], and diastolic BP by 0.3 mmHg (95% CI: –0.2, 0.8 mmHg) per 2.4-gμ/m 3 increase in 1-year mean PM2.5. Adjustment for short-term exposures and area- level variables led to small increases in the effect estimates. After adjusting for short-term exposures, traffic proximity, and individual- level covariates (main model), estimated effects on systolic and diastolic BP were 1.4 mmHg (95% CI: 0.5, 2.3 mmHg) and 0.9 mmHg (95% CI: 0.4, 1.4 mmHg), respectively. Temperature, female sex, and current smok- ing were inversely associated with systolic BP, whereas age, alcohol (> 3 drinks/week), BMI, and time trend showed positive association (see Supplemental Material, Table 3). Using road traffic noise instead of traffic proxim- ity and including individual SES in the main model did not change the estimates notice- ably (Table 2). When we used traffic counts within 100 m of the residence instead of traf- fic proximity, estimates remained unchanged (data not shown). Adjusting for antihyperten- sive medication, diabetes, short-term O3, and area-level variables did not alter the estimated effect of long-term PM2.5. Adjusting for the same variables also had little impact on esti- mated effects for PM10, with the exception of area-level variables, which attenuated esti- mated effects for PM10: 1.1 (95% CI: 0.2, 2.0) mmHg change in systolic BP in the main model and 0.6 (95% CI: –0.8, 2.1) mmHg when additionally adjusted for city and area. When restricting the study population to participants who did not use antihypertensive medication (n = 2,741), estimates for long- term PM2.5 were marginally lower for systolic BP and less precise: 1.1 (95% CI: 0.0, 2.2) mmHg and 0.8 (95% CI: 0.2, 1.4) mmHg increases in systolic and diastolic BP, respec- tively. Exclusion of participants with high noise exposure (Lden > 65 dB, n = 506) mar- ginally increased the estimates for PM2.5: 1.5 (95% CI: 0.6, 2.5) mmHg and 1.0 (95% CI: 0.4, 1.5) mmHg for systolic and diastolic BP, correspondingly. Results for PM exposures modeled in quartiles were consistent with monotonic relationships (Figure 1). Individual risk factors did not clearly modify the effect of PM2.5 on BP, although point estimates were increased somewhat for female sex, nondiabetics, nonsmokers, and participants with 11–17 years of education [representing medium SES in this cohort; for systolic BP, see Figure 2; for numeric values and interaction p-values for systolic and dia- stolic BP, see Supplemental Material, Table 4 (http://dx.doi.org/10.1289/ehp.1103564)]. Higher effects were also seen in those par- ticipants who were likely to spend more time at home, such as homemakers and retired subjects, but not for unemployed. Effect esti- mates were somewhat higher in the southern region, in the cities of Essen and Bochum, and in the spring and summer period. Residential proximity to high road traffic was linked to elevated systolic and diastolic BP with higher point estimates and linear trend in subjects living close to high heavy-duty traffic, but estimates were imprecise because of small numbers in the exposure groups or because of loss of information using a categorized vari- able [see Supplemental Material, Tables 5 and 6 (http://dx.doi.org/10.1289/ehp.1103564)]. Long-term road traffic noise exposure > 60 dB at the residence was linked to higher BP, but estimates were again imprecise and generally lower than for traffic proximity and long-term PM exposure (see Supplemental Material, Table 7). Table 2. Estimated absolute increase in arterial BP (mmHg) (with 95% CI) per corresponding IQR of long- term exposure to PM2.5 and PM10 (µg/m3) (n = 4,291). Change in arterial BP (mmHg) Per IQR of PM2.5 (2.4 μg/m3) Per IQR of PM10 (3.9 μg/m3) Model Systolic BP Diastolic BP Systolic BP Diastolic BP Crude 1.0 (0.1, 2.0) 0.3 (–0.2, 0.8) 1.3 (0.3, 2.2) 0.5 (0.0, 1.0) Basica 1.3 (–0.4, 3.0) 0.7 (–0.2, 1.6) 0.3 (–1.3, 1.9) 0.3 (–0.5, 1.2) + Noiseb and SES 1.5 (–0.1, 3.2) 0.7 (–0.2, 1.6) 0.6 (–0.9, 2.1) 0.3 (–0.5, 1.1) Mainc 1.4 (0.5, 2.3) 0.9 (0.4, 1.4) 1.1 (0.2, 2.0) 0.8 (0.3, 1.2) + Noiseb and SES 1.4 (0.5, 2.4) 0.8 (0.3, 1.4) 1.1 (0.2, 2.0) 0.7 (0.3, 1.2) Extended = main + Medication 1.4 (0.5, 2.3) 0.9 (0.4, 1.4) 1.1 (0.2, 2.0) 0.8 (0.3, 1.2) + Diabetes 1.4 (0.5, 2.4) 0.9 (0.4, 1.4) 1.1 (0.2, 2.0) 0.8 (0.3, 1.2) + O3d 1.3 (0.3, 2.2) 0.8 (0.3, 1.3) 1.0 (0.1, 1.9) 0.7 (0.2, 1.2) + City, area 1.5 (–0.1, 3.1) 0.7 (–0.2, 1.5) 0.6 (–0.8, 2.1) 0.5 (–0.3, 1.3) aAdjusted for short-term PM, temperature, season, time trend, traffic proximity, city, and area of residence. bModels adjusting for traffic noise do not include traffic proximity. cAdjusted for short-term PM, temperature, season, time trend, traffic proximity, sex, age, BMI, alcohol consumption, smoking, passive smoking, and physical activity. dBecause of high correlation with O3, short-term temperature was excluded from this adjustment set. ovlume 119 | number 12 | December 2011 • Environmental Health Perspectives