Associations between PM2.5 and Heart Rate Variability Are Modified by Particle Composition and Beta-Blocker Use in Patients with Coronary Heart Disease

Background It has been hypothesized that ambient particulate air pollution is able to modify the autonomic nervous control of the heart, measured as heart rate variability (HRV). Previously we reported heterogeneous associations between particulate matter with aerodynamic diameter < 2.5 μm (PM2.5) and HRV across three study centers. Objectives We evaluated whether exposure misclassification, effect modification by medication, or differences in particle composition could explain the inconsistencies. Methods Subjects with coronary heart disease visited clinics biweekly in Amsterdam, the Netherlands; Erfurt, Germany; and Helsinki, Finland for 6–8 months. The standard deviation (SD) of NN intervals on an electrocardiogram (ECG; SDNN) and high frequency (HF) power of HRV was measured with ambulatory ECG during paced breathing. Outdoor levels of PM2.5 were measured at a central site. In Amsterdam and Helsinki, indoor and personal PM2.5 were measured during the 24 hr preceding the clinic visit. PM2.5 was apportioned between sources using principal component analyses. We analyzed associations of indoor/personal PM2.5, elements of PM2.5, and source-specific PM2.5 with HRV using linear regression. Results Indoor and personal PM2.5 were not associated with HRV. Increased outdoor PM2.5 was associated with decreased SDNN and HF at lags of 2 and 3 days only among persons not using beta-blocker medication. Traffic-related PM2.5 was associated with decreased SDNN, and long-range transported PM2.5 with decreased SDNN and HF, most strongly among persons not using beta blockers. Indicators for PM2.5 from traffic and long-range transport were also associated with decreased HRV. Conclusions Our results suggest that differences in the composition of particles, beta-blocker use, and obesity of study subjects may explain some inconsistencies among previous studies on HRV.

Increased cardiovascular mortality and mor bidity have been reported in association with increases in daily ambient levels of particulate matter (PM) in epidemiologic studies (Analitis et al. 2006;Le Tertre et al. 2002;Samet et al. 2000). However, it is not known which con stituents of particles are responsible for the effects associated with particle mass. The source of particles defines their composition. Recent epidemiologic studies suggest that par ticles from combustion sources are especially harmful (Laden et al. 2000;Lanki et al. 2006). Transition metals and organic carbon com pounds were shown to be toxic in a toxicologic study (Pagan et al. 2003). These can be found in abundance in combustion particles.
The relative importance of different path ways from particle exposure to effects on the cardiovascular system is not clear, but expo sure to particles has been associated both with increased systemic inflammation and changes in autonomic nervous control of the heart (Brook et al. 2004). The latter is most often measured indirectly as heart rate variability (HRV) (Task Force 1996). A decreased overall HRV has proven to be a strong independent predictor of cardiac mortality in subjects with existing cardiovascular disease (La Rovere et al. 1998;Nolan et al. 1998). Several studies have shown decreased indices of HRV on days with increased outdoor levels of respirable particles [aerodynamic diameter < 10 µm (PM 10 )] (Liao et al. 2004;Lipsett et al. 2006) and fine par ticles [< 2.5 µm (PM 2.5 )] (Holguín et al. 2003;Schwartz et al. 2005).
In the Exposure and Risk Assessment for Fine and Ultrafine Particles in Ambient Air (ULTRA) study, levels of outdoor air pol lution were monitored for 6-8 months in [1998][1999] in three European cities. At the same time, panels of patients with coronary heart disease were followed up with measure ments of HRV. We previously reported that the levels of ultrafine particles (PM < 0.1 µm) were associated with changes in the balance between sympathetic and vagal nervous input to the heart (Timonen et al. 2006). However, PM 2.5 in particular showed different associa tions with HRV in the different study centers. In Helsinki, Finland, elevated concentrations of PM 2.5 were associated with decreased high frequency (HF) and increased low frequency (LF)/HF ratio, whereas the opposite was true in Erfurt, Germany. No such associations were observed in Amsterdam, the Netherlands.
In the present article, we evaluate whether exposure misclassification, effect modifica tion by medication, or variable particle com position could explain these inconsistencies. Personal and indoor PM 2.5 were measured in Amsterdam and Helsinki to obtain more accurate estimates of exposure. Possible effect modification by betablocker (βadrenergic antagonist) medication or obesity was evalu ated in light of the limited number of earlier studies (Chen et al. 2007;Park et al. 2005;Wheeler et al. 2006). For comparison, we also tested other medication possibly modifying the effect of particulate air pollution on HRV.
Finally, we linked sourcespecific PM 2.5 with HRV to evaluate the importance of particle composition for cardiovascular effects of PM.

Methods
Heart rate variability was measured at biweekly clinic visits in panels of elderly subjects with Background: It has been hypothesized that ambient particulate air pollution is able to modify the autonomic nervous control of the heart, measured as heart rate variability (HRV). Previously we reported heterogeneous associations between particulate matter with aerodynamic diameter < 2.5 µm (PM 2.5 ) and HRV across three study centers. oBjective: We evaluated whether exposure misclassification, effect modification by medication, or differences in particle composition could explain the inconsistencies. Methods: Subjects with coronary heart disease visited clinics biweekly in Amsterdam, the Netherlands; Erfurt, Germany; and Helsinki, Finland for 6-8 months. The standard deviation (SD) of NN intervals on an electrocardiogram (ECG; SDNN) and high frequency (HF) power of HRV was measured with ambulatory ECG during paced breathing. Outdoor levels of PM 2.5 were measured at a central site. In Amsterdam and Helsinki, indoor and personal PM 2.5 were measured during the 24 hr preceding the clinic visit. PM 2.5 was apportioned between sources using principal component analyses. We analyzed associations of indoor/personal PM 2.5 , elements of PM 2.5 , and source-specific PM 2.5 with HRV using linear regression. results: Indoor and personal PM 2.5 were not associated with HRV. Increased outdoor PM 2.5 was associated with decreased SDNN and HF at lags of 2 and 3 days only among persons not using beta-blocker medication. Traffic-related PM 2.5 was associated with decreased SDNN, and longrange transported PM 2.5 with decreased SDNN and HF, most strongly among persons not using beta blockers. Indicators for PM 2.5 from traffic and long-range transport were also associated with decreased HRV. conclusions: Our results suggest that differences in the composition of particles, beta-blocker use, and obesity of study subjects may explain some inconsistencies among previous studies on HRV. key words: absorbance, air pollution, cardiovascular health, elements of PM 2.5 , heart rate variability, medication, PM 2.5 , source-specific particulate matter.  Amsterdam, Erfurt, andHelsinki in 1998-1999. In Amsterdam, 37 panelists were followed for 8 months, and in Erfurt and Helsinki, 47 panelists were fol lowed for 6 months. The visits of every subject were always scheduled for the same weekday and for the same time. The medication of the subjects was not changed for the clinic visits. Outdoor levels of PM 2.5 were measured concurrently with the visits at one central site in each city. In Helsinki and Amsterdam, indoor and personal measurements of PM 2.5 were also performed during the 24 hr preced ing the clinic visit. All measurements in the study were performed according to standard operating procedures (Brunekreef et al. 2005;Pekkanen et al. 2000).
The main inclusion criteria for the study were a selfreport of a physiciandiagnosed coronary heart disease, being a nonsmoker, and age ≥ 50 years. Ethical committees in each study center approved the study proto col. A written informed consent was obtained from all subjects.
At the clinic visits, HRV was recorded with an ambulatory electrocardiogram (ECG) recorder (Medilog MR 63 recorder; Oxford Instruments, Abington, UK) using a standardized protocol (Timonen et al. 2006). Breathing frequency strongly affects HRV, and for that reason, HRV recorded during a 5min period of paced breathing in supine position (frequency 0.2 Hz; 2.5sec inhala tion and 2.5sec exhalation) has been used for the analyses. Twochannel ambulatory ECG recordings were performed with analog ambulatory ECG recorders (Medilog MR 63 recorder; Oxford Instruments) using standard electrode position for leads V1 and V5. The recordings were analyzed with ambulatory ECG analysis software (Exel Medilog II V7.5 system; Oxford Instruments). The record ings were digitized with a sampling rate of 128 Hz. The software used an interpolation algorithm to refine the R wave fiducial point and to improve the resolution in Rpeak detection. Details of the analyses have been published previously (Tarkiainen et al. 2005;Timonen et al. 2006).
We were mainly interested in explaining the heterogeneous results in the main end points [the SD of NN intervals (SDNN), HF, and LF/HF ratio] of a previous ULTRA paper (Timonen et al. 2006). Therefore, we used two common indices of HRV in the present analyses: SDNN, which is a time domain measure of overall HRV, and HF power (0.15-0.4 Hz) of HRV, which is a frequency domain measure believed to reflect mainly the vagal (parasympathetic) part of the autonomic nervous input to the heart. HF is highly correlated with rMSSD, a commonly used timedomain variable (Task Force 1996). The LF/HF ratio was left out of the paper, because the interpretation and physiological basis are more controversial.
Information on physicianadministrated daily medication was collected at baseline visit. Medication categories tested for effect modification were betablockers, calcium (Ca 2+ ) channel blockers, statins, angiotensin converting enzyme (ACE) inhibitors, angi otensin receptor blockers, and acetylsalicylic acid (ASA). Antiarrhythmic medication was not included in the analyses because of lim ited use among study participants (7%).
Harvard impactors (BGI, Inc., Waltham, MA, USA) were used to collect filter sam ples of outdoor PM 2.5 ; GK2.05 cyclones and batteryoperated AFC400S pumps (BGI, Inc.) were used for the collection of personal PM 2.5 samples. The filters were weighted to determine mass of PM 2.5 , and reflectance was measured with a reflectometer (Model 43, Diffusion Systems Ltd., London, UK). The reflectance was transformed into absorb ance [absorption coefficient (ABS)], which is an indicator for elemental carbon. Finally, elemental composition of the samples was determined using energydispersive Xray fluorescence spectrometry. All methods have been described in detail in previous papers (Brunekreef et al. 2005;de Hartog et al. 2005;Janssen et al. 2000. We used principalcomponent analysis and multivariate linear regression to apportion PM 2.5 mass to different sources (Vallius et al. 2005), thereby obtaining estimates of daily sourcespecific PM 2.5 concentrations. Besides components of PM 2.5 (elemental concentra tions and absorbance), daily data on ultrafine (diameter < 0.1 µm) and accumulation mode particles (0.1-1.0 µm), nitrogen dioxide, and sulfur dioxide were used to identify sources.
We identified four to six main source categories in each city: local traffic (with contribution from other local combustion sources), longrange transported (secondary) air pollution, industry, crustal, oil combus tion, and salt (Vallius et al. 2005).
We analyzed data using the SAS statistical package and mixed models (PROC MIXED) (SAS Institute Inc., Cary, NC, USA) taking into account repeated observations and assum ing constant correlation between observations within a subject. A basic model was first built without including particulate air pollution in the model. Criteria for building the basic model were Akaike's information criterion and covariateresponse plots. The same basic mod els as in the previous paper have been used (Timonen et al. 2006). Lag 0 was defined as the 24hr period from noon of the day of the clinic visit to noon of the previous day, lag 1 was the previous 24hr period, and so on. In Amsterdam, the model included linear terms for time trend, temperature (lag 2), relative humidity (lag 3), and barometric pressure. In Erfurt, the model included linear terms for time trend, relative humidity (lag 3), and barometric pressure (lag 2). Temperature (lag 3) was mod eled with linear, squared, and cubic terms. The basic model for Helsinki included linear terms for time trend, relative humidity (lag 1), and barometric pressure (lag 1). Temperature (lag 3) was modeled with linear and squared terms. In all cities, the model included weekday as a categorical variable. Results were insensitive to alternative model specifications.
For comparison of the effects of outdoor, indoor, and personal PM 2.5 on HRV, only the days with all three types of measurements were included in the analyses. We analzed asso ciations of sourcespecific PM 2.5 with HRV using multipollutant models that included at the same time all identified sources and the unidentified PM 2.5 fraction. Multipollutant models were not used for elements of PM 2.5 because of high intercorrelations. We ana lyzed data only for the elements that are either indicators for the PM 2.5 sources or that have been found harmful in toxicologic studies. The indicators were chosen based on the elemen tal profiles of sources (Vallius et al. 2005): absorbance for local traffic; sulfur for long range transported particles; vanadium for oil combustion (not used for Erfurt because oil source was not identified there, and > 50% of concentrations were below detection limit); Ca for soil particles; and chloride for salt particles (not in Erfurt). Elements considered because of potential toxicity were the transition metals copper, iron, and zinc. HF was logtransformed for the analy ses, and the effect of particulate air pollution on the end point was estimated as percent change: [e (β × IQR) -1] × 100%, where β is the estimated regression coefficient and IQR is the interquartile range. Effect estimates for the elements are presented for increases that are close to study mean interquartile ranges (IQRs)-the differences between the 25th and 75th percentiles of the exposure distribu tions. Pooled effect estimates were calculated as a weighted average of the centerspecific estimates using the inverse of centerspecific variances as weights. The heterogeneity of effect estimates between centers was tested with a chisquare test (Normand 1999).
Effect of extreme sourcespecific PM 2.5 values on the results was evaluated by exclud ing at each lag the concentrations that were more than three times the IQR.

Results
There were 424 clinical visits in Amsterdam, 491 in Erfurt, and 519 in Helsinki. Although special care was given to attachment of the electrodes, some ECG recordings were unsuc cessful. There were 366 successful recordings (from 33 patients) in Amsterdam,432 (44) in Erfurt,and 468 (45) in Helsinki.
In Helsinki, the proportion of males and females was almost equal, but in Amsterdam the panel contained mostly males and in Erfurt almost exclusively males (Table 1). Obesity was common in Helsinki, where one third of the study subjects were obese (17 persons). There were clearly fewer obese per sons in Amsterdam and Erfurt (7 in both). The most commonly used medication was ASA. About twothirds of the study sub jects in Erfurt and Helsinki had daily beta blocker medication, whereas only about onethird of the subjects were on medica tion in Amsterdam. Except for SDNN in Amsterdam, HRV indices were lower among betablocker users than among nonusers.
Outdoor levels of PM 2.5 were lower in Helsinki than in Amsterdam and Erfurt (Table 2). In Helsinki, about half of PM 2.5 was of secondary origin, that is, could be consid ered longrange transported; in Amsterdam and Erfurt, this was about onethird. Industrial sources of PM 2.5 were not identified in Helsinki (Vallius et al. 2005). Oil combustion and salt as sources of PM 2.5 were not identified in Erfurt, and the indicator elements for these sources have not been included. PM 2.5 (total) correlated most strongly with longrange transported PM 2.5 , and the cor relation with S, the indicator element for this source, was even higher (Table 3). Transition metals Zn, Fe, and Cu correlated highly with absorbance, with the correlation highest for Cu in Amsterdam (r = 0.83) and lowest for Fe in Helsinki (r = 0.49) (data not shown).
Outdoor, indoor, and personal PM 2.5 were not associated with SDNN at lag 0 ( Figure 1). Indoor and personal PM 2.5 meas urements were not available at lags 1, 2, or 3. There was a suggestive positive association of outdoor and personal PM 2.5 with HF.
Among study subjects not on daily beta blocker medication, increased concentrations of PM 2.5 were associated with decreased SDNN and HF, especially at longer lags ( Figure 2). For this group the cityspecific estimates were homogeneous. There was a positive association at single (1day) lag between PM 2.5 and HF among subjects who were on medication.
There was no consistent modification of the effects of PM sources by medication other than betablockers (results not shown). Those not using ACE inhibitors or angio tensin receptor blockers had more clearly decreased HF in association with longrange transported PM than all subjects [at lag 2: -1.25; 95% confidence interval (CI), -2.09 to -0.41; at lag 3: -1.1; 95% CI, -2.04 to  On the other hand, those not using statins had decreased HF in association with PM 2.5 at a 3day lag (-6.45; 95% CI, -11.63 to -0.96), but no modifying effect of statins was observed for sourcespecific PM 2.5 or SDNN. Obesity was not associated with beta blocker use: 60.0% of obese and 60.4% of non obese persons used betablockers. However, obesity itself seemed to modify the effects of PM 2.5. At a 3day lag, PM 2.5 was associated with SDNN (-1.99; 95% CI, -3.69 to -0.30) and HF (-12.50; 95% CI, -20.1 to -4.24) among obese persons, whereas such an effect was not observed among all subjects. Effects of long range transported PM 2.5 were similarly modi fied by obesity (results not shown), obviously because of substantial correlation between PM 2.5 and longrange transported PM 2.5 . However, no such effect modification was observed for PM 2.5 from traffic or other sources of PM 2.5 .
Increases in PM 2.5 originating from local traffic were consistently associated with decreased SDNN, somewhat more strongly among study subjects not using betablock ers than in the whole study panel (Table 4). Longrange transported PM 2.5 was associated with decreased SDNN and HF at lags 2 and 3 among persons not having daily betablocker medication. Among all subjects, there was hetero geneity in the effect estimate for long range transported PM at a 2day lag for HF because of negative estimates in Amsterdam (-0.91; 95% CI, -2.02 to 0.22) and Helsinki (-1.92; 95% CI, -3.26 to -0.57) and a posi tive estimate in Erfurt (0.25; 95% CI, -0.81 to 1.31). There was evidence of the effect of PM 2.5 from oil combustion only for SDNN among nonmedicated subjects. Crustal PM 2.5 was associated with increased HF irrespec tive of medication use at lag 2. Associations between 5day average (lags 0-4) particulate air pollution and HRV were weaker than for individual lags (data not shown).
The fraction of PM 2.5 that could not be linked to any particular source category was positively associated at 0day lag with SDNN (estimate 0.18; 95% CI, 0.00 to 0.35) and HF (1.53; CI, 0.48 to 2.59) among all study sub jects, but the association was not evident among subjects not using betablockers. The positive association between unidentified PM 2.5 frac tion and SDNN disappeared when extreme sourcespecific PM 2.5 concentrations were excluded from the analyses. Overall, exclusions of extreme values did not change the interpre tation of the results. After exclusion, the city specific estimates were no longer heterogeneous for the association of longrange transported PM 2.5 with HF at lag 2 among all study centers.
Among persons not having daily beta blocker medication, increases in absorbance (local traffic) and S (longrange transport) were consistently associated with decreased SDNN and HF (Table 5). The associations between V (oil combustion) and HRV were less consistent, and for the other source indi cators there was no evidence of an effect. Table 4. Pooled effect estimates in three study panels [β (95% CIs)] a for the associations of source-specific PM 2.5 with HRV in multipollutant models. b

SDNN (msec) HF (%) All subjects
Subjects without beta-blockers All subjects Subjects without beta-blockers   However, for the transition metals (Cu, Fe, and Zn) included because of potential toxic ity, there was some evidence of negative asso ciations with HRV at longer lags.

Discussion
In this panel study conducted among persons with coronary heart disease in three European cities, personal, indoor, or outdoor PM 2.5 measured during the 24 hr preceding clinic visit (lag 0) were not associated with HRV. However, at 2 and 3day lags, we observed that daily increases in outdoor levels of PM 2.5 were associated with decreased HRV, but only among persons not on betablocker medica tion. When we linked sourcespecific PM 2.5 to HRV, we observed increases in trafficrelated PM 2.5 to be associated with decreased SDNN, especially among persons who were not on betablocker medication. Daily increases in the longrange transported PM 2.5 were associ ated both with decreased HF and SDNN, more strongly or exclusively among nonmedi cated persons. In separate analyses, indicator elements for these two sources, absorbance and S, were also negatively associated with HRV among persons not on medication. There was also evidence for a negative associa tion of transition metals with HRV. We reported previously that outdoor lev els of PM 2.5 were not consistently associated with HRV in the three study panels (Timonen et al. 2006). However, people spend most of their time indoors, and persons with com promised health, like the panel members in our study, even more so (Brunekreef 2005). Consequently, outdoor levels of particulate air pollution measured at a central site may not be perfect proxies for variation in personal PM exposure. However, we did not find per sonal or indoor PM 2.5 to be associated with decreased HRV. Unfortunately, we had only personal and indoor measurements in the 24 hr preceding the clinic visit, and PM 2.5 mass and composition during that time period were not associated with HRV. Our observation thus indicates only that the lack of association at 0day lag for outdoor PM 2.5 was not due to exposure misclassification. In some studies, the effects of PM on HRV have been observed even within hours of exposure (Devlin et al. 2003;Gold et al. 2000). However, the use of daily averages to measure PM 2.5 exposure in our study prevented us from detecting possible immediate effects of PM.
Betablockers have been shown to enhance HRV in patients with coronary heart disease (Niemela et al. 1994;Sandrone et al. 1994). Consistent with this, we observed increased outdoor levels of PM 2.5 to be associated with decreased SDNN and HF (at 2 and 3day lags) only among persons not using betablock ers. Effect modification by medication use thus seems to explain the lack of associations between PM 2.5 and HRV in our previous anal ysis (Timonen et al. 2006). There was little evidence of effect modification by any other medication group in the present study.
The interpretation of earlier studies evalu ating the importance of betablocker use for the effects of ambient particles on HRV is somewhat difficult because of the differences in disease status between users and nonusers of betablockers. In a study by Park et al. (2005) conducted among veteran men, betablocker users were all hypertensive, whereas only half of the nonusers had hypertension. No clear effect of PM 2.5 (adjusted for ozone) on SDNN or HF was observed in either medication group. However, the lowfrequency component of HRV decreased in association with PM 2.5 only among persons not using betablockers. In a study by Wheeler and coworkers (2006), all but one of the betablocker users were myocardial infarction survivors, whereas most nonusers had chronic obstructive pulmonary disease. Effect modification by betablocker use was reported only for SDNN, which decreased in association with PM 2.5 among users and increased among nonusers. In the present study, all patients had coronary heart disease, and our results suggest that the use of betablockers modifies the effect of PM on HRV even in this more homogene ous patient group.
Medication use is obviously never inde pendent of health status. Consequently, the suggestive increase in HF in association with PM 2.5 among betablocker users in our study may indicate either that the use of medication changes the direction of the association, or that those with less severe heart disease differ in their response to particulate air pollution. Obesity has been suggested to modify the effects of PM on HRV (Chen et al. 2007), which was con firmed by our results. PM 2.5 seemed to be more strongly associated with HRV among obese persons. In our study, obesity was not associ ated with betablocker use. Clinical studies have related decreased HRV in cardiac patients with increased risk of mortality over relatively long periods of followup (Task Force 1996). The extent to which shortterm decreases in HRV measures predict shortterm mortality is not known. However, vagal withdrawal is observed a few minutes before transient ischemic events (Kochiadakis et al. 2000;Kop et al. 2001), suggesting that shortterm changes in HRV are not harmless. In a large study among elderly subjects (de Bruyne et al. 1999), increased HRV has been even more strongly associated with decreased survival than decreased HRV. Taking this into account, our study cannot be straightforwardly inter preted as showing that betablocker use is protective against the effects of particulate air pollution on cardiovascular health, because there was a suggestive increase in HF in asso ciation with PM 2.5 among medicated persons.
There was some indication of the effects of traffic related PM 2.5 on SDNN, and long range transported PM 2.5 on HF and SDNN even before taking medication into account, but after considering betablocker use, the associations became stronger. Some earlier studies have evaluated the effects of traffic related particles on HRV without conducting source apportionment. Absorbance, consid ered as an indicator for trafficoriginating par ticles, has been more strongly associated with HRV among elderly subjects than PM 2.5 . Invehicle PM 2.5 was more strongly associated with HRV in healthy young men than were ambient or roadside PM 2.5 (Riediker et al. 2004a). Invehicle PM 2.5 was further apportioned among different sources (Riediker et al. 2004b), and strongest associations were observed between PM 2.5 from brake wear and engine emissions and HRV. Schwartz et al. (2005) evaluated indirectly the effects of secondary particles on HRV and found no effect. They regressed PM 2.5 against black carbon concentrations and interpreted residuals to represent the fraction of second ary particles that varied independently from primary combustion particles. It is possible that the effects of longrange transported PM 2.5 on HRV in our study are related to primary combustion particles generated, for example, by regional traffic. In our study, the effect esti mates (for SDNN) per microgram of particle mass were clearly higher for local trafficrelated PM 2.5 than for longrange transported parti cles. However, there was also some evidence of the effects of PM 2.5 from oil combustion on SDNN. The results are consistent with our pre vious study, where PM 2.5 from traffic and other local combustion was most strongly associated with the occurrence of ST segment depressions in Helsinki, but longrange transported particles and possibly oil combustion were also contrib uting to the effects of PM 2.5 (Lanki et al. 2006).
In the last part of our analyses, we evalu ated the associations of HRV with elements of PM 2.5 and absorbance, a proxy for ele mental carbon content of particles. In these analyses, decreased HRV was associated with absorbance and S, which were consid ered markers for local traffic and longrange transported PM 2.5 , respectively. The finding thus confirmed the analyses conducted using sourcespecific PM 2.5 . However, longrange transported PM 2.5 also contains trafficorigi nating PM and elemental carbon. There was also evidence of the negative associations of V (oil combustion), Zn (e.g., industry), Fe, and Cu with HRV, but the associations were mostly nonsignificant. Transition metals are typically associated with combustion proc esses, so it was not a surprise that absorbance was highly correlated with Zn, Fe, and Cu. It has been suggested that organic carbon compounds and transition metals attached to elemental carbon core (approximated by absorbance) are responsible for the effects of PM on health (Obot et al. 2002).
Toxicologic studies have often observed cellular defenses to be even more responsive to the coarse particle fraction (PM 10 -PM 2.5 ) than to finersize fractions (Hetland et al. 2004;Soukup and Becker 2001). The ambient lev els of coarse particles are typically dominated by crustal material, whereas PM 2.5 levels are more influenced by combustion emissions. In a recent study (Lipsett et al. 2006), coarse particles were associated with decreased HRV, whereas PM 2.5 was not. Interestingly, we found increases in HF in association with increased outdoor levels of crustal PM 2.5 . On the other hand, the chosen indicator element for crustal PM 2.5 -Ca-was not associated with HF.
Our study has both strengths and weak nesses. The study had rather stringent inclu sion criteria for the study subjects to obtain a homogeneous cardiac panel presumably vul nerable for the effects of air pollution (von Klot et al. 2005). The three study centers used common standard operating procedures and standardized equipment, and Holter record ings were analyzed in a single lab. HRV was recorded during a paced breathing period to avoid influence of breathing patterns on the results. However, because we measured out door levels of sourcespecific PM 2.5 instead of actual exposure, exposure misclassification may have biased the results. We previously reported considerable longitudinal correlations between outdoor and personal PM 2.5 , absorb ance (traffic), and S (longrange transport), but correlations were lower for Ca (soil), Cl (salt), and Cu . Finally, our sourcespecific PM 2.5 levels are not always products of homogeneous sources but rather of broader source categories.
In conclusion, we found PM 2.5 originating from local traffic and other local combustion and also longrange transported PM 2.5 to be associated with decreased indices of HRV. The effects were stronger among persons not using betablocker medication and among obese persons. Differences in the composition of particles and medication use or disease severity of study subjects may explain some inconsist encies between previous studies on HRV.