### Environmental Health Perspectives • volume 117 | number 5 | May 2009 

### 751 

# Research

Studies of human populations show that ambient particulate matter (PM) air pollu

tion is associated with coronary heart dis

ease (CHD) morbidity and mortality. The consistent findings suggest direct associations between both short- and long-term exposure to PM and CHD incident [Brook et al. 2004; Dockery et al. 1993; Miller et al. 2007; Pope

et al. 2006; U.S. Environmental Protection Agency (EPA) 2006] . However, biologi

cal mechanisms underlying the association between PM and CHD remain incompletely characterized in human populations despite calls for epidemiologic research designed to help elucidate them (Brook et al. 2004; Health Effects Institute 2002; National Research Council 2004). Resting, supine, standard 12 -lead electro

cardiography (ECG) has been recognized as a potentially valuable epidemiologic tool in this regard, yet to date much of its value remains unrealized. ECG findings characteristic of myocardial ischemia, for example, have not been adequately evaluated in this context. These measures include ST- segment depres

sion and T- wave inversion on the ECG. Because of their clinical value, these ECG findings have also attracted environmental, toxicologic

, and epidemiologic interest. Indeed, they are thought to be relevant in studies focus

ing on arrhythmogenic effects of air pollution (Zareba et al. 2001) and risk factors for sudden death due to cardiac arrhythmia (Huikuri et al. 2001). The literature in this area has never

theless focused on experimentation in animal models of coronary vasoconstriction (Campen

et al. 2005; Godleski et al. 2000; Nikolov et al. 2007; Wellenius et al. 2003) or examinationof typically small, single-city panels of CHDburdened, Holter-monitored male participants during exercise (Gold et al. 2005; Henneberger

et al. 2005; Lanki et al. 2006; Mills et al. 2007; Pekkanen et al. 2002 ; Yue et al. 2007 ). For this reason, epidemiologic evidence linking PM exposure to minor but prognostically important abnormalities of the ST segment and T wave in human populations at rest is quite limited. We therefore designed the present study to investigate the association between acute exposures to ambient PM < 2.5 μm in diam

eter (PM 2.5 

### ) and ECG measures of myocardial ischemia in a relatively large, geographically diverse, healthy female population enrolled in the Women’s Health Initiative (WHI) clinical trials.



## Methods Study design . We examined the associa tion between PM 2.5 

### and ischemia in the Environ

mental Epidemiology of Arrhythmogenesis in WHI (EEAWHI) study , an ancillary study of proarrhythmic mechanisms linking air pollu

tion and CHD among 68,133 WHI clinical trial participants examined at 49 sites. The WHI clinical trial is a multi center study of risk factors for prevention of common causes of mortality, morbidity, and impaired qual

ity of life in U.S. post menopausal women. Details of the study design

, including recruit

ment procedures and selection and exclusion
criteria

, have been published elsewhere ( WHI Study Group 1998). The study was approved by each study site’s institutional review board. All participants provided written informed

consent. Study population. Of the 68,133 WHI clinical trial participants at baseline, we excluded 2,082 (3.1%) with foreign, U.S. mili

tary, U.S

. protectorate, Hawaiian, Alaskan

, or missing addresses; 417 (0.6%) with missing or

poor- quality ECGs; 2

, 379 (3.5%) with ECG QRS duration ≥ 120 ms ec ; and 7,726 (11%)

Address correspondence to Z. Zhang, Epidemiologic Cardiology Research Center (EPICARE), Department of Epidemiology and Prevention, Division of Public Health Sciences, Wake Forest University School ofMedicine, 2000 West First St., Suite 505, WinstonSalem, NC 27104 USA. Telephone: (336) 716-0835. Fax: (336) 716-0834. E-mail: zmzhang@wfubmc.edu

Supplemental Material is available online at http:// www.ehponline.org/members/2009/0800046/suppl.pdf

We acknowledge the contributions of WHI inves

tigators listed in the Short List of WHI Investigators (http://www.whiscience.org/publications/WHI_ investigators_shortlist.pdf).

T h e E n v i r o n m e n t a l E p i d e m i o l o g y o f Arrhythmogenesis in the Women’s Health Initiative (WHI) study is supported by the National Institute of Environmental Health Sciences (5-R01- ES012238); an ancillary study of the WHI pro

gram is funded by the National Heart, Lung, and Blood Institute, Department of Health and Human Services.

The authors declare they have no competing financial interests.

Received 25 July 2008; accepted 23 January 2009. 

# Ambient Fine Particulate Matter Exposure and Myocardial Ischemia in the Environmental Epidemiology of Arrhythmogenesis in the Women’s Health Initiative (EEAWHI) Study

Zhu-ming Zhang, 1 

### Eric A. Whitsel, 2,3 

### P. Miguel Quibrera, 2 

### Richard L. Smith, 4 

### Duanping Liao, 5 

### Garnet L. Anderson, 6 

### and Ronald J. Prineas 1

1 Epidemiologic Cardiology Research Center, Department of Epidemiology and Prevention, Division of Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, North Carolina, USA; 2 Departments of Epidemiology, 3 Medicine, and 4 Statistics and Operations Research, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA; 5 Department of Health Evaluation Sciences, Pennsylvania State University, Hershey, Pennsylvania, USA; 6 Fred Hutchinson Cancer Research Center, Seattle, Washington, USA



### B ackground 

### : Ambient particulate matter (PM) air pollution is associated with coronary heart disease, but the pathways underlying the association remain to be elucidated.

M ethods 

### : We studied the association between PM and ischemia among 57,908 Women’s Health Initiative clinical trial participants from 1999–2003. We used the Minnesota Code criteria to identify ST-segment and T-wave abnormalities, and estimated T amplitude (microvolt) from resting, standard 12-lead electrocardiogram (ECG). We used U.S. Environmental Protection Agency’s monitor data to estimate concentrations of PM < 2.5 μm (PM 2.5 

### ) at geocoded participant addresses over 6 days before the ECGs (lag0 through lag5). We excluded 2,379 women with ECG QRS duration ≥ 120 msec.

R

esults 

### : Overall, 6% of the remaining 55,529 women (52–90 years of age; 83% non-Hispanic white) had ST abnormalities and 16% had T abnormalities. Lead-specific T amplitude was nor

mally distributed (range of means from –14 to 349 μV). PM 2.5 

### (mean ± SD) averaged over lag 0–2 

### was 14 ± 7 μg/m 3 

### . In logistic and linear regression models adjusted for demographic, clinical, tem

poral, and climatic factors, a 10-μg/m 3 

### increase in lag 0–2 

### PM 2.5 

### was associated with a 4% [95% con

fidence interval (CI), –3%, to 10%] increase in the odds of ST abnormality and a 5% (95% CI, 0% to 9%) increase in the odds of T abnormality. We observed corresponding decreases in T amplitude in all exam sites and leads except lead V1, reaching a minimum of –2 μV (95% CI, –5 to 0 μV) in lead V3.

C onclusions 

### : Short-term PM 2.5 

### exposure is associated with ECG evidence of myocardial ischemia among postmenopausal women. The principal manifestations include subclinical but potentially arrhythmogenic ST

– T abnormalities and decreases in T amplitude.

K

ey words 

### : air pollution, cardiovascular disease, electrocardiography, myocardial ischemia, particu

late matter. Environ Health Perspect 117:751–756 (2009). doi:10.1289/ehp.0800046 available via http://dx.doi.org/ [Online 23 January 2009]

### Zhang et al.



### 752 volume 117 | number 5 | May 2009 • 

### Environmental Health Perspectives 

### without an ECG recording between 1999 and 2003, the initial 5 -year period in which PM 2.5 

### data were routinely collected by the U.S. EPA Air Quality System (AQS). The present study focuses on the initial high-quality, resting, stan

dard 12 -lead ECG s recorded during this period among the remaining 55,529 participants, all of whom had addresses in the contiguous United States

. ECG methodology. Identical ECGs (MAC PC, Marquette Electronics, Inc., Milwaukee, WI ) were used in all clinic sites

, and resting, standard 12 -lead ECGs were recorded for all participants using strictly standardized pro

cedures. The chest electrodes were located in precise positions. All ECGs were processed in a central ECG laboratory (Epidemiological Cardiology Research Center

, Wake Forest University, Winston-Salem, NC), where they were visually inspected for technical errors and inadequate quality. The ECGs were initially processed with the Dalhousie ECG program

, and for the present study we reprocessed them with the 2001 version of the GE Marquette 12-SL program ( GE Healthcare 2008; Prineas

et al. 1982; Rautaharju et al. 1998). The Marquette measurement matrix contained sev

eral ECG measures of myocardial ischemia that

we used as outcome variables in this study

. ST- segment and T- wave amplitudes (microvolt). We defined lead -specific depth (or height) of the ST segment (ST) 60 ms ec after the J point and T- wave amplitude (T) relative to the isoelectric line. ST, T, and ST

– T abnormalities. We applied Minnesota Code (MC) criteria to the former interval-scale measures to identify ST abnormality (MC 4.1–4.4), T abnormality (MC 5.1–5.4), or any ST

–

T abnormality (MC 4.1–4.4 or MC 5.1–5.4) (Prineas et al. 1982). QRS/T angles (degrees). The frontal plane QRS/T angle was defined as the abso

lute value of the difference between the frontal plane QRS and T axes (range

, –89° to 270°). When > 180°, it was adjusted to the minimal angle as follows: 360° – frontal plane QRS/T angle (Zhang et al. 2007). We defined the spatial QRS/T angle as the angle between the mean QRS and T vectors, which we calcu

lated from quasi-orthogonal X, Y

, and Z leads reconstructed from the standard ECG leads via matrix transformation (Rautaharju et al. 2006 b ). Air pollutant concentrations, weather vari

ables

, and other participant characteristics. We obtained all ambient PM 2.5 

### concentra

tion data recorded at monitors operating in the contiguous United States during the study from the U.S. EPA AQS. The data included the longitude and latitude of each monitor. We used a semi automated program built on ArcView GIS ( version 8.3) software and its Geostatistical Analyst extension (ESRI, Inc. Redlands, CA) to produce kriging-estimated daily mean concentrations (and their SEs) at each geocoded participant and exam site address from the baseline examination through 2004 (Liao et al. 2006

, 2007; Whitsel et al. 2006). The program relied on a spherical model to perform national-scale, lognormal ordinary kriging and the weighted least-squares method to estimate semivariograms, and ran and cross-validated each daily semivariogram. From the kriging-estimated, daily mean, loca

tion-specific PM 2.5 

### concentrations, we then computed a matrix of 15 short-term pollut

ant exposures by averaging within over

lapping 1-

, 2

- , and 3 -day lag combinations inside a 6 -day exposure window beginning 5 days before and ending on the examination date, that is, days 0–5. A ssociations between PM and ischemia were strongest on days 0–2 (lag 0–2 

### ), the emphasis of the present report. We obtained all meteorologic data recorded at relevant stations and times from the National Climatic Data Center (U.S. National Climatic Data Center 2007) : ambi

ent temperature (degrees centigrade), dew point (degrees centigrade)

, and barometric pressures (kilo pascal), as well as station lon

gitudes, latitudes, and altitudes. Daily mean temperature, dew point

, and pressure at each geocoded participant and exam site address from baseline to closeout were estimated by averaging daily means across all stations within50 km, a distance over which their stationto-station correlations exceed 0.90 (Ito et al. 2001). Thereafter, we computed weather variables at lag 0–2 

### /lag 3–5 

### as described above for PM 2.5 

### . Self-reported education, medication use, health history

, and a variety of other attributes were determined at each visit by standardized participant interview and examination by the WHI staff. Interim health events were iden

tified via standardized medical record review and physician adjudication. Specifically, diabe

tes was defined by anti diabetic medication use or history; hypertension by anti hypertensive medication use, systolic blood pressure (SBP)

≥ 140 mmHg, diastolic blood pressure (DBP)

≥ 90 mmHg, or history; body mass index (BMI) as the ratio of weight ( kilograms) to height (square meters) ; hypercholesterolemia by
anti hyperlipidemic medication use or history; smoking as current, former, or never; chronic lung disease by history of asthma, emphysema

, or lung cancer; CHD by anti anginal medica

tion use, history of angina

, or myocardial infarc

tion and medical record review/adjudication; revascularization by history of coronary artery angioplasty, stent

, or bypass and medical record review/adjudication; and congestive heart fail

ure by cardiac glycoside/diuretic use, history

, and medical record review/adjudication. Statistical analysis methods. We inspected frequency distributions of all variables for out

liers but did not identify influential values. **Table 1.** The d emographic and c linical c har ac

teristics of the study population on the date of ECG examination ( n = 55,529)

. Characteristic Mean ± SD or percent
Age in years on ECG exam date 67 ± 7 Race White 83 Black 10 Other 7 Education < college 23 BMI (kg/m 2 ) 29 ± 6 SBP (mmHg) 126 ± 17 DBP (mmHg) 73 ± 9 Hypertension 52 Hypercholesterolemia 20 Diabetes 8 Current smoking 6 CHD a 11 Chronic lung disease 10 Beta-blocker use 13 Exam season Spring 27 Summer 26 Fall 25 Winter 22 Exam day Monday–Thursday 86 Friday 12 Saturday–Sunday 2 Exam time Morning 64 Afternoon 36

**a** CHD includes congestive heart failure, coronary revas

cularization, or myocardial infarction by Minnesota Code or Novacode

. **Table 2** 

**.** The ECG p arameters of the study population on the date of ECG examination ( n

= 55,529)

. ECG parameter Mean ± SD or percent

Minnesota codes MC 4 a 6 MC 5 b 16 MC 4 or MC 5 c 18 T-wave amplitude (μV)

Lead I 202 ± 105 Lead II 241 ± 105 Lead aVL 86 ± 93 Lead V1 –14 ± 116 Lead V2 313 ± 197 Lead V3 349 ± 203 Lead V4 324 ± 193 Lead V5 284 ± 167 Lead V6 221 ± 126 ST-segment amplitude (μV)

Lead I 13 ± 21 Lead II 19 ± 25 Lead aVL 4 ± 17 Lead V1 27 ± 27 Lead V2 64 ± 46 Lead V3 47 ± 41 Lead V4 29 ± 35 Lead V5 18 ± 29 Lead V6 11 ± 23 QRS/T angles and heart rate

Heart rate (beats/min) 66 ± 10 QRS/T angle–spatial (°) 60 ± 28 QRS/T angle–frontal plane (°) 29 ± 27

a Any ST abnormality (MC 4.1–4.4). b A ny T abnormal- ny T abnormal

ity ( MC 5.1–5.4). c Any ST– T abnormality (MC 4.1–4.4 or MC 5.1–5.4)

.

### PM 2.5 

### and myocardial ischemia

Environmental Health Perspectives • volume 117 | number 5 | May 2009 

### 753 Initially ignoring the influences of exam site, we explored the associations between ischemia and PM 2.5 

### in unadjusted linear and logistic regression models. To control for residual con

founding by exam season, day of week, time of day, health, and weather, we added tempo

ral, demographic, clinical

, and meteorologic charac teristics to the models. We then con

ducted hierarchical analyses in two stages. In the first stage we used site-specific, adjusted regression models to estimate strength of the ischemia

– PM 2.5 

### associations. The models allowed these estimates to vary among sites. In the second stage we used random effects meta-regression of the site-specific, linear regression coefficients from the first stage to estimate overall strength of the ischemia

– PM associations across sites. These weighted, itera

tive regression models allowed for an additive, between-study component of residual variance estimated via restricted maximum likelihood (Berkey et al. 1995). We repeated the secondstage analyses by placing uninformative priors on the second- stage parameters and Monte Carlo sampling from the conditional distribu

tion of each unknown using standard Bayesian hierarchical regression algorithms (Robert and Casella 2004). We evaluated effect meas

ure modification by including cross-product terms for the interaction between PM 2.5 

### and CHD and its major risk factors at the first stage. Analyses based on logistic and linear regression models adjusting for exam site, and both the random-effects meta-analyses and Bayesian hierarchical regression analyses of the adjusted, site-specific regression coefficients produced similar results. W e conducted all analyses using SAS version 9.1 (SAS Institute

, Inc., Cary

, NC) and MATLAB, version 7.0, software (MathWorks, Inc., Natick, MA). By convention, we report resulting estimates as odds ratios for ST, T

, and ST

– T abnormali

ties, or microvolt ( μV ) changes in ST- segment and T- wave amplitudes associated with
10 μg/m 3 

### increases in PM 2.5 

### concentrations. 

## Results Of the 55,529 female participants (age range

, 52

– 90 years), 83% were non-Hispanic white, 52% hypertensive

, and 20% hyper

cholesterolemia (Table 1). Somewhat smaller percentages were current smokers (6%) or had diabetes (8%), CHD (11%), or chronic lung disease (10%). Six percent of the study population had ST abnormalities, and 16% had T abnormalities. Lead-specific ST and T amplitudes were normally distributed ( range of means = 4, 64 μV and –14, 349 μV, respectively ) . Mean ± SD spatial and fron

tal plane QRS/T angles were 60° ± 28° and 29° ± 27°, with heart rate 66 ± 10 beats /min ( Table 2 ). Mean PM 2.5 

### averaged over the first 3 days and second 3 days preceding the ECG (lag 0–2 

### and lag 3–5 

### ) were equivalent, as were mean temperature, dew point

, and barometric pressure ( Table 3 ). In logistic and linear regression models adjusted for demographic, clinical, tempo

ral

, and climatic factors, 10 μg/m 3 

### increases in lag 0–2 

### PM 2.5 

### were associated with 4

– 5% increases in odds ratios (ORs) for ST, T

, and ST

– T abnormalities, small decreases in lead-specific ST and T amplitudes, and slight increases in the QRS/T angles and heart rate ( Table 4 ). We observed decreases in T amplitude in all leads except V1, reaching a minimum of –2.3 μV [95% confidence inter

val (CI), –5.2 to 0.5 μV] in lead V3 even after controlling for its reported dependence on heart rate (Couderc et al. 2007). These observations were consistent across exam sites ( Figure 1 ). The observed magnitude and direc

tion of effects associated with lag 3–5 

### PM 2.5 

### were often weaker and less consistent [ Table 4 and Supplemental Material, Tables 1 and 2 (available online at http://www.ehponline. org/members/2009/0800046/suppl.pdf)]

. Findings based on unadjusted models and those controlling for randomization status aswell as additional participant- and contextuallevel measures of education, occupation,
income

, and housing were comparable. Effects of lag 0–2 

### PM 2.5 

### were slightly
stronger among users versus non users of beta -blockers: 10% (1%, 20%) versus 3% (

– 1%, 8%) increases in the odds of T abnor

mality ( p = 0.098) and –8 (

– 15, –1) versus –2 (

– 4, 1) μV decreases in T amplitude in lead V3 ( p = 0.076), but in general, there was little suggestion of effect measure modification by CHD or its major risk factors.



## Discussion Judging from the U.S. EPA ’s Provisional Assessment of Recent Studies on Health Effects of Particulate Matter Exposure ( National Center for Environmental Assessment 2006), interest in subclinical, atherosclerotic manifestations of long-term ambient PM 2.5 

### exposure has dramatically increased. Indeed,

**Table 3** 

**.** PM concentrations and weather vari

ables for the study population on the date of ECG examination

. Characteristic Mean ± SD

PM 2.5 a

Lag 0 14.1 ± 8 Lag 1 13.8 ± 8 Lag 2 13.8 ± 8 Lag 3 13.8 ± 8 Lag 4 13.9 ± 8 Lag 5 14.1 ± 8 Lag 0–2 b 13.9 ± 7 Weather

Temperature lag 0–2 b 13.9 ± 9 Dew point lag 0–2 b 7.6 ± 9 Barometric pressure lag 0–2 b 102 ± 1

a Concentrations at geocoded participant addresses on day of exam (lag 0 ) and preceding 5 days ( lag 1 –5 ). b The

mean ± SD for PM 2.5 and weather variables were the same at lag 3 –5
. **Table 4** 

**.** Multivariable-a djusted a ORs and changes (95% CI ) per 10-μ g /m 3 increase in PM 2.5

. ECG parameter Lag 0–2 (95% CI) Lag 3–5 (95% CI)

Minnesota Codes (OR ) MC 4 b 1.04 (0.97 to 1.10) 1.04 (0.98 to 1.11) MC 5 c 1.05 (1.00 to 1.09) 1.04 (1.00 to 1.08) MC 4 or MC 5 d 1.0 4 (1.00 to 1.09) 1.0 3 ( 0.99 to 1.07) ST-segment amplitude ( μ V, change)

Lead I –0.0 7 (–0.3 6 to 0.21) 0.1 8 (–0.1 0 to 0.4 6 ) Lead II –0.12 (–0.47 to 0.23) 0.1 6 (–0.1 8 to 0. 50 ) Lead aVL –0.0 1 (–0.2 5 to 0.2 3 ) 0.1 1 (–0.1 2 to 0.3 4 ) Lead V1 –0.0 2 (–0. 39 to 0.3 5 ) –0.2 2 (–0.5 8 to 0.1 4 ) Lead V2 0.0 7 (–0. 57 to 0. 70 ) –0.0 1 (–0.6 1 to 0.6 2 ) Lead V3 –0.1 1 (–0. 68 to 0.4 7 ) –0.0 2 (–0. 58 to 0.5 4 ) Lead V4 –0.0 3 (–0.5 1 to 0.4 5 ) 0.2 4 (–0.2 3 to 0. 71 ) Lead V5 –0.0 1 (–0.4 1 to 0.3 9 ) 0.3 5 (–0.0 4 to 0.7 4 ) Lead V6 0.0 2 (–0.30 to 0.3 3 ) 0.3 5 ( 0.0 4 to 0.6 5 ) T-wave amplitude ( μ V, change)

Lead I –1.6 0 (–3.0 7 to –0.1 3 ) –0.3 1 (–1.7 3 to 1. 11 ) Lead II –0.5 4 (–1.9 9 to 0.9 2 ) 0.7 1 (–0.7 0 to 2.1 3 ) Lead aVL –1.2 1 (–2.5 0 to 0. 10 ) –0.5 5 (–1.8 1 to 0. 71 ) Lead V1 1.4 5 (–0.1 6 to 3.0 6 ) 0.0 3 (–1.5 3 to 1.5 9 ) Lead V2 –0. 18 (– 2.96 to 2. 60 ) 0. 57 (–2. 1 2 to 3. 27 ) Lead V3 –2. 33 (–5. 15 to 0. 49 ) –0. 1 3 (–2. 8 7 to 2. 60 ) Lead V4 –2. 03 (–4. 69 to 0. 63 ) 0. 64 (– 1.94 to 3. 22 ) Lead V5 –1.9 2 (–4.2 2 to 0.3 8 ) 0.5 5 (–1. 69 to 2.7 8 ) Lead V6 –0.63 (–2.36 to 1.10) 0.8 2 (–0.8 6 to 2.4 9 ) QRS/T angles and heart rate (change) QRS/T angle–spatial (°) 0.1 9 (–0.2 1 to 0.5 9 ) –0.20 (–0.59 to 0.1 9 ) QRS/T angle– frontal plane (°) 0.13 (–0.2 4 to 0.50) 0.35 (–0.01 to 0.71) Heart rate (beats/min) 0.16 ( 0.02 to 0.30) 0.04 (–0.10 to 0.18)

a Estimates based on logistic and linear regression models adjusted for demographic, clinical, and weather variables: age ; race/ethnicity ; education ; exam site ; BMI ; current smoking status ; history of CHD, diabetes, hypertension, SBP, chronic lung disease, or hypercholesterolemia; day of week ; time of day ; temperature ; dew point ; pressure and season ; b Any ST abnormality (MC 4.1–4.4). c A ny T abnormality ( MC 5.1–5.4). d Any ST– T abnormality (MC 4.1–4.4 or MC 5.1–5.4).

### Zhang et al.



### 754 volume 117 | number 5 | May 2009 • 

### Environmental Health Perspectives 

### the July 2006 assessment included only one such study (of coronary artery calcium), yet in the interim, several others have also exam

ined associations between PM 2.5 

### exposures sustained over months to years and non in

vasive measures of atherosclerosis

, including carotid intimal-medial thickness, abdominal aortic calcification

, and ankle-brachial index (Allen et al. 2009; Diez Roux et al. 2008; Hoffmann et al. 2007; Kunzli et al. 2005). The epidemiologic associations observed in these studies are not entirely consistent with one another or collectively as strong as those that may have been anticipated on the basis of recently reported associations between chronic PM exposure and cardiovascular dis

ease (e.g.

, Miller et al. 2007), and the role of atherosclerotic mechanisms in the associa

tion remains uncertain. We examined the role of acute, ischemic mechanisms in the association between PM 2.5 

### and CHD among WHI clinical trial partic

ipants with this uncertainty in mind , using ECG— a simple, non invasive, and underused research tool. In this epidemiologic context, however, we did not limit the examination to characteristics of clinically manifest ischemia ( e.g. , ≥ 0.1 m V of downsloping ST segment depression and/or deep, symmetrical, pre

cordial T- wave inversion ) . We opted instead to include minor abnormalities of ventricu

lar repolarization (ST

– T abnormalities

, ST and T amplitudes) and depolarization (QRS/T angles) to increase sensitivity of the ECG for sub clinical forms of myocardial ischemia. Using this tool, we found that a 10 μg/m 3 

### increment in lag 0–2 

### PM 2.5 

### is associated with 4

– 5% increased odds of minor ST, T

, and ST

–

T abnormalities

, small decreases in ST and T amplitudes across most leads and exam sites

, and corresponding increases in QRS/T angles. Previous findings from the WHI clinical trials cohort include significant prospective relationships between isolated ST

– T abnor

malities, lead-specific ST and T amplitudes, and wide QRS/T angle at baseline

, and CHD mortality, incident CHD

, and congestive heart failure (Rautaharju et al. 2006 b ). Similar find

ings also have been described in populationbased settings, such as the Atherosclerosis Risk in Communities study (Zhang et al. 2007), Cardiovascular Health Study (Rautaharju et al. 2006 a ), and Chicago Western Electric Study (Daviglus et al. 1999), among others (Engel

et al. 2004; Larsen et al. 2002; Okin et al. 2005

, 2007; Schouten et al. 1992). However, the clinical utility of these ECG measures remains limited. Considering the consistent associations between PM 2.5 

### and the ECG measures of myocardial ischemia observed in this context and the established, prospective association of these measures with CHD, the findings from the present study provide additional support for the hypothesis that subclinical myocardial ischemia has a pathophysiologic role in the adverse effects of acute exposure to PM 2.5 

### on the heart, including predisposition to ven

tricular arrhythmogenesis and sudden cardiac death (Rubart and Zipes 2005). This is the first study to examine such an association in a large

popu lation of postmenopausal women. Indeed, prior studies have focused on either animal models of coronary vasoconstriction (Campen

et al. 2005; Godleski et al. 2000; Nikolov et al. 2007; Wellenius et al. 2003) or typically small,single-city panels of CHD-burdened, Holtermonitored male participants during exercise (Gold et al. 2005; Henneberger et al. 2005; Lanki et al. 2006; Mills et al. 2007; Pekkanen

et al. 2002; Yue et al. 2007) (Table 5 ). The findings described herein are nonetheless con

sistent with and thereby extend the findings previously described in these populations. They do not imply, however, that ischemia is the sole process by which PM 2.5 

### exerts its adverse effects on the heart. Autonomic, thrombotic, endothelial, inflammatory, oxidative , and other mechanisms of disease have all been implicated in cardiovascular effects of PM (Chuang et al. 2007; Mills et al. 2007). This study has several limitations that may affect interpretation of its findings. First, it is an ancillary study of participants in the WHI clinical trials. Inference is therefore limited to postmenopausal women 52–90 years of age liv

ing in the contiguous 48 United States between 1999 and 2003, the initial 5 -year period dur

ing which PM 2.5 

### data were routinely collected by the U.S. EPA AQS. Because women in the WHI clinical trials were randomized to
estrogen with or without progestin treatment, **Table 5** 

**.** Human studies of association of PM and ischemia.
Mean age Detection Reference No. Location (years) Female (%) Outcomes method

Pekkanen et al. 2002 45 Helsinki, Finland 68 47 STD E Holter Henneberger et al. 2005 56 Efurt, Germany 66 0 TWA R Holter Gold et al. 2005 24 Boston, MA, USA 73 75 STD E Holter Lanki et al. 2006 45 Helsinki, Finland 68 47 STD E Holter Yue et al. 2007 56 Efurt, Germany 66 0 TWA R Holter Mills et al. 2007 20 Southampton, UK 60 0 STD E Holter Zhang et al. 2008 55

, 529 4 9 exam sites a 67 100 STT, ST A, TWA R esting ECG

Abbreviations: E

, exercise; R, rest; STA

, ST-segment amplitude; STD

, ST-segment depression; STT

, ST-segment and T-wave abnormalities; TWA

, T-wave amplitude. ECG involved resting, supine, standard 12-lead ECG.

a In the contiguous United States

. **Figure 1.** Multivariable-adjusted ORs for ST

– T abnormality and changes in T amplitude (μV) in lead V3 (95% CI ) per 10-μ g /m 3 increase in lag 0–2 PM 2.5 , by exam site. We based estimates on Bayesian hierarchical regression models adjusted for demographic, clinical, and weather variables: age ; race/ethnicity ; education ; BMI ; current smoking status ; history of CHD, diabetes, hypertension, SBP, chronic lung disease, or hypercholesterolemia ; season ; day of week ; time of day ; temperature ; dew point ; and pressure. Nevada Portland To rrance Cincinnat i Chicago Rush GWU Iowa City T ucson Wo rcester

Chicago Jacksonville Milwaukee Birmingham

Madiso n Memphi s Stanfor d Pawtucket Memphis satellite Davenpor t

La Jolla Seattle Minneapolis

Housto n Buffalo Newar k New Yo rk Pittsburgh

Phoeni x Winston-Salem

Chapel Hill Los Angeles San Antoni o Winston-Salem Satellite Fall River

Miam i Oakland Chula Vist a

Evanston Stony Brook Des Moines

Gainsville Columbus

Irvin e New Brunswick Boston Medsta r Detroit Davi s Atlant a Davi s Fall Rive r

GWU Birmingham

Nevada San Antoni o New Brunswick

Milwaukee Memphi s Iowa City Madison Stanfor d Memphis Satellite Houston

Irvin e Evanston

Boston Pittsburgh Chula Vist a Pawtucket Jacksonville Chicago Rush Phoeni x Cincinnat i Des Moines

Buffalo Winston-Salem satellite Miam i T ucson Chicago New Yo rk Winston-Salem Detroit Stony Brook

To rrance Davenpor t Chapel Hill Gainsville Minneapolis

Newar k La Jolla Medstar Oakland Los Angeles

Atlant a Wo rceste r

Seattle Columbus Portland

1.0 0.95 1.05 1.10 1.15 –10 –5 0 5 **OR μV**  1.04 (1.00, 1.09) –2.20 (–5.38,1.06) All site s A ll site s

### PM 2.5 

### and myocardial ischemia

Environmental Health Perspectives • volume 117 | number 5 | May 2009 

### 755 calcium/vitamin D supplementation, and/or dietary modification, these exposures could have affected the ECG measures examined in this setting. Because ambient PM 2.5 

### con

centrations also decreased 11% in the United States between 2000 and 2007 (U.S. EPA 2008a), observed associations between PM and ischemia could be weaker if this study were repeated today. Findings were nevertheless robust to adjustment for randomization status. Moreover, seasonally weighted annual average PM 2.5 

### concentrations in the United States still exceed the 15 μg/m 3 

### national ambient air qual

ity standard at approximately 10% of trend sites (U.S. EPA 2008b). Second, we did not measure PM 2.5 

### in the personal breathing space of participants. Instead, it was spatially interpolated at each participant’s geocoded address, raising ques

tions about its validity (Szpiro et al. 2007). Third, the associations described herein also may be subject to residual socioeconomic confounding because we defined diabetes and hypercholesterolemia by self-reported history of the disease and/or use of antihyperlipidemic or antidiabetic medications rather than fasting glucose or lipid concentrations, which were only available for 6% site- and race-stratified minority participant over sample. In the face of these additional limitations, in this study we took several precautions. We carefully established the validity of the geo

codes relative to criterion standards (Whitsel

et al. 2006) and the spatial interpolations using standard cross-validation statistics: the prediction error (PE = predicted minus meas

ured pollutant concentration at each moni

tor site), standardized prediction error (SPE = PE divided by its estimated standard error), root mean square standardized error (RMSS = standard deviation of SPE across sites), root mean square prediction error (RMS = empiri

cal standard error based on the mean square of the predictions), and mathematically calculated standard error (SE). Observed values of PE and SPE near 0 and RMSS near 1 , and similarity of RMS and SE provide evidence of model valid

ity (Liao et al. 2006

, 2007). In addition, the study documented modest effects of geo coding and kriging error on PM

– CHD associations (Crooks et al. 2008; Whitsel et al. 2006). Finally, the study demonstrated high reliability of treated diabetes and hypercholesterolemia (Langer et al. 2003)

, and we adjusted effectsizes for additional participant- and contextuallevel measures of socio economic status, noting only small changes as a result of adjustment.



## Conclusion We conclude that short-term exposure to PM 2.5 

### is associated with ECG evidence of myocardial ischemia among postmenopausal women. The principal manifestations include ST- segment and T- wave abnormalities, decreases in ST segment and T amplitude, and increases in QRS/T angles. These findings sug

gest that the adverse effects of PM 2.5 

### on CHD risk among postmenopausal women may be related to its subclinical, ischemic effects on the myocardium.

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